wip: dump waaaaaay too much stuff

2022-12-15 17:11:00 +01:00
562 changed files with 16223 additions and 110463 deletions
--- a/.cargo/config.toml
+++ b/.cargo/config.toml
@ -1,3 +0,0 @@
 [target.x86_64-unknown-linux-gnu]
 linker = "clang"
 rustflags = ["-C", "link-arg=-fuse-ld=mold"]
--- a/.drone.yml
+++ b/.drone.yml
@ -0,0 +1,288 @@
 ---
 kind: pipeline
 name: default
 node:
  nix-daemon: 1
 steps:
  - name: check formatting
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-shell --attr rust --run "cargo fmt -- --check"
  - name: build
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr clippy.amd64 --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
  - name: unit + func tests
    image: nixpkgs/nix:nixos-22.05
    environment:
      GARAGE_TEST_INTEGRATION_EXE: result-bin/bin/garage
    commands:
      - nix-build --no-build-output --attr clippy.amd64 --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
      - nix-build --no-build-output --attr test.amd64
      - ./result/bin/garage_db-*
      - ./result/bin/garage_api-*
      - ./result/bin/garage_model-*
      - ./result/bin/garage_rpc-*
      - ./result/bin/garage_table-*
      - ./result/bin/garage_util-*
      - ./result/bin/garage_web-*
      - ./result/bin/garage-*
      - ./result/bin/integration-*
      - rm result
  - name: integration tests
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr clippy.amd64 --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr integration --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
 trigger:
  event:
  - custom
  - push
  - pull_request
  - tag
  - cron
 ---
 kind: pipeline
 type: docker
 name: release-linux-amd64
 node:
  nix-daemon: 1
 steps:
  - name: build
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr pkgs.amd64.release --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr rust --run "./script/not-dynamic.sh result-bin/bin/garage"
  - name: integration
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-shell --attr integration --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
  - name: push static binary
    image: nixpkgs/nix:nixos-22.05
    environment:
      AWS_ACCESS_KEY_ID:
        from_secret: garagehq_aws_access_key_id
      AWS_SECRET_ACCESS_KEY:
        from_secret: garagehq_aws_secret_access_key
      TARGET: "x86_64-unknown-linux-musl"
    commands:
      - nix-shell --attr release --run "to_s3"
  - name: docker build and publish
    image: nixpkgs/nix:nixos-22.05
    environment:
      DOCKER_AUTH:
        from_secret: docker_auth
      DOCKER_PLATFORM: "linux/amd64"
      CONTAINER_NAME: "dxflrs/amd64_garage"
      HOME: "/kaniko"
    commands:
      - mkdir -p /kaniko/.docker
      - echo $DOCKER_AUTH > /kaniko/.docker/config.json
      - export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr release --run "to_docker"
 trigger:
  event:
  - promote
  - cron
 ---
 kind: pipeline
 type: docker
 name: release-linux-i386
 node:
  nix-daemon: 1
 steps:
  - name: build
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr pkgs.i386.release --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr rust --run "./script/not-dynamic.sh result-bin/bin/garage"
  - name: integration
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-shell --attr integration --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
  - name: push static binary
    image: nixpkgs/nix:nixos-22.05
    environment:
      AWS_ACCESS_KEY_ID:
        from_secret: garagehq_aws_access_key_id
      AWS_SECRET_ACCESS_KEY:
        from_secret: garagehq_aws_secret_access_key
      TARGET: "i686-unknown-linux-musl"
    commands:
      - nix-shell --attr release --run "to_s3"
  - name: docker build and publish
    image: nixpkgs/nix:nixos-22.05
    environment:
      DOCKER_AUTH:
        from_secret: docker_auth
      DOCKER_PLATFORM: "linux/386"
      CONTAINER_NAME: "dxflrs/386_garage"
      HOME: "/kaniko"
    commands:
      - mkdir -p /kaniko/.docker
      - echo $DOCKER_AUTH > /kaniko/.docker/config.json
      - export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr release --run "to_docker"
 trigger:
  event:
  - promote
  - cron
 ---
 kind: pipeline
 type: docker
 name: release-linux-arm64
 node:
  nix-daemon: 1
 steps:
  - name: build
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr pkgs.arm64.release --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr rust --run "./script/not-dynamic.sh result-bin/bin/garage"
  - name: push static binary
    image: nixpkgs/nix:nixos-22.05
    environment:
      AWS_ACCESS_KEY_ID:
        from_secret: garagehq_aws_access_key_id
      AWS_SECRET_ACCESS_KEY:
        from_secret: garagehq_aws_secret_access_key
      TARGET: "aarch64-unknown-linux-musl"
    commands:
      - nix-shell --attr release --run "to_s3"
  - name: docker build and publish
    image: nixpkgs/nix:nixos-22.05
    environment:
      DOCKER_AUTH:
        from_secret: docker_auth
      DOCKER_PLATFORM: "linux/arm64"
      CONTAINER_NAME: "dxflrs/arm64_garage"
      HOME: "/kaniko"
    commands:
      - mkdir -p /kaniko/.docker
      - echo $DOCKER_AUTH > /kaniko/.docker/config.json
      - export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr release --run "to_docker"
 trigger:
  event:
  - promote
  - cron
 ---
 kind: pipeline
 type: docker
 name: release-linux-arm
 node:
  nix-daemon: 1
 steps:
  - name: build
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr pkgs.arm.release --argstr git_version ${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr rust --run "./script/not-dynamic.sh result-bin/bin/garage"
  - name: push static binary
    image: nixpkgs/nix:nixos-22.05
    environment:
      AWS_ACCESS_KEY_ID:
        from_secret: garagehq_aws_access_key_id
      AWS_SECRET_ACCESS_KEY:
        from_secret: garagehq_aws_secret_access_key
      TARGET: "armv6l-unknown-linux-musleabihf"
    commands:
      - nix-shell --attr release --run "to_s3"
  - name: docker build and publish
    image: nixpkgs/nix:nixos-22.05
    environment:
      DOCKER_AUTH:
        from_secret: docker_auth
      DOCKER_PLATFORM: "linux/arm"
      CONTAINER_NAME: "dxflrs/arm_garage"
      HOME: "/kaniko"
    commands:
      - mkdir -p /kaniko/.docker
      - echo $DOCKER_AUTH > /kaniko/.docker/config.json
      - export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr release --run "to_docker"
 trigger:
  event:
  - promote
  - cron
 ---
 kind: pipeline
 type: docker
 name: refresh-release-page
 node:
  nix-daemon: 1
 steps:
  - name: multiarch-docker
    image: nixpkgs/nix:nixos-22.05
    environment:
      DOCKER_AUTH:
        from_secret: docker_auth
      HOME: "/root"
    commands:
      - mkdir -p /root/.docker
      - echo $DOCKER_AUTH > /root/.docker/config.json
      - export CONTAINER_TAG=${DRONE_TAG:-$DRONE_COMMIT}
      - nix-shell --attr release --run "multiarch_docker"
  - name: refresh-index
    image: nixpkgs/nix:nixos-22.05
    environment:
      AWS_ACCESS_KEY_ID:
        from_secret: garagehq_aws_access_key_id
      AWS_SECRET_ACCESS_KEY:
        from_secret: garagehq_aws_secret_access_key
    commands:
      - mkdir -p /etc/nix && cp nix/nix.conf /etc/nix/nix.conf
      - nix-shell --attr release --run "refresh_index"
 depends_on:
  - release-linux-amd64
  - release-linux-i386
  - release-linux-arm64
  - release-linux-arm
 trigger:
  event:
  - promote
  - cron
 ---
 kind: signature
 hmac: ac09a5a8c82502f67271f93afa1e1e21ce66383b8e24a6deb26b285cc1c378ba
 ...
--- a/.envrc
+++ b/.envrc
@ -1 +0,0 @@
 use flake
--- a/.gitignore
+++ b/.gitignore
@ -3,4 +3,3 @@
 /pki
 **/*.rs.bk
 *.swp
 /.direnv
--- a/.woodpecker/debug.yaml
+++ b/.woodpecker/debug.yaml
@ -1,47 +0,0 @@
 when:
  event:
  - push
  - tag
  - pull_request
  - deployment
  - cron
  - manual
 steps:
  - name: check formatting
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-shell --attr devShell --run "cargo fmt -- --check"
  - name: build
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr clippy.amd64 --argstr git_version ${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
  - name: unit + func tests
    image: nixpkgs/nix:nixos-22.05
    environment:
      GARAGE_TEST_INTEGRATION_EXE: result-bin/bin/garage
      GARAGE_TEST_INTEGRATION_PATH: tmp-garage-integration
    commands:
      - nix-build --no-build-output --attr clippy.amd64 --argstr git_version ${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
      - nix-build --no-build-output --attr test.amd64
      - ./result/bin/garage_db-*
      - ./result/bin/garage_api-*
      - ./result/bin/garage_model-*
      - ./result/bin/garage_rpc-*
      - ./result/bin/garage_table-*
      - ./result/bin/garage_util-*
      - ./result/bin/garage_web-*
      - ./result/bin/garage-*
      - GARAGE_TEST_INTEGRATION_DB_ENGINE=lmdb ./result/bin/integration-* || (cat tmp-garage-integration/stderr.log; false)
      - nix-shell --attr ci --run "killall -9 garage" || true
      - GARAGE_TEST_INTEGRATION_DB_ENGINE=sqlite ./result/bin/integration-* || (cat tmp-garage-integration/stderr.log; false)
      - rm result
      - rm -rv tmp-garage-integration
  - name: integration tests
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr clippy.amd64 --argstr git_version ${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
      - nix-shell --attr ci --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
--- a/.woodpecker/publish.yaml
+++ b/.woodpecker/publish.yaml
@ -1,29 +0,0 @@
 when:
  event:
  - deployment
  - cron
 depends_on:
  - release
 steps:
  - name: refresh-index
    image: nixpkgs/nix:nixos-22.05
    secrets:
      - source: garagehq_aws_access_key_id
        target: AWS_ACCESS_KEY_ID
      - source: garagehq_aws_secret_access_key
        target: AWS_SECRET_ACCESS_KEY
    commands:
      - mkdir -p /etc/nix && cp nix/nix.conf /etc/nix/nix.conf
      - nix-shell --attr ci --run "refresh_index"
  - name: multiarch-docker
    image: nixpkgs/nix:nixos-22.05
    secrets:
      - docker_auth
    commands:
      - mkdir -p /root/.docker
      - echo $DOCKER_AUTH > /root/.docker/config.json
      - export CONTAINER_TAG=${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
      - nix-shell --attr ci --run "multiarch_docker"
--- a/.woodpecker/release.yaml
+++ b/.woodpecker/release.yaml
@ -1,70 +0,0 @@
 when:
  event:
  - deployment
  - cron
 matrix:
  include:
    - ARCH: amd64
      TARGET: x86_64-unknown-linux-musl
    - ARCH: i386
      TARGET: i686-unknown-linux-musl
    - ARCH: arm64
      TARGET: aarch64-unknown-linux-musl
    - ARCH: arm
      TARGET: armv6l-unknown-linux-musleabihf
 steps:
  - name: build
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr pkgs.${ARCH}.release --argstr git_version ${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
  - name: check is static binary
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-build --no-build-output --attr pkgs.${ARCH}.release --argstr git_version ${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
      - nix-shell --attr ci --run "./script/not-dynamic.sh result-bin/bin/garage"
  - name: integration tests
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-shell --attr ci --run ./script/test-smoke.sh || (cat /tmp/garage.log; false)
    when:
      - matrix:
          ARCH: amd64
      - matrix:
          ARCH: i386
  - name: upgrade tests
    image: nixpkgs/nix:nixos-22.05
    commands:
      - nix-shell --attr ci --run "./script/test-upgrade.sh v0.8.4 x86_64-unknown-linux-musl" || (cat /tmp/garage.log; false)
    when:
      - matrix:
          ARCH: amd64
  - name: push static binary
    image: nixpkgs/nix:nixos-22.05
    environment:
      TARGET: "${TARGET}"
    secrets:
      - source: garagehq_aws_access_key_id
        target: AWS_ACCESS_KEY_ID
      - source: garagehq_aws_secret_access_key
        target: AWS_SECRET_ACCESS_KEY
    commands:
      - nix-shell --attr ci --run "to_s3"
  - name: docker build and publish
    image: nixpkgs/nix:nixos-22.05
    environment:
      DOCKER_PLATFORM: "linux/${ARCH}"
      CONTAINER_NAME: "dxflrs/${ARCH}_garage"
    secrets:
      - docker_auth
    commands:
      - mkdir -p /root/.docker
      - echo $DOCKER_AUTH > /root/.docker/config.json
      - export CONTAINER_TAG=${CI_COMMIT_TAG:-$CI_COMMIT_SHA}
      - nix-shell --attr ci --run "to_docker"
--- a/Cargo.lock
+++ b/Cargo.lock
--- a/Cargo.nix
+++ b/Cargo.nix
--- a/Cargo.toml
+++ b/Cargo.toml
@ -3,7 +3,6 @@ resolver = "2"
 members = [
 	"src/db",
 	"src/util",
 	"src/net",
 	"src/rpc",
 	"src/table",
 	"src/block",
@ -12,141 +11,12 @@ members = [
 	"src/web",
 	"src/garage",
 	"src/k2v-client",
 	"src/format-table",
 ]
 default-members = ["src/garage"]
 [workspace.dependencies]
 # Internal Garage crates
 format_table = { version = "0.1.1", path = "src/format-table" }
 garage_api = { version = "1.0.1", path = "src/api" }
 garage_block = { version = "1.0.1", path = "src/block" }
 garage_db = { version = "1.0.1", path = "src/db", default-features = false }
 garage_model = { version = "1.0.1", path = "src/model", default-features = false }
 garage_net = { version = "1.0.1", path = "src/net" }
 garage_rpc = { version = "1.0.1", path = "src/rpc" }
 garage_table = { version = "1.0.1", path = "src/table" }
 garage_util = { version = "1.0.1", path = "src/util" }
 garage_web = { version = "1.0.1", path = "src/web" }
 k2v-client = { version = "0.0.4", path = "src/k2v-client" }
 # External crates from crates.io
 arc-swap = "1.0"
 argon2 = "0.5"
 async-trait = "0.1.7"
 backtrace = "0.3"
 base64 = "0.21"
 blake2 = "0.10"
 bytes = "1.0"
 bytesize = "1.1"
 cfg-if = "1.0"
 chrono = "0.4"
 crc32fast = "1.4"
 crc32c = "0.6"
 crypto-common = "0.1"
 digest = "0.10"
 err-derive = "0.3"
 gethostname = "0.4"
 git-version = "0.3.4"
 hex = "0.4"
 hexdump = "0.1"
 hmac = "0.12"
 idna = "0.5"
 itertools = "0.12"
 ipnet = "2.9.0"
 lazy_static = "1.4"
 md-5 = "0.10"
 mktemp = "0.5"
 nix = { version = "0.27", default-features = false, features = ["fs"] }
 nom = "7.1"
 parse_duration = "2.1"
 pin-project = "1.0.12"
 pnet_datalink = "0.34"
 rand = "0.8"
 sha1 = "0.10"
 sha2 = "0.10"
 timeago = { version = "0.4", default-features = false }
 xxhash-rust = { version = "0.8", default-features = false, features = ["xxh3"] }
 aes-gcm = { version = "0.10", features = ["aes", "stream"] }
 sodiumoxide = { version = "0.2.5-0", package = "kuska-sodiumoxide" }
 kuska-handshake = { version = "0.2.0", features = ["default", "async_std"] }
 clap = { version = "4.1", features = ["derive", "env"] }
 pretty_env_logger = "0.5"
 structopt = { version = "0.3", default-features = false }
 syslog-tracing = "0.3"
 tracing = "0.1"
 tracing-subscriber = { version = "0.3", features = ["env-filter"] }
 heed = { version = "0.11", default-features = false, features = ["lmdb"] }
 rusqlite = "0.31.0"
 r2d2 = "0.8"
 r2d2_sqlite = "0.24"
 async-compression = { version = "0.4", features = ["tokio", "zstd"] }
 zstd = { version = "0.13", default-features = false }
 quick-xml = { version = "0.26", features = [ "serialize" ] }
 rmp-serde = "1.1.2"
 serde = { version = "1.0", default-features = false, features = ["derive", "rc"] }
 serde_bytes = "0.11"
 serde_json = "1.0"
 toml = { version = "0.8", default-features = false, features = ["parse"] }
 # newer version requires rust edition 2021
 k8s-openapi = { version = "0.21", features = ["v1_24"] }
 kube = { version = "0.88", default-features = false, features = ["runtime", "derive", "client", "rustls-tls"] }
 schemars = "0.8"
 reqwest = { version = "0.11", default-features = false, features = ["rustls-tls-manual-roots", "json"] }
 form_urlencoded = "1.0.0"
 http = "1.0"
 httpdate = "1.0"
 http-range = "0.1"
 http-body-util = "0.1"
 hyper = { version = "1.0", default-features = false }
 hyper-util = { version = "0.1", features = [ "full" ] }
 multer = "3.0"
 percent-encoding = "2.2"
 roxmltree = "0.19"
 url = "2.3"
 futures = "0.3"
 futures-util = "0.3"
 tokio = { version = "1.0", default-features = false, features = ["net", "rt", "rt-multi-thread", "io-util", "net", "time", "macros", "sync", "signal", "fs"] }
 tokio-util = { version = "0.7", features = ["compat", "io"] }
 tokio-stream = { version = "0.1", features = ["net"] }
 opentelemetry = { version = "0.17", features = [ "rt-tokio", "metrics", "trace" ] }
 opentelemetry-prometheus = "0.10"
 opentelemetry-otlp = "0.10"
 opentelemetry-contrib = "0.9"
 prometheus = "0.13"
 # used by the k2v-client crate only
 aws-sigv4 = { version = "1.1" }
 hyper-rustls = { version = "0.26", features = ["http2"] }
 log = "0.4"
 thiserror = "1.0"
 # ---- used only as build / dev dependencies ----
 assert-json-diff = "2.0"
 rustc_version = "0.4.0"
 static_init = "1.0"
 aws-config = "1.1.4"
 aws-sdk-config = "1.13"
 aws-sdk-s3 = "1.14"
 [profile.dev]
 #lto = "thin"	# disabled for now, adds 2-4 min to each CI build
 lto = "off"
 [profile.release]
-lto = true
+debug = true
 codegen-units = 1
 opt-level = "s"
 strip = true
--- a/2
+++ b/2
@ -4,7 +4,7 @@ all:
 	clear; cargo build
 release:
-	nix-build --attr pkgs.amd64.release --no-build-output
+	nix-build --arg release true
 shell:
 	nix-shell
--- a/README.md
+++ b/README.md
@ -1,4 +1,4 @@
-Garage [![status-badge](https://woodpecker.deuxfleurs.fr/api/badges/1/status.svg)](https://woodpecker.deuxfleurs.fr/repos/1)
+Garage [![Build Status](https://drone.deuxfleurs.fr/api/badges/Deuxfleurs/garage/status.svg?ref=refs/heads/main)](https://drone.deuxfleurs.fr/Deuxfleurs/garage)
 ===
 <p align="center" style="text-align:center;">
--- a/default.nix
+++ b/default.nix
@ -1,4 +1,7 @@
-{ system ? builtins.currentSystem, git_version ? null, }:
+{
  system ? builtins.currentSystem,
  git_version ? null,
 }:
 with import ./nix/common.nix;
@ -10,20 +13,21 @@ let
    debug = (compile {
      inherit system target git_version pkgsSrc cargo2nixOverlay;
      release = false;
-    }).workspace.garage { compileMode = "build"; };
+    }).workspace.garage {
      compileMode = "build";
    };
    release = (compile {
      inherit system target git_version pkgsSrc cargo2nixOverlay;
      release = true;
-    }).workspace.garage { compileMode = "build"; };
+    }).workspace.garage {
      compileMode = "build";
    };
  });
-  test = (rustPkgs:
+  test = (rustPkgs: pkgs.symlinkJoin {
    pkgs.symlinkJoin {
    name ="garage-tests";
-      paths =
+    paths = builtins.map (key: rustPkgs.workspace.${key} { compileMode = "test"; }) (builtins.attrNames rustPkgs.workspace);
        builtins.map (key: rustPkgs.workspace.${key} { compileMode = "test"; })
        (builtins.attrNames rustPkgs.workspace);
  });
 in {
@ -40,6 +44,7 @@ in {
      features = [
        "garage/bundled-libs"
        "garage/k2v"
        "garage/sled"
        "garage/lmdb"
        "garage/sqlite"
      ];
@ -50,6 +55,8 @@ in {
      inherit system git_version pkgsSrc cargo2nixOverlay;
      target = "x86_64-unknown-linux-musl";
      compiler = "clippy";
-    }).workspace.garage { compileMode = "build"; };
+    }).workspace.garage {
      compileMode = "build";
    };
  };
 }
--- a/doc/api/garage-admin-v0.yml
+++ b/doc/api/garage-admin-v0.yml
@ -632,7 +632,7 @@ paths:
      operationId: "UpdateBucket"
      summary: "Update a bucket"
      description: |
-        All fields (`websiteAccess` and `quotas`) are optional.
+        All fields (`websiteAccess` and `quotas`) are optionnal.
        If they are present, the corresponding modifications are applied to the bucket, otherwise nothing is changed.
        In `websiteAccess`: if `enabled` is `true`, `indexDocument` must be specified.
@ -678,12 +678,10 @@ paths:
                  properties:
                    maxSize: 
                      type: integer
                      format: int64
                      nullable: true
                      example: 19029801
                    maxObjects:
                      type: integer
                      format: int64
                      nullable: true
                      example: null
@ -1160,11 +1158,9 @@ components:
            $ref: '#/components/schemas/BucketKeyInfo'
        objects:
          type: integer
          format: int64
          example: 14827
        bytes:
          type: integer
          format: int64
          example: 13189855625
        unfinishedUploads:
          type: integer
@ -1175,12 +1171,10 @@ components:
            maxSize:
              nullable: true
              type: integer
              format: int64
              example: null
            maxObjects:
              nullable: true
              type: integer
              format: int64
              example: null
--- a/doc/api/garage-admin-v1.html
+++ b/doc/api/garage-admin-v1.html
@ -1,24 +0,0 @@
 <!DOCTYPE html>
 <html>
  <head>
    <title>Garage Adminstration API v0</title>
    <!-- needed for adaptive design -->
    <meta charset="utf-8"/>
    <meta name="viewport" content="width=device-width, initial-scale=1">
    <link href="./css/redoc.css" rel="stylesheet">
    <!--
    Redoc doesn't change outer page styles
    -->
    <style>
      body {
        margin: 0;
        padding: 0;
      }
    </style>
  </head>
  <body>
    <redoc spec-url='./garage-admin-v1.yml'></redoc>
    <script src="./redoc.standalone.js"> </script>
  </body>
 </html>
--- a/doc/api/garage-admin-v1.yml
+++ b/doc/api/garage-admin-v1.yml
--- a/doc/book/build/_index.md
+++ b/doc/book/build/_index.md
@ -1,6 +1,6 @@
 +++
 title = "Build your own app"
-weight = 40
+weight = 4
 sort_by = "weight"
 template = "documentation.html"
 +++
--- a/doc/book/build/golang.md
+++ b/doc/book/build/golang.md
@ -37,84 +37,30 @@ import (
    "context"
    "fmt"
    "os"
    "strings"
    garage "git.deuxfleurs.fr/garage-sdk/garage-admin-sdk-golang"
 )
 func main() {
-    // Initialization
+    // Set Host and other parameters
    configuration := garage.NewConfiguration()
    configuration.Host = "127.0.0.1:3903"
    // We can now generate a client
    client := garage.NewAPIClient(configuration)
    // Authentication is handled through the context pattern
    ctx := context.WithValue(context.Background(), garage.ContextAccessToken, "s3cr3t")
-    // Nodes
+    // Send a request
-    fmt.Println("--- nodes ---")
+    resp, r, err := client.NodesApi.GetNodes(ctx).Execute()
-    nodes, _, _ := client.NodesApi.GetNodes(ctx).Execute()
+    if err != nil {
-    fmt.Fprintf(os.Stdout, "First hostname: %v\n", nodes.KnownNodes[0].Hostname)
+        fmt.Fprintf(os.Stderr, "Error when calling `NodesApi.GetNodes``: %v\n", err)
-    capa := int64(1000000000)
+        fmt.Fprintf(os.Stderr, "Full HTTP response: %v\n", r)
    change := []garage.NodeRoleChange{
 	    garage.NodeRoleChange{NodeRoleUpdate: &garage.NodeRoleUpdate {
 	        Id: *nodes.KnownNodes[0].Id,
 	        Zone: "dc1",
 	        Capacity: *garage.NewNullableInt64(&capa),
 	        Tags: []string{ "fast", "amd64" },
 	    }},
    }
    staged, _, _ := client.LayoutApi.AddLayout(ctx).NodeRoleChange(change).Execute()
    msg, _, _ := client.LayoutApi.ApplyLayout(ctx).LayoutVersion(*garage.NewLayoutVersion(staged.Version + 1)).Execute()
    fmt.Printf(strings.Join(msg.Message, "\n")) // Layout configured
-    health, _, _ := client.NodesApi.GetHealth(ctx).Execute()
+    // Process the response
-    fmt.Printf("Status: %s, nodes: %v/%v, storage: %v/%v, partitions: %v/%v\n", health.Status, health.ConnectedNodes, health.KnownNodes, health.StorageNodesOk, health.StorageNodes, health.PartitionsAllOk, health.Partitions)
+    fmt.Fprintf(os.Stdout, "Target hostname: %v\n", resp.KnownNodes[resp.Node].Hostname)
    // Key
    fmt.Println("\n--- key ---")
    key := "openapi-key"
    keyInfo, _, _ := client.KeyApi.AddKey(ctx).AddKeyRequest(garage.AddKeyRequest{Name: *garage.NewNullableString(&key) }).Execute()
    defer client.KeyApi.DeleteKey(ctx).Id(*keyInfo.AccessKeyId).Execute()
    fmt.Printf("AWS_ACCESS_KEY_ID=%s\nAWS_SECRET_ACCESS_KEY=%s\n", *keyInfo.AccessKeyId, *keyInfo.SecretAccessKey.Get())
    id := *keyInfo.AccessKeyId
    canCreateBucket := true
    updateKeyRequest := *garage.NewUpdateKeyRequest()
    updateKeyRequest.SetName("openapi-key-updated")
    updateKeyRequest.SetAllow(garage.UpdateKeyRequestAllow { CreateBucket: &canCreateBucket })
    update, _, _ := client.KeyApi.UpdateKey(ctx).Id(id).UpdateKeyRequest(updateKeyRequest).Execute()
    fmt.Printf("Updated %v with key name %v\n", *update.AccessKeyId, *update.Name)
    keyList, _, _ := client.KeyApi.ListKeys(ctx).Execute()
    fmt.Printf("Keys count: %v\n", len(keyList))
    // Bucket
    fmt.Println("\n--- bucket ---")
    global_name := "global-ns-openapi-bucket"
    local_name := "local-ns-openapi-bucket"
    bucketInfo, _, _ := client.BucketApi.CreateBucket(ctx).CreateBucketRequest(garage.CreateBucketRequest{
        GlobalAlias: &global_name,
        LocalAlias: &garage.CreateBucketRequestLocalAlias {
            AccessKeyId: keyInfo.AccessKeyId,
 	    Alias: &local_name,
        },
    }).Execute()
    defer client.BucketApi.DeleteBucket(ctx).Id(*bucketInfo.Id).Execute()
    fmt.Printf("Bucket id: %s\n", *bucketInfo.Id)
    updateBucketRequest := *garage.NewUpdateBucketRequest()
    website := garage.NewUpdateBucketRequestWebsiteAccess()
    website.SetEnabled(true)
    website.SetIndexDocument("index.html")
    website.SetErrorDocument("errors/4xx.html")
    updateBucketRequest.SetWebsiteAccess(*website)
    quotas := garage.NewUpdateBucketRequestQuotas()
    quotas.SetMaxSize(1000000000)
    quotas.SetMaxObjects(999999999)
    updateBucketRequest.SetQuotas(*quotas)
    updatedBucket, _, _ := client.BucketApi.UpdateBucket(ctx).Id(*bucketInfo.Id).UpdateBucketRequest(updateBucketRequest).Execute()
    fmt.Printf("Bucket %v website activation: %v\n", *updatedBucket.Id, *updatedBucket.WebsiteAccess)
    bucketList, _, _ := client.BucketApi.ListBuckets(ctx).Execute()
    fmt.Printf("Bucket count: %v\n", len(bucketList))
 }
 ```
--- a/doc/book/build/javascript.md
+++ b/doc/book/build/javascript.md
@ -31,9 +31,9 @@ npm install --save git+https://git.deuxfleurs.fr/garage-sdk/garage-admin-sdk-js.
 A short example:
 ```javascript
-const garage = require('garage_administration_api_v1garage_v0_9_0');
+const garage = require('garage_administration_api_v0garage_v0_8_0');
-const api = new garage.ApiClient("http://127.0.0.1:3903/v1");
+const api = new garage.ApiClient("http://127.0.0.1:3903/v0");
 api.authentications['bearerAuth'].accessToken = "s3cr3t";
 const [node, layout, key, bucket] = [
--- a/doc/book/build/python.md
+++ b/doc/book/build/python.md
@ -5,56 +5,13 @@ weight = 20
 ## S3
 ### Using Minio SDK
 First install the SDK:
 ```bash
 pip3 install minio
 ```
 Then instantiate a client object using garage root domain, api key and secret:
 ```python
 import minio
 client = minio.Minio(
  "your.domain.tld",
  "GKyourapikey",
  "abcd[...]1234",
  # Force the region, this is specific to garage
  region="garage",
 )
 ```
 Then use all the standard S3 endpoints as implemented by the Minio SDK:
 ```
 # List buckets
 print(client.list_buckets())
 # Put an object containing 'content' to /path in bucket named 'bucket':
 content = b"content"
 client.put_object(
  "bucket",
  "path",
  io.BytesIO(content),
  len(content),
 )
 # Read the object back and check contents
 data = client.get_object("bucket", "path").read()
 assert data == content
 ```
 For further documentation, see the Minio SDK
 [Reference](https://docs.min.io/docs/python-client-api-reference.html)
 ### Using Amazon boto3
 *Coming soon*
-See the official documentation:
+Some refs:
  - Minio SDK
    - [Reference](https://docs.min.io/docs/python-client-api-reference.html)
  - Amazon boto3
    - [Installation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/quickstart.html)
    - [Reference](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html)
    - [Example](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/s3-uploading-files.html)
@ -80,7 +37,7 @@ from garage_admin_sdk.apis import *
 from garage_admin_sdk.models import *
 configuration = garage_admin_sdk.Configuration(
-  host = "http://localhost:3903/v1",
+  host = "http://localhost:3903/v0",
  access_token = "s3cr3t"
 )
@ -94,14 +51,13 @@ print(f"running garage {status.garage_version}, node_id {status.node}")
 # Change layout of this node
 current = layout.get_layout()
-layout.add_layout([
+layout.add_layout({
-  NodeRoleChange(
+  status.node: NodeClusterInfo(
    id = status.node,
    zone = "dc1",
-    capacity = 1000000000,
+    capacity = 1,
    tags = [ "dev" ],
  )
-])
+})
 layout.apply_layout(LayoutVersion(
  version = current.version + 1
 ))
--- a/doc/book/connect/_index.md
+++ b/doc/book/connect/_index.md
@ -1,6 +1,6 @@
 +++
 title = "Existing integrations"
-weight = 30
+weight = 3
 sort_by = "weight"
 template = "documentation.html"
 +++
@ -10,12 +10,11 @@ Garage implements the Amazon S3 protocol, which makes it compatible with many ex
 In particular, you will find here instructions to connect it with:
  - [Applications](@/documentation/connect/apps/index.md)
  - [Browsing tools](@/documentation/connect/cli.md)
-  - [FUSE](@/documentation/connect/fs.md)
+  - [Applications](@/documentation/connect/apps/index.md)
  - [Observability](@/documentation/connect/observability.md)
  - [Software repositories](@/documentation/connect/repositories.md)
  - [Website hosting](@/documentation/connect/websites.md)
  - [Software repositories](@/documentation/connect/repositories.md)
  - [FUSE](@/documentation/connect/fs.md)
 ### Generic instructions
--- a/doc/book/connect/apps/index.md
+++ b/doc/book/connect/apps/index.md
@ -8,13 +8,12 @@ In this section, we cover the following web applications:
 | Name | Status | Note |
 |------|--------|------|
 | [Nextcloud](#nextcloud)     | ✅       |  Both Primary Storage and External Storage are supported    |
-| [Peertube](#peertube)     | ✅       | Supported with the website endpoint, proxifying private videos unsupported     |
+| [Peertube](#peertube)     | ✅       | Must be configured with the website endpoint     |
 | [Mastodon](#mastodon)     | ✅       | Natively supported    |
 | [Matrix](#matrix)     | ✅       |  Tested with `synapse-s3-storage-provider`    |
 | [ejabberd](#ejabberd)     | ✅       |  `mod_s3_upload`    |
 | [Pixelfed](#pixelfed)     | ❓       |  Not yet tested    |
 | [Pleroma](#pleroma)     | ❓       |  Not yet tested    |
-| [Lemmy](#lemmy)     | ✅        |  Supported with pict-rs    |
+| [Lemmy](#lemmy)     | ❓       |  Not yet tested    |
 | [Funkwhale](#funkwhale)     | ❓       | Not yet tested     |
 | [Misskey](#misskey)     | ❓       | Not yet tested     |
 | [Prismo](#prismo)     | ❓       | Not yet tested     |
@ -37,7 +36,7 @@ Second, we suppose you have created a key and a bucket.
 As a reminder, you can create a key for your nextcloud instance as follow:
 ```bash
-garage key create nextcloud-key
+garage key new --name nextcloud-key
 ```
 Keep the Key ID and the Secret key in a pad, they will be needed later.  
@ -80,53 +79,6 @@ To test your new configuration, just reload your Nextcloud webpage and start sen
 *External link:* [Nextcloud Documentation > Primary Storage](https://docs.nextcloud.com/server/latest/admin_manual/configuration_files/primary_storage.html)
 #### SSE-C encryption (since Garage v1.0)
 Since version 1.0, Garage supports server-side encryption with customer keys
 (SSE-C).  In this mode, Garage is responsible for encrypting and decrypting
 objects, but it does not store the encryption key itself. The encryption key
 should be provided by Nextcloud upon each request.  This mode of operation is
 supported by Nextcloud and it has successfully been tested together with
 Garage.
 To enable SSE-C encryption:
 1. Make sure your Garage server is accessible via SSL through a reverse proxy
   such as Nginx, and that it is using a valid public certificate (Nextcloud
   might be able to connect to an S3 server that is using a self-signed
   certificate, but you will lose many hours while trying, so don't).
   Configure values for `use_ssl` and `port` accordingly in your `config.php`
   file.
 2. Generate an encryption key using the following command:
    ```
    openssl rand -base64 32
    ```
    Make sure to keep this key **secret**!
 3. Add the encryption key in your `config.php` file as follows:
    ```php
    <?php
    $CONFIG = array(
    'objectstore' => [
        'class' => '\\OC\\Files\\ObjectStore\\S3',
        'arguments' => [
            ...
            'sse_c_key' => 'exampleencryptionkeyLbU+5fKYQcVoqnn+RaIOXgo=',
            ...
        ],
    ],
    ```
 Nextcloud will now make Garage encrypt files at rest in the storage bucket.
 These files will not be readable by an S3 client that has credentials to the
 bucket but doesn't also know the secret encryption key.
 ### External Storage
 **From the GUI.** Activate the "External storage support" app from the "Applications" page (click on your account icon on the top right corner of your screen to display the menu). Go to your parameters page (also located below your account icon). Click on external storage (or the corresponding translation in your language).
@ -176,24 +128,20 @@ In other words, Peertube is only responsible of the "control plane" and offload
 In return, this system is a bit harder to configure.
 We show how it is still possible to configure Garage with Peertube, allowing you to spread the load and the bandwidth usage on the Garage cluster.
 Starting from version 5.0, Peertube also supports improving the security for private videos by not exposing them directly
 but relying on a single control point in the Peertube instance. This is based on S3 per-object and prefix ACL, which are not currently supported
 in Garage, so this feature is unsupported. While this technically impedes security for private videos, it is not a blocking issue and could be
 a reasonable trade-off for some instances.
 ### Create resources in Garage
 Create a key for Peertube:
 ```bash
-garage key create peertube-key
+garage key new --name peertube-key
 ```
 Keep the Key ID and the Secret key in a pad, they will be needed later.  
 We need two buckets, one for normal videos (named peertube-video) and one for webtorrent videos (named peertube-playlist).
 ```bash
-garage bucket create peertube-videos
+garage bucket create peertube-video
 garage bucket create peertube-playlist
 ```
@ -247,11 +195,6 @@ object_storage:
  max_upload_part: 2GB
  proxy:
    # You may enable this feature, yet it will not provide any security benefit, so
    # you should rather benefit from Garage public endpoint for all videos
    proxify_private_files: false
  streaming_playlists:
    bucket_name: 'peertube-playlist'
@ -263,7 +206,7 @@ object_storage:
  # Same settings but for webtorrent videos
  videos:
-    bucket_name: 'peertube-videos'
+    bucket_name: 'peertube-video'
    prefix: ''
    # You must fill this field to make Peertube use our reverse proxy/website logic
    base_url: 'http://peertube-videos.web.garage.localhost'
@ -292,7 +235,7 @@ with average object size ranging from 50 KB to 150 KB.
 As such, your Garage cluster should be configured appropriately for good performance:
 - use Garage v0.8.0 or higher with the [LMDB database engine](@documentation/reference-manual/configuration.md#db-engine-since-v0-8-0).
-  Older versions of Garage used the Sled database engine which had issues, such as databases quickly ending up taking tens of GB of disk space.
+  With the default Sled database engine, your database could quickly end up taking tens of GB of disk space.
 - the Garage database should be stored on a SSD
 ### Creating your bucket
@ -300,7 +243,7 @@ As such, your Garage cluster should be configured appropriately for good perform
 This is the usual Garage setup:
 ```bash
-garage key create mastodon-key
+garage key new --name mastodon-key
 garage bucket create mastodon-data
 garage bucket allow mastodon-data --read --write --key mastodon-key
 ```
@ -335,7 +278,6 @@ From the [official Mastodon documentation](https://docs.joinmastodon.org/admin/t
 ```bash
 $ RAILS_ENV=production bin/tootctl media remove --days 3
 $ RAILS_ENV=production bin/tootctl media remove --days 15 --prune-profiles
 $ RAILS_ENV=production bin/tootctl media remove-orphans
 $ RAILS_ENV=production bin/tootctl preview_cards remove --days 15
 ```
@ -354,6 +296,8 @@ Imports:	1.7 KB
 Settings:	0 Bytes
 ```
 Unfortunately, [old avatars and headers cannot currently be cleaned up](https://github.com/mastodon/mastodon/issues/9567).
 ### Migrating your data
 Data migration should be done with an efficient S3 client.
@ -425,7 +369,7 @@ Supposing you have a working synapse installation, you can add the module with p
 Now create a bucket and a key for your matrix instance (note your Key ID and Secret Key somewhere, they will be needed later):
 ```bash
-garage key create matrix-key
+garage key new --name matrix-key
 garage bucket create matrix
 garage bucket allow matrix --read --write --key matrix-key
 ```
@ -467,7 +411,7 @@ Now we can write a simple script (eg `~/.local/bin/matrix-cache-gc`):
 ## CONFIGURATION ##
 AWS_ACCESS_KEY_ID=GKxxx
 AWS_SECRET_ACCESS_KEY=xxxx
-AWS_ENDPOINT_URL=http://localhost:3900
+S3_ENDPOINT=http://localhost:3900
 S3_BUCKET=matrix
 MEDIA_STORE=/var/lib/matrix-synapse/media
 PG_USER=matrix
@ -488,7 +432,7 @@ EOF
 s3_media_upload update-db 1d
 s3_media_upload --no-progress check-deleted $MEDIA_STORE
-s3_media_upload --no-progress upload $MEDIA_STORE $S3_BUCKET --delete --endpoint-url $AWS_ENDPOINT_URL
+s3_media_upload --no-progress upload $MEDIA_STORE $S3_BUCKET --delete --endpoint-url $S3_ENDPOINT
 ```
 This script will list all the medias that were not accessed in the 24 hours according to your database.
@ -521,52 +465,6 @@ And add a new line. For example, to run it every 10 minutes:
 *External link:* [matrix-media-repo Documentation > S3](https://docs.t2bot.io/matrix-media-repo/configuration/s3-datastore.html)
 ## ejabberd
 ejabberd is an XMPP server implementation which, with the `mod_s3_upload`
 module in the [ejabberd-contrib](https://github.com/processone/ejabberd-contrib)
 repository, can be integrated to store chat media files in Garage.
 For uploads, this module leverages presigned URLs - this allows XMPP clients to
 directly send media to Garage. Receiving clients then retrieve this media
 through the [static website](@/documentation/cookbook/exposing-websites.md)
 functionality.
 As the data itself is publicly accessible to someone with knowledge of the
 object URL - users are recommended to use
 [E2EE](@/documentation/cookbook/encryption.md) to protect this data-at-rest
 from unauthorized access.
 Install the module with:
 ```bash
 ejabberdctl module_install mod_s3_upload
 ```
 Create the required key and bucket with:
 ```bash
 garage key new --name ejabberd
 garage bucket create objects.xmpp-server.fr
 garage bucket allow objects.xmpp-server.fr --read --write --key ejabberd
 garage bucket website --allow objects.xmpp-server.fr
 ```
 The module can then be configured with:
 ```
  mod_s3_upload:
    #bucket_url: https://objects.xmpp-server.fr.my-garage-instance.mydomain.tld
    bucket_url: https://my-garage-instance.mydomain.tld/objects.xmpp-server.fr
    access_key_id: GK...
    access_key_secret: ...
    region: garage
    download_url: https://objects.xmpp-server.fr
 ```
 Other configuration options can be found in the
 [configuration YAML file](https://github.com/processone/ejabberd-contrib/blob/master/mod_s3_upload/conf/mod_s3_upload.yml).
 ## Pixelfed
 [Pixelfed Technical Documentation > Configuration](https://docs.pixelfed.org/technical-documentation/env.html#filesystem)
@ -577,68 +475,7 @@ Other configuration options can be found in the
 ## Lemmy
-Lemmy uses pict-rs that [supports S3 backends](https://git.asonix.dog/asonix/pict-rs/commit/f9f4fc63d670f357c93f24147c2ee3e1278e2d97).
+Lemmy uses pict-rs that [supports S3 backends](https://git.asonix.dog/asonix/pict-rs/commit/f9f4fc63d670f357c93f24147c2ee3e1278e2d97)
 This feature requires `pict-rs >= 4.0.0`.
 ### Creating your bucket
 This is the usual Garage setup:
 ```bash
 garage key new --name pictrs-key
 garage bucket create pictrs-data
 garage bucket allow pictrs-data --read --write --key pictrs-key
 ```
 Note the Key ID and Secret Key.
 ### Migrating your data
 If your pict-rs instance holds existing data, you first need to migrate to the S3 bucket.
 Stop pict-rs, then run the migration utility from local filesystem to the bucket:
 ```
 pict-rs \
  filesystem -p /path/to/existing/files \
  object-store \
   -e my-garage-instance.mydomain.tld:3900 \
   -b pictrs-data \
   -r garage \
   -a GK... \
   -s abcdef0123456789...
 ```
 This is pretty slow, so hold on while migrating.
 ### Running pict-rs with an S3 backend
 Pict-rs supports both a configuration file and environment variables.
 Either set the following section in your `pict-rs.toml`:
 ```
 [store]
 type = 'object_storage'
 endpoint = 'http://my-garage-instance.mydomain.tld:3900'
 bucket_name = 'pictrs-data'
 region = 'garage'
 access_key = 'GK...'
 secret_key = 'abcdef0123456789...'
 ```
 ... or set these environment variables:
 ```
 PICTRS__STORE__TYPE=object_storage
 PICTRS__STORE__ENDPOINT=http://my-garage-instance.mydomain.tld:3900
 PICTRS__STORE__BUCKET_NAME=pictrs-data
 PICTRS__STORE__REGION=garage
 PICTRS__STORE__ACCESS_KEY=GK...
 PICTRS__STORE__SECRET_KEY=abcdef0123456789...
 ```
 ## Funkwhale
--- a/doc/book/connect/backup.md
+++ b/doc/book/connect/backup.md
@ -13,50 +13,16 @@ Borg Backup is very popular among the backup tools but it is not yet compatible
 We recommend using any other tool listed in this guide because they are all compatible with the S3 API.
 If you still want to use Borg, you can use it with `rclone mount`.
 ## git-annex
 [git-annex](https://git-annex.branchable.com/) supports synchronizing files
 with its [S3 special remote](https://git-annex.branchable.com/special_remotes/S3/).
 Note that `git-annex` requires to be compiled with Haskell package version
 `aws-0.24` to work with Garage.
 ```bash
 garage key new --name my-key
 garage bucket create my-git-annex
 garage bucket allow my-git-annex --read --write --key my-key
 ```
 Register your Key ID and Secret key in your environment:
 ```bash
 export AWS_ACCESS_KEY_ID=GKxxx
 export AWS_SECRET_ACCESS_KEY=xxxx
 ```
 Within a git-annex enabled repository, configure your Garage S3 endpoint with
 the following command:
 ```bash
 git annex initremote garage type=S3 encryption=none host=my-garage-instance.mydomain.tld protocol=https bucket=my-git-annex requeststyle=path region=garage signature=v4
 ```
 Files can now be synchronized using the usual `git-annex` `copy` or `get`
 commands.
 Note that for simplicity - this example does not enable encryption for the files
 sent to Garage - please refer to the
 [git-annex encryption page](https://git-annex.branchable.com/encryption/) for
 how to configure this.
 ## Restic
 Create your key and bucket:
 ```bash
-garage key create my-key
+garage key new my-key
-garage bucket create backups
+garage bucket create backup
-garage bucket allow backups --read --write --key my-key
+garage bucket allow backup --read --write --key my-key
 ```
 Then register your Key ID and Secret key in your environment:
@ -105,7 +71,6 @@ restic restore 79766175 --target /var/lib/postgresql
 Restic has way more features than the ones presented here.
 You can discover all of them by accessing its documentation from the link below.
 Files on Android devices can also be backed up with [restic-android](https://github.com/lhns/restic-android).
 *External links:* [Restic Documentation > Amazon S3](https://restic.readthedocs.io/en/stable/030_preparing_a_new_repo.html#amazon-s3)
--- a/doc/book/connect/cli.md
+++ b/doc/book/connect/cli.md
@ -12,7 +12,6 @@ These tools are particularly suitable for debug, backups, website deployments or
 | [AWS CLI](#aws-cli)     | ✅       | Recommended   |
 | [rclone](#rclone)     | ✅       |    |
 | [s3cmd](#s3cmd)     | ✅       |    |
 | [s5cmd](#s5cmd)     | ✅       |    |
 | [(Cyber)duck](#cyberduck)     | ✅       |    |
 | [WinSCP (libs3)](#winscp)     | ✅       | CLI instructions only   |
 | [sftpgo](#sftpgo)     | ✅       |    |
@ -70,17 +69,16 @@ Then a file named `~/.aws/config` and put:
 ```toml
 [default]
 region=garage
 endpoint_url=http://127.0.0.1:3900
 ```
 Now, supposing Garage is listening on `http://127.0.0.1:3900`, you can list your buckets with:
 ```bash
-aws s3 ls
+aws --endpoint-url http://127.0.0.1:3900 s3 ls
 ```
-If you're using awscli `<1.29.0` or `<2.13.0`, you need to pass `--endpoint-url` to each CLI invocation explicitly.
+Passing the `--endpoint-url` parameter to each command is annoying but AWS developers do not provide a corresponding configuration entry.
-As a workaround, you can redefine the aws command by editing the file `~/.bashrc` in this case:
+As a workaround, you can redefine the aws command by editing the file `~/.bashrc`:
 ```
 function aws { command aws --endpoint-url http://127.0.0.1:3900 $@ ; }
@ -180,34 +178,59 @@ s3cmd put /tmp/hello.txt s3://my-bucket/
 s3cmd get s3://my-bucket/hello.txt hello.txt
 ```
 ## `s5cmd`
 Configure a credentials file as follows:
 ```bash
 export AWS_ACCESS_KEY_ID=GK...
 export AWS_SECRET_ACCESS_KEY=
 export AWS_DEFAULT_REGION='garage'
 export AWS_ENDPOINT='http://localhost:3900'
 ```
 After adding these environment variables in your shell, `s5cmd` can be used
 with:
 ```bash
 s5cmd --endpoint-url=$AWS_ENDPOINT ls
 ```
 See its usage output for other commands available.
 ## Cyberduck & duck {#cyberduck}
 Both Cyberduck (the GUI) and duck (the CLI) have a concept of "Connection Profiles" that contain some presets for a specific provider.
 We wrote the following connection profile for Garage:
-Within Cyberduck, a
+```xml
-[Garage connection profile](https://docs.cyberduck.io/protocols/s3/garage/) is
+<?xml version="1.0" encoding="UTF-8"?>
-available within the `Preferences -> Profiles` section. This can enabled and
+<!DOCTYPE plist PUBLIC "-//Apple//DTD PLIST 1.0//EN" "http://www.apple.com/DTDs/PropertyList-1.0.dtd">
-then connections to Garage may be configured.
+<plist version="1.0">
    <dict>
        <key>Protocol</key>
        <string>s3</string>
        <key>Vendor</key>
        <string>garage</string>
        <key>Scheme</key>
        <string>https</string>
        <key>Description</key>
        <string>GarageS3</string>
        <key>Default Hostname</key>
        <string>127.0.0.1</string>
        <key>Default Port</key>
        <string>4443</string>
        <key>Hostname Configurable</key>
        <false/>
        <key>Port Configurable</key>
        <false/>
        <key>Username Configurable</key>
        <true/>
        <key>Username Placeholder</key>
        <string>Access Key ID (GK...)</string>
        <key>Password Placeholder</key>
        <string>Secret Key</string>
        <key>Properties</key>
        <array>
            <string>s3service.disable-dns-buckets=true</string>
        </array>
        <key>Region</key>
        <string>garage</string>
        <key>Regions</key>
        <array>
            <string>garage</string>
        </array>
    </dict>
 </plist>
 ```
 *Note: If your garage instance is configured with vhost access style, you can remove `s3service.disable-dns-buckets=true`.*
 ### Instructions for the GUI
 Copy the connection profile, and save it anywhere as `garage.cyberduckprofile`.
 Then find this file with your file explorer and double click on it: Cyberduck will open a connection wizard for this profile.
 Simply follow the wizard and you should be done!
 ### Instuctions for the CLI
@ -259,7 +282,7 @@ duck --delete garage:/my-files/an-object.txt
 ## WinSCP (libs3) {#winscp}
-*You can find instructions on how to use the GUI in french [in our wiki](https://guide.deuxfleurs.fr/prise_en_main/winscp/).*
+*You can find instructions on how to use the GUI in french [in our wiki](https://wiki.deuxfleurs.fr/fr/Guide/Garage/WinSCP).*
 How to use `winscp.com`, the CLI interface of WinSCP:
--- a/doc/book/connect/observability.md
+++ b/doc/book/connect/observability.md
@ -1,57 +0,0 @@
 +++
 title = "Observability"
 weight = 25
 +++
 An object store can be used as data storage location for metrics, and logs which
 can then be leveraged for systems observability.
 ## Metrics
 ### Prometheus
 Prometheus itself has no object store capabilities, however two projects exist
 which support storing metrics in an object store:
 - [Cortex](https://cortexmetrics.io/)
 - [Thanos](https://thanos.io/)
 ## System logs
 ### Vector
 [Vector](https://vector.dev/) natively supports S3 as a
 [data sink](https://vector.dev/docs/reference/configuration/sinks/aws_s3/)
 (and [source](https://vector.dev/docs/reference/configuration/sources/aws_s3/)).
 This can be configured with Garage with the following:
 ```bash
 garage key new --name vector-system-logs
 garage bucket create system-logs
 garage bucket allow system-logs --read --write --key vector-system-logs
 ```
 The `vector.toml` can then be configured as follows:
 ```toml
 [sources.journald]
 type = "journald"
 current_boot_only = true
 [sinks.out]
 encoding.codec = "json"
 type = "aws_s3"
 inputs = [ "journald" ]
 bucket = "system-logs"
 key_prefix = "%F/"
 compression = "none"
 region = "garage"
 endpoint = "https://my-garage-instance.mydomain.tld"
 auth.access_key_id = ""
 auth.secret_access_key = ""
 ```
 This is an example configuration - please refer to the Vector documentation for
 all configuration and transformation possibilities. Also note that Garage
 performs its own compression, so this should be disabled in Vector.
--- a/doc/book/connect/repositories.md
+++ b/doc/book/connect/repositories.md
@ -23,7 +23,7 @@ You can configure a different target for each data type (check `[lfs]` and `[att
 Let's start by creating a key and a bucket (your key id and secret will be needed later, keep them somewhere):
 ```bash
-garage key create gitea-key
+garage key new --name gitea-key
 garage bucket create gitea
 garage bucket allow gitea --read --write --key gitea-key
 ```
@ -118,7 +118,7 @@ through another support, like a git repository.
 As a first step, we will need to create a bucket on Garage and enabling website access on it:
 ```bash
-garage key create nix-key
+garage key new --name nix-key
 garage bucket create nix.example.com
 garage bucket allow nix.example.com --read --write --key nix-key
 garage bucket website nix.example.com --allow
--- a/doc/book/cookbook/_index.md
+++ b/doc/book/cookbook/_index.md
@ -1,12 +1,12 @@
 +++
 title="Cookbook"
 template = "documentation.html"
-weight = 20
+weight = 2
 sort_by = "weight"
 +++
 A cookbook, when you cook, is a collection of recipes.
-Similarly, Garage's cookbook contains a collection of recipes that are known to work well!
+Similarly, Garage's cookbook contains a collection of recipes that are known to works well!
 This chapter could also be referred as "Tutorials" or "Best practices".
 - **[Multi-node deployment](@/documentation/cookbook/real-world.md):** This page will walk you through all of the necessary
@ -16,10 +16,6 @@ This chapter could also be referred as "Tutorials" or "Best practices".
  source in case a binary is not provided for your architecture, or if you want to
  hack with us!
 - **[Binary packages](@/documentation/cookbook/binary-packages.md):** This page
  lists the different platforms that provide ready-built software packages for
  Garage.
 - **[Integration with Systemd](@/documentation/cookbook/systemd.md):** This page explains how to run Garage
  as a Systemd service (instead of as a Docker container).
@ -30,10 +26,6 @@ This chapter could also be referred as "Tutorials" or "Best practices".
 - **[Configuring a reverse-proxy](@/documentation/cookbook/reverse-proxy.md):** This page explains how to configure a reverse-proxy to add TLS support to your S3 api endpoint.
- **[Deploying on Kubernetes](@/documentation/cookbook/kubernetes.md):** This page explains how to deploy Garage on Kubernetes using our Helm chart.
+- **[Recovering from failures](@/documentation/cookbook/recovering.md):** Garage's first selling point is resilience
-
+  to hardware failures. This section explains how to recover from such a failure in the
- **[Deploying with Ansible](@/documentation/cookbook/ansible.md):** This page lists available Ansible roles developed by the community to deploy Garage.
+  best possible way.
 - **[Monitoring Garage](@/documentation/cookbook/monitoring.md)** This page
  explains the Prometheus metrics available for monitoring the Garage
  cluster/nodes.
--- a/doc/book/cookbook/ansible.md
+++ b/doc/book/cookbook/ansible.md
@ -1,51 +0,0 @@
 +++
 title = "Deploying with Ansible"
 weight = 35
 +++
 While Ansible is not officially supported to deploy Garage, several community members
 have published Ansible roles.  We list them and compare them below.
 ## Comparison of Ansible roles
 | Feature                            | [ansible-role-garage](#zorun-ansible-role-garage) | [garage-docker-ansible-deploy](#moan0s-garage-docker-ansible-deploy) |
 |------------------------------------|---------------------------------------------|---------------------------------------------------------------|
 | **Runtime**                        | Systemd                                     | Docker                                                        |
 | **Target OS**                      | Any Linux                                   | Any Linux                                                     |
 | **Architecture**                   | amd64, arm64, i686                          | amd64, arm64                                                  |
 | **Additional software**            | None                                        | Traefik                                                       |
 | **Automatic node connection**      | ❌                                          | ✅                                                            |
 | **Layout management**              | ❌                                          | ✅                                                            |
 | **Manage buckets & keys**          | ❌                                          | ✅ (basic)                                                    |
 | **Allow custom Garage config**     | ✅                                          | ❌                                                            |
 | **Facilitate Garage upgrades**     | ✅                                          | ❌                                                            |
 | **Multiple instances on one host** | ✅                                          | ✅                                                            |
 ## zorun/ansible-role-garage
 [Source code](https://github.com/zorun/ansible-role-garage), [Ansible galaxy](https://galaxy.ansible.com/zorun/garage)
 This role is voluntarily simple: it relies on the official Garage static
 binaries and only requires Systemd.  As such, it should work on any
 Linux-based OS.
 To make things more flexible, the user has to provide a Garage
 configuration template.  This allows to customize Garage configuration in
 any way.
 Some more features might be added, such as a way to automatically connect
 nodes to each other or to define a layout.
 ## moan0s/garage-docker-ansible-deploy
 [Source code](https://github.com/moan0s/garage-docker-ansible-deploy), [Blog post](https://hyteck.de/post/garage/)
 This role is based on the Docker image for Garage, and comes with
 "batteries included": it will additionally install Docker and Traefik. In
 addition, it is "opinionated" in the sense that it expects a particular
 deployment structure (one instance per disk, one gateway per host,
 structured DNS names, etc).
 As a result, this role makes it easier to start with Garage on Ansible,
 but is less flexible.
--- a/doc/book/cookbook/binary-packages.md
+++ b/doc/book/cookbook/binary-packages.md
@ -1,41 +0,0 @@
 +++
 title = "Binary packages"
 weight = 11
 +++
 Garage is also available in binary packages on:
 ## Alpine Linux
 If you use Alpine Linux, you can simply install the
 [garage](https://pkgs.alpinelinux.org/packages?name=garage) package from the
 Alpine Linux repositories (available since v3.17):
 ```bash
 apk add garage
 ```
 The default configuration file is installed to `/etc/garage.toml`. You can run
 Garage using: `rc-service garage start`. If you don't specify `rpc_secret`, it
 will be automatically replaced with a random string on the first start.
 Please note that this package is built without Consul discovery, Kubernetes
 discovery, OpenTelemetry exporter, and K2V features (K2V will be enabled once
 it's stable).
 ## Arch Linux
 Garage is available in the [AUR](https://aur.archlinux.org/packages/garage).
 ## FreeBSD
 ```bash
 pkg install garage
 ```
 ## NixOS
 ```bash
 nix-shell -p garage
 ```
--- a/doc/book/cookbook/encryption.md
+++ b/doc/book/cookbook/encryption.md
@ -1,139 +0,0 @@
 +++
 title = "Encryption"
 weight = 50
 +++
 Encryption is a recurring subject when discussing Garage. 
 Garage does not handle data encryption by itself, but many things can
 already be done with Garage's current feature set and the existing ecosystem.
 This page takes a high level approach to security in general and data encryption
 in particular.
 # Examining your need for encryption
 - Why do you want encryption in Garage?
 - What is your threat model? What are you fearing?
  - A stolen HDD?
  - A curious administrator?
  - A malicious administrator?
  - A remote attacker?
  - etc.
 - What services do you want to protect with encryption?
  - An existing application? Which one? (eg. Nextcloud)
  - An application that you are writing
 - Any expertise you may have on the subject
 This page explains what Garage provides, and how you can improve the situation by yourself
 by adding encryption at different levels.
 We would be very curious to know your needs and thougs about ideas such as
 encryption practices and things like key management, as we want Garage to be a
 serious base platform for the developpment of secure, encrypted applications.
 Do not hesitate to come talk to us if you have any thoughts or questions on the
 subject.
 # Capabilities provided by Garage
 ## Traffic is encrypted between Garage nodes
 RPCs between Garage nodes are encrypted. More specifically, contrary to many
 distributed software, it is impossible in Garage to have clear-text RPC.  We
 use the [kuska handshake](https://github.com/Kuska-ssb/handshake) library which
 implements a protocol that has been clearly reviewed, Secure ScuttleButt's
 Secret Handshake protocol.  This is why setting a `rpc_secret` is mandatory,
 and that's also why your nodes have super long identifiers.
 ## HTTP API endpoints provided by Garage are in clear text
 Adding TLS support built into Garage is not currently planned.
 ## Garage stores data in plain text on the filesystem or encrypted using customer keys (SSE-C)
 For standard S3 API requests, Garage does not encrypt data at rest by itself.
 For the most generic at rest encryption of data, we recommend setting up your
 storage partitions on encrypted LUKS devices.
 If you are developping your own client software that makes use of S3 storage,
 we recommend implementing data encryption directly on the client side and never
 transmitting plaintext data to Garage. This makes it easy to use an external
 untrusted storage provider if necessary.
 Garage does support [SSE-C
 encryption](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ServerSideEncryptionCustomerKeys.html),
 an encryption mode of Amazon S3 where data is encrypted at rest using
 encryption keys given by the client.  The encryption keys are passed to the
 server in a header in each request, to encrypt or decrypt data at the moment of
 reading or writing. The server discards the key as soon as it has finished
 using it for the request.  This mode allows the data to be encrypted at rest by
 Garage itself, but it requires support in the client software. It is also not
 adapted to a model where the server is not trusted or assumed to be
 compromised, as the server can easily know the encryption keys.  Note however
 that when using SSE-C encryption, the only Garage node that knows the
 encryption key passed in a given request is the node to which the request is
 directed (which can be a gateway node), so it is easy to have untrusted nodes
 in the cluster as long as S3 API requests containing SSE-C encryption keys are
 not directed to them.
 Implementing automatic data encryption directly in Garage without client-side
 management of keys (something like
 [SSE-S3](https://docs.aws.amazon.com/AmazonS3/latest/userguide/UsingServerSideEncryption.html))
 could make things simpler for end users that don't want to setup LUKS, but also
 raises many more questions, especially around key management: for encryption of
 data, where could Garage get the encryption keys from? If we encrypt data but
 keep the keys in a plaintext file next to them, it's useless. We probably don't
 want to have to manage secrets in Garage as it would be very hard to do in a
 secure way. At the time of speaking, there are no plans to implement this in
 Garage.
 # Adding data encryption using external tools
 ## Encrypting traffic between a Garage node and your client
 You have multiple options to have encryption between your client and a node:
  - Setup a reverse proxy with TLS / ACME / Let's encrypt
  - Setup a Garage gateway locally, and only contact the garage daemon on `localhost`
  - Only contact your Garage daemon over a secure, encrypted overlay network such as Wireguard
 ## Encrypting data at rest
 Protects against the following threats:
 - Stolen HDD
 Crucially, does not protect againt malicious sysadmins or remote attackers that
 might gain access to your servers.
 Methods include full-disk encryption with tools such as LUKS.
 ## Encrypting data on the client side
 Protects againt the following threats:
 - A honest-but-curious administrator
 - A malicious administrator that tries to corrupt your data
 - A remote attacker that can read your server's data
 Implementations are very specific to the various applications. Examples:
 - Matrix: uses the OLM protocol for E2EE of user messages. Media files stored
  in Matrix are probably encrypted using symmetric encryption, with a key that is
  distributed in the end-to-end encrypted message that contains the link to the object.
 - XMPP: clients normally support either OMEMO / OpenPGP for the E2EE of user
  messages. Media files are encrypted per
  [XEP-0454](https://xmpp.org/extensions/xep-0454.html).
 - Aerogramme: use the user's password as a key to decrypt data in the user's bucket
 - Cyberduck: comes with support for
  [Cryptomator](https://docs.cyberduck.io/cryptomator/) which allows users to
  create client-side vaults to encrypt files in before they are uploaded to a
  cloud storage endpoint.
--- a/doc/book/cookbook/exposing-websites.md
+++ b/doc/book/cookbook/exposing-websites.md
@ -38,7 +38,7 @@ Our website serving logic is as follow:
 Now we need to infer the URL of your website through your bucket name.
 Let assume:
-  - we set `root_domain = ".web.example.com"` in `garage.toml` ([ref](@/documentation/reference-manual/configuration.md#web_root_domain))
+  - we set `root_domain = ".web.example.com"` in `garage.toml` ([ref](@/documentation/reference-manual/configuration.md#root_domain))
  - our bucket name is `garagehq.deuxfleurs.fr`.
 Our bucket will be served if the Host field matches one of these 2 values (the port is ignored):
--- a/doc/book/cookbook/from-source.md
+++ b/doc/book/cookbook/from-source.md
@ -90,6 +90,6 @@ The following feature flags are available in v0.8.0:
 | `kubernetes-discovery` | optional | Enable automatic registration and discovery<br>of cluster nodes through the Kubernetes API |
 | `metrics` | *by default* | Enable collection of metrics in Prometheus format on the admin API |
 | `telemetry-otlp` | optional | Enable collection of execution traces using OpenTelemetry |
-| `syslog` | optional | Enable logging to Syslog |
+| `sled` | *by default* | Enable using Sled to store Garage's metadata |
-| `lmdb` | *by default* | Enable using LMDB to store Garage's metadata |
+| `lmdb` | optional | Enable using LMDB to store Garage's metadata |
-| `sqlite` | *by default* | Enable using Sqlite3 to store Garage's metadata |
+| `sqlite` | optional | Enable using Sqlite3 to store Garage's metadata |
--- a/doc/book/cookbook/gateways.md
+++ b/doc/book/cookbook/gateways.md
@ -21,7 +21,7 @@ You can configure Garage as a gateway on all nodes that will consume your S3 API
 The instructions are similar to a regular node, the only option that is different is while configuring the node, you must set the `--gateway` parameter:
 ```bash
-garage layout assign --gateway --tag gw1 -z dc1 <node_id>
+garage layout assign --gateway --tag gw1 <node_id>
 garage layout show    # review the changes you are making
 garage layout apply   # once satisfied, apply the changes
 ```
--- a/doc/book/cookbook/kubernetes.md
+++ b/doc/book/cookbook/kubernetes.md
@ -48,7 +48,6 @@ garage:
  replicationMode: "2"
 # Start 4 instances (StatefulSets) of garage
 deployment:
 replicaCount: 4
 # Override default storage class and size
--- a/doc/book/cookbook/monitoring.md
+++ b/doc/book/cookbook/monitoring.md
@ -18,7 +18,7 @@ api_bind_addr = "0.0.0.0:3903"
 ```
 This will allow anyone to scrape Prometheus metrics by fetching
-`http://localhost:3903/metrics`. If you want to restrict access
+`http://localhost:3093/metrics`. If you want to restrict access
 to the exported metrics, set the `metrics_token` configuration value
 to a bearer token to be used when fetching the metrics endpoint.
@ -49,5 +49,258 @@ add the following lines in your Prometheus scrape config:
 To visualize the scraped data in Grafana,
 you can either import our [Grafana dashboard for Garage](https://git.deuxfleurs.fr/Deuxfleurs/garage/raw/branch/main/script/telemetry/grafana-garage-dashboard-prometheus.json)
 or make your own.
 We detail below the list of exposed metrics and their meaning.
 ## List of exported metrics
 ### Metrics of the API endpoints
 #### `api_admin_request_counter` (counter)
 Counts the number of requests to a given endpoint of the administration API. Example:
 ```
 api_admin_request_counter{api_endpoint="Metrics"} 127041
 ```
 #### `api_admin_request_duration` (histogram)
 Evaluates the duration of API calls to the various administration API endpoint. Example:
 ```
 api_admin_request_duration_bucket{api_endpoint="Metrics",le="0.5"} 127041
 api_admin_request_duration_sum{api_endpoint="Metrics"} 605.250344830999
 api_admin_request_duration_count{api_endpoint="Metrics"} 127041
 ```
 #### `api_s3_request_counter` (counter)
 Counts the number of requests to a given endpoint of the S3 API. Example:
 ```
 api_s3_request_counter{api_endpoint="CreateMultipartUpload"} 1
 ```
 #### `api_s3_error_counter` (counter)
 Counts the number of requests to a given endpoint of the S3 API that returned an error. Example:
 ```
 api_s3_error_counter{api_endpoint="GetObject",status_code="404"} 39
 ```
 #### `api_s3_request_duration` (histogram)
 Evaluates the duration of API calls to the various S3 API endpoints. Example:
 ```
 api_s3_request_duration_bucket{api_endpoint="CreateMultipartUpload",le="0.5"} 1
 api_s3_request_duration_sum{api_endpoint="CreateMultipartUpload"} 0.046340762
 api_s3_request_duration_count{api_endpoint="CreateMultipartUpload"} 1
 ```
 #### `api_k2v_request_counter` (counter), `api_k2v_error_counter` (counter), `api_k2v_error_duration` (histogram)
 Same as for S3, for the K2V API.
 ### Metrics of the Web endpoint
 #### `web_request_counter` (counter)
 Number of requests to the web endpoint
 ```
 web_request_counter{method="GET"} 80
 ```
 #### `web_request_duration` (histogram)
 Duration of requests to the web endpoint
 ```
 web_request_duration_bucket{method="GET",le="0.5"} 80
 web_request_duration_sum{method="GET"} 1.0528433229999998
 web_request_duration_count{method="GET"} 80
 ```
 #### `web_error_counter` (counter)
 Number of requests to the web endpoint resulting in errors
 ```
 web_error_counter{method="GET",status_code="404 Not Found"} 64
 ```
 ### Metrics of the data block manager
 #### `block_bytes_read`, `block_bytes_written` (counter)
 Number of bytes read/written to/from disk in the data storage directory.
 ```
 block_bytes_read 120586322022
 block_bytes_written 3386618077
 ```
 #### `block_read_duration`, `block_write_duration` (histograms)
 Evaluates the duration of the reading/writing of individual data blocks in the data storage directory.
 ```
 block_read_duration_bucket{le="0.5"} 169229
 block_read_duration_sum 2761.6902550310056
 block_read_duration_count 169240
 block_write_duration_bucket{le="0.5"} 3559
 block_write_duration_sum 195.59170078500006
 block_write_duration_count 3571
 ```
 #### `block_delete_counter` (counter)
 Counts the number of data blocks that have been deleted from storage.
 ```
 block_delete_counter 122
 ```
 #### `block_resync_counter` (counter), `block_resync_duration` (histogram)
 Counts the number of resync operations the node has executed, and evaluates their duration.
 ```
 block_resync_counter 308897
 block_resync_duration_bucket{le="0.5"} 308892
 block_resync_duration_sum 139.64204196100016
 block_resync_duration_count 308897
 ```
 #### `block_resync_queue_length` (gauge)
 The number of block hashes currently queued for a resync.
 This is normal to be nonzero for long periods of time.
 ```
 block_resync_queue_length 0
 ```
 #### `block_resync_errored_blocks` (gauge)
 The number of block hashes that we were unable to resync last time we tried.
 **THIS SHOULD BE ZERO, OR FALL BACK TO ZERO RAPIDLY, IN A HEALTHY CLUSTER.**
 Persistent nonzero values indicate that some data is likely to be lost.
 ```
 block_resync_errored_blocks 0
 ```
 ### Metrics related to RPCs (remote procedure calls) between nodes
 #### `rpc_netapp_request_counter` (counter)
 Number of RPC requests emitted
 ```
 rpc_request_counter{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>"} 176
 ```
 #### `rpc_netapp_error_counter` (counter)
 Number of communication errors (errors in the Netapp library, generally due to disconnected nodes)
 ```
 rpc_netapp_error_counter{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>"} 354
 ```
 #### `rpc_timeout_counter` (counter)
 Number of RPC timeouts, should be close to zero in a healthy cluster.
 ```
 rpc_timeout_counter{from="<this node>",rpc_endpoint="garage_rpc/membership.rs/SystemRpc",to="<remote node>"} 1
 ```
 #### `rpc_duration` (histogram)
 The duration of internal RPC calls between Garage nodes.
 ```
 rpc_duration_bucket{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>",le="0.5"} 166
 rpc_duration_sum{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>"} 35.172253716
 rpc_duration_count{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>"} 174
 ```
 ### Metrics of the metadata table manager
 #### `table_gc_todo_queue_length` (gauge)
 Table garbage collector TODO queue length
 ```
 table_gc_todo_queue_length{table_name="block_ref"} 0
 ```
 #### `table_get_request_counter` (counter), `table_get_request_duration` (histogram)
 Number of get/get_range requests internally made on each table, and their duration.
 ```
 table_get_request_counter{table_name="bucket_alias"} 315
 table_get_request_duration_bucket{table_name="bucket_alias",le="0.5"} 315
 table_get_request_duration_sum{table_name="bucket_alias"} 0.048509778000000024
 table_get_request_duration_count{table_name="bucket_alias"} 315
 ```
 #### `table_put_request_counter` (counter), `table_put_request_duration` (histogram)
 Number of insert/insert_many requests internally made on this table, and their duration
 ```
 table_put_request_counter{table_name="block_ref"} 677
 table_put_request_duration_bucket{table_name="block_ref",le="0.5"} 677
 table_put_request_duration_sum{table_name="block_ref"} 61.617528636
 table_put_request_duration_count{table_name="block_ref"} 677
 ```
 #### `table_internal_delete_counter` (counter)
 Number of value deletions in the tree (due to GC or repartitioning)
 ```
 table_internal_delete_counter{table_name="block_ref"} 2296
 ```
 #### `table_internal_update_counter` (counter)
 Number of value updates where the value actually changes (includes creation of new key and update of existing key)
 ```
 table_internal_update_counter{table_name="block_ref"} 5996
 ```
 #### `table_merkle_updater_todo_queue_length` (gauge)
 Merkle tree updater TODO queue length (should fall to zero rapidly)
 ```
 table_merkle_updater_todo_queue_length{table_name="block_ref"} 0
 ```
 #### `table_sync_items_received`, `table_sync_items_sent` (counters)
 Number of data items sent to/recieved from other nodes during resync procedures
 ```
 table_sync_items_received{from="<remote node>",table_name="bucket_v2"} 3
 table_sync_items_sent{table_name="block_ref",to="<remote node>"} 2
 ```
 The list of exported metrics is available on our [dedicated page](@/documentation/reference-manual/monitoring.md) in the Reference manual section.
--- a/doc/book/cookbook/real-world.md
+++ b/doc/book/cookbook/real-world.md
@ -19,13 +19,8 @@ To run a real-world deployment, make sure the following conditions are met:
 - You have at least three machines with sufficient storage space available.
- Each machine has an IP address which makes it directly reachable by all other machines.
+- Each machine has a public IP address which is reachable by other machines.
-  In many cases, nodes will be behind a NAT and will not each have a public
+  Running behind a NAT is likely to be possible but hasn't been tested for the latest version (TODO).
  IPv4 addresses. In this case, is recommended that you use IPv6 for this
  end-to-end connectivity if it is available. Otherwise, using a mesh VPN such as
  [Nebula](https://github.com/slackhq/nebula) or
  [Yggdrasil](https://yggdrasil-network.github.io/) are approaches to consider
  in addition to building out your own VPN tunneling.
 - This guide will assume you are using Docker containers to deploy Garage on each node. 
  Garage can also be run independently, for instance as a [Systemd service](@/documentation/cookbook/systemd.md).
@ -43,7 +38,7 @@ For our example, we will suppose the following infrastructure with IPv6 connecti
 | Brussels | Mars    | fc00:F::1  | 1.5 TB     |
 Note that Garage will **always** store the three copies of your data on nodes at different
-locations. This means that in the case of this small example, the usable capacity
+locations. This means that in the case of this small example, the available capacity
 of the cluster is in fact only 1.5 TB, because nodes in Brussels can't store more than that.
 This also means that nodes in Paris and London will be under-utilized.
 To make better use of the available hardware, you should ensure that the capacity
@ -53,9 +48,9 @@ to store 2 TB of data in total.
 ### Best practices
- If you have reasonably fast networking between all your nodes, and are planing to store
+- If you have fast dedicated networking between all your nodes, and are planing to store
-  mostly large files, bump the `block_size` configuration parameter to 10 MB
+  very large files, bump the `block_size` configuration parameter to 10 MB
-  (`block_size = "10M"`).
+  (`block_size = 10485760`).
 - Garage stores its files in two locations: it uses a metadata directory to store frequently-accessed
  small metadata items, and a data directory to store data blocks of uploaded objects.
@ -68,42 +63,36 @@ to store 2 TB of data in total.
  EXT4 is not recommended as it has more strict limitations on the number of inodes,
  which might cause issues with Garage when large numbers of objects are stored.
- Servers with multiple HDDs are supported natively by Garage without resorting
+- If you only have an HDD and no SSD, it's fine to put your metadata alongside the data
-  to RAID, see [our dedicated documentation page](@/documentation/operations/multi-hdd.md).
+  on the same drive. Having lots of RAM for your kernel to cache the metadata will
  help a lot with performance.  Make sure to use the LMDB database engine,
  instead of Sled, which suffers from quite bad performance degradation on HDDs.
  Sled is still the default for legacy reasons, but is not recommended anymore.
 - For the metadata storage, Garage does not do checksumming and integrity
-  verification on its own, so it is better to use a robust filesystem such as
+  verification on its own. If you are afraid of bitrot/data corruption,
-  BTRFS or ZFS. Users have reported that when using the LMDB database engine
+  put your metadata directory on a BTRFS partition. Otherwise, just use regular
-  (the default), database files have a tendency of becoming corrupted after an
+  EXT4 or XFS.
  unclean shutdown (e.g. a power outage), so you should take regular snapshots
  to be able to recover from such a situation.  This can be done using Garage's
  built-in automatic snapshotting (since v0.9.4), or by using filesystem level
  snapshots. If you cannot do so, you might want to switch to Sqlite which is
  more robust.
- LMDB is the fastest and most tested database engine, but it has the following
+- Having a single server with several storage drives is currently not very well
-  weaknesses: 1/ data files are not architecture-independent, you cannot simply
+  supported in Garage ([#218](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/218)).
-  move a Garage metadata directory between nodes running different architectures,
+  For an easy setup, just put all your drives in a RAID0 or a ZFS RAIDZ array.
-  and 2/ LMDB is not suited for 32-bit platforms. Sqlite is a viable alternative
+  If you're adventurous, you can try to format each of your disk as
-  if any of these are of concern.
+  a separate XFS partition, and then run one `garage` daemon per disk drive,
-
+  or use something like [`mergerfs`](https://github.com/trapexit/mergerfs) to merge
- If you only have an HDD and no SSD, it's fine to put your metadata alongside
+  all your disks in a single union filesystem that spreads load over them.
  the data on the same drive, but then consider your filesystem choice wisely
  (see above). Having lots of RAM for your kernel to cache the metadata will
  help a lot with performance.  The default LMDB database engine is the most
  tested and has good performance.
 ## Get a Docker image
 Our docker image is currently named `dxflrs/garage` and is stored on the [Docker Hub](https://hub.docker.com/r/dxflrs/garage/tags?page=1&ordering=last_updated).
-We encourage you to use a fixed tag (eg. `v1.0.1`) and not the `latest` tag.
+We encourage you to use a fixed tag (eg. `v0.8.0`) and not the `latest` tag.
-For this example, we will use the latest published version at the time of the writing which is `v1.0.1` but it's up to you
+For this example, we will use the latest published version at the time of the writing which is `v0.8.0` but it's up to you
 to check [the most recent versions on the Docker Hub](https://hub.docker.com/r/dxflrs/garage/tags?page=1&ordering=last_updated).
 For example:
 ```
-sudo docker pull dxflrs/garage:v1.0.1
+sudo docker pull dxflrs/garage:v0.8.0
 ```
 ## Deploying and configuring Garage
@ -126,9 +115,8 @@ A valid `/etc/garage.toml` for our cluster would look as follows:
 metadata_dir = "/var/lib/garage/meta"
 data_dir = "/var/lib/garage/data"
 db_engine = "lmdb"
 metadata_auto_snapshot_interval = "6h"
-replication_factor = 3
+replication_mode = "3"
 compression_level = 2
@ -152,8 +140,6 @@ Check the following for your configuration files:
 - Make sure `rpc_public_addr` contains the public IP address of the node you are configuring.
  This parameter is optional but recommended: if your nodes have trouble communicating with
  one another, consider adding it.
  Alternatively, you can also set `rpc_public_addr_subnet`, which can filter
  the addresses announced to other peers to a specific subnet.
 - Make sure `rpc_secret` is the same value on all nodes. It should be a 32-bytes hex-encoded secret key.
  You can generate such a key with `openssl rand -hex 32`.
@ -171,13 +157,12 @@ docker run \
  -v /etc/garage.toml:/etc/garage.toml \
  -v /var/lib/garage/meta:/var/lib/garage/meta \
  -v /var/lib/garage/data:/var/lib/garage/data \
-  dxflrs/garage:v1.0.1
+  dxflrs/garage:v0.8.0
 ```
-With this command line, Garage should be started automatically at each boot.
+It should be restarted automatically at each reboot.
-Please note that we use host networking as otherwise the network indirection
+Please note that we use host networking as otherwise Docker containers
-added by Docker would prevent Garage nodes from communicating with one another
+can not communicate with IPv6.
 (especially if using IPv6).
 If you want to use `docker-compose`, you may use the following `docker-compose.yml` file as a reference:
@ -185,7 +170,7 @@ If you want to use `docker-compose`, you may use the following `docker-compose.y
 version: "3"
 services:
  garage:
-    image: dxflrs/garage:v1.0.1
+    image: dxflrs/garage:v0.8.0
    network_mode: "host"
    restart: unless-stopped
    volumes:
@ -194,14 +179,12 @@ services:
      - /var/lib/garage/data:/var/lib/garage/data
 ```
-If you wish to upgrade your cluster, make sure to read the corresponding
+Upgrading between Garage versions should be supported transparently,
-[documentation page](@/documentation/operations/upgrading.md) first, as well as
+but please check the relase notes before doing so!
-the documentation relevant to your version of Garage in the case of major
+To upgrade, simply stop and remove this container and
-upgrades.  With the containerized setup proposed here, the upgrade process
+start again the command with a new version of Garage.
 will require stopping and removing the existing container, and re-creating it
 with the upgraded version.
-## Controlling the daemon
+## Controling the daemon
 The `garage` binary has two purposes:
  - it acts as a daemon when launched with `garage server`
@ -210,12 +193,6 @@ The `garage` binary has two purposes:
 Ensure an appropriate `garage` binary (the same version as your Docker image) is available in your path.
 If your configuration file is at `/etc/garage.toml`, the `garage` binary should work with no further change.
 You can also use an alias as follows to use the Garage binary inside your docker container:
 ```bash
 alias garage="docker exec -ti <container name> /garage"
 ```
 You can test your `garage` CLI utility by running a simple command such as:
 ```bash
@ -259,7 +236,7 @@ You can then instruct nodes to connect to one another as follows:
 Venus$ garage node connect 563e1ac825ee3323aa441e72c26d1030d6d4414aeb3dd25287c531e7fc2bc95d@[fc00:1::1]:3901
 ```
-You don't need to instruct all node to connect to all other nodes:
+You don't nead to instruct all node to connect to all other nodes:
 nodes will discover one another transitively.
 Now if your run `garage status` on any node, you should have an output that looks as follows:
@ -283,12 +260,12 @@ of a role that is assigned to each active cluster node.
 For our example, we will suppose we have the following infrastructure
 (Capacity, Identifier and Zone are specific values to Garage described in the following):
-| Location | Name    | Disk Space | Identifier | Zone (`-z`) | Capacity (`-c`) |
+| Location | Name    | Disk Space | `Capacity` | `Identifier` | `Zone` |
-|----------|---------|------------|------------|-------------|-----------------|
+|----------|---------|------------|------------|--------------|--------------|
-| Paris    | Mercury | 1 TB       | `563e`     | `par1`      | `1T`            |
+| Paris    | Mercury | 1 TB       | `10`       | `563e`     | `par1`       |
-| Paris    | Venus   | 2 TB       | `86f0`     | `par1`      | `2T`            |
+| Paris    | Venus   | 2 TB       | `20`       | `86f0`     | `par1`       |
-| London   | Earth   | 2 TB       | `6814`     | `lon1`      | `2T`            |
+| London   | Earth   | 2 TB       | `20`       | `6814`     | `lon1`       |
-| Brussels | Mars    | 1.5 TB     | `212f`     | `bru1`      | `1.5T`          |
+| Brussels | Mars    | 1.5 TB     | `15`       | `212f`     | `bru1`       |
 #### Node identifiers
@ -310,8 +287,6 @@ garage status
 It will display the IP address associated with each node;
 from the IP address you will be able to recognize the node.
 We will now use the `garage layout assign` command to configure the correct parameters for each node.
 #### Zones
 Zones are simply a user-chosen identifier that identify a group of server that are grouped together logically.
@ -321,29 +296,29 @@ In most cases, a zone will correspond to a geographical location (i.e. a datacen
 Behind the scene, Garage will use zone definition to try to store the same data on different zones,
 in order to provide high availability despite failure of a zone.
 Zones are passed to Garage using the `-z` flag of `garage layout assign` (see below).
 #### Capacity
-Garage needs to know the storage capacity (disk space) it can/should use on
+Garage reasons on an abstract metric about disk storage that is named the *capacity* of a node.
-each node, to be able to correctly balance data.
+The capacity configured in Garage must be proportional to the disk space dedicated to the node.
-Capacity values are expressed in bytes and are passed to Garage using the `-c` flag of `garage layout assign` (see below).
+Capacity values must be **integers** but can be given any signification.
 Here we chose that 1 unit of capacity = 100 GB.
-#### Tags
+Note that the amount of data stored by Garage on each server may not be strictly proportional to
-
+its capacity value, as Garage will priorize having 3 copies of data in different zones,
-You can add additional tags to nodes using the `-t` flag of `garage layout assign` (see below).
+even if this means that capacities will not be strictly respected. For example in our above examples,
-Tags have no specific meaning for Garage and can be used at your convenience.
+nodes Earth and Mars will always store a copy of everything each, and the third copy will
 have 66% chance of being stored by Venus and 33% chance of being stored by Mercury.
 #### Injecting the topology
 Given the information above, we will configure our cluster as follow:
 ```bash
-garage layout assign 563e -z par1 -c 1T -t mercury
+garage layout assign 563e -z par1 -c 10 -t mercury
-garage layout assign 86f0 -z par1 -c 2T -t venus
+garage layout assign 86f0 -z par1 -c 20 -t venus
-garage layout assign 6814 -z lon1 -c 2T -t earth
+garage layout assign 6814 -z lon1 -c 20 -t earth 
-garage layout assign 212f -z bru1 -c 1.5T -t mars
+garage layout assign 212f -z bru1 -c 15 -t mars 
 ```
 At this point, the changes in the cluster layout have not yet been applied.
@ -353,7 +328,6 @@ To show the new layout that will be applied, call:
 garage layout show
 ```
 Make sure to read carefully the output of `garage layout show`.
 Once you are satisfied with your new layout, apply it with:
 ```bash
@ -361,7 +335,7 @@ garage layout apply
 ```
 **WARNING:** if you want to use the layout modification commands in a script,
-make sure to read [this page](@/documentation/operations/layout.md) first.
+make sure to read [this page](@/documentation/reference-manual/layout.md) first.
 ## Using your Garage cluster
@ -371,5 +345,5 @@ and is covered in the [quick start guide](@/documentation/quick-start/_index.md)
 Remember also that the CLI is self-documented thanks to the `--help` flag and
 the `help` subcommand (e.g. `garage help`, `garage key --help`).
-Configuring S3-compatible applications to interact with Garage
+Configuring S3-compatible applicatiosn to interact with Garage
 is covered in the [Integrations](@/documentation/connect/_index.md) section.
--- a/doc/book/operations/recovering.md
+++ b/doc/book/operations/recovering.md
@ -1,11 +1,11 @@
 +++
 title = "Recovering from failures"
-weight = 40
+weight = 50
 +++
 Garage is meant to work on old, second-hand hardware.
 In particular, this makes it likely that some of your drives will fail, and some manual intervention will be needed.
-Fear not! Garage is fully equipped to handle drive failures, in most common cases.
+Fear not! For Garage is fully equipped to handle drive failures, in most common cases.
 ## A note on availability of Garage
@ -108,57 +108,3 @@ garage layout apply   # once satisfied, apply the changes
 Garage will then start synchronizing all required data on the new node.
 This process can be monitored using the `garage stats -a` command.
 ## Replacement scenario 3: corrupted metadata {#corrupted_meta}
 In some cases, your metadata DB file might become corrupted, for instance if
 your node suffered a power outage and did not shut down properly. In this case,
 you can recover without having to change the node ID and rebuilding a cluster
 layout. This means that data blocks will not need to be shuffled around, you
 must simply find a way to repair the metadata file. The best way is generally
 to discard the corrupted file and recover it from another source.
 First of all, start by locating the database file in your metadata directory,
 which [depends on your `db_engine`
 choice](@/documentation/reference-manual/configuration.md#db_engine).  Then,
 your recovery options are as follows:
 - **Option 1: resyncing from other nodes.** In case your cluster is replicated
  with two or three copies, you can simply delete the database file, and Garage
  will resync from other nodes. To do so, stop Garage, delete the database file
  or directory, and restart Garage. Then, do a full table repair by calling
  `garage repair -a --yes tables`.  This will take a bit of time to complete as
  the new node will need to receive copies of the metadata tables from the
  network.
 - **Option 2: restoring a snapshot taken by Garage.** Since v0.9.4, Garage can
  [automatically take regular
  snapshots](@/documentation/reference-manual/configuration.md#metadata_auto_snapshot_interval)
  of your metadata DB file. This file or directory should be located under
  `<metadata_dir>/snapshots`, and is named according to the UTC time at which it
  was taken. Stop Garage, discard the database file/directory and replace it by the
  snapshot you want to use. For instance, in the case of LMDB:
  ```bash
  cd $METADATA_DIR
  mv db.lmdb db.lmdb.bak
  cp -r snapshots/2024-03-15T12:13:52Z db.lmdb
  ```
  And for Sqlite:
  ```bash
  cd $METADATA_DIR
  mv db.sqlite db.sqlite.bak
  cp snapshots/2024-03-15T12:13:52Z db.sqlite
  ```
  Then, restart Garage and run a full table repair by calling `garage repair -a
  --yes tables`.  This should run relatively fast as only the changes that
  occurred since the snapshot was taken will need to be resynchronized. Of
  course, if your cluster is not replicated, you will lose all changes that
  occurred since the snapshot was taken.
 - **Option 3: restoring a filesystem-level snapshot.** If you are using ZFS or
  BTRFS to snapshot your metadata partition, refer to their specific
  documentation on rolling back or copying files from an old snapshot.
--- a/doc/book/cookbook/reverse-proxy.md
+++ b/doc/book/cookbook/reverse-proxy.md
@ -168,65 +168,40 @@ Here is [a basic configuration file](https://doc.traefik.io/traefik/https/acme/#
 ### Add Garage service
-To add Garage on Traefik you should declare two new services using its IP
+To add Garage on Traefik you should declare a new service using its IP address (or hostname) and port:
 address (or hostname) and port, these are used for the S3, and web components
 of Garage:
 ```toml
 [http.services]
-  [http.services.garage-s3-service.loadBalancer]
+  [http.services.my_garage_service.loadBalancer]
-    [[http.services.garage-s3-service.loadBalancer.servers]]
+    [[http.services.my_garage_service.loadBalancer.servers]]
      url = "http://xxx.xxx.xxx.xxx"
      port = 3900
  [http.services.garage-web-service.loadBalancer]
    [[http.services.garage-web-service.loadBalancer.servers]]
      url = "http://xxx.xxx.xxx.xxx"
      port = 3902
 ```
 It's possible to declare multiple Garage servers as back-ends:
 ```toml
 [http.services]
-    [[http.services.garage-s3-service.loadBalancer.servers]]
+    [[http.services.my_garage_service.loadBalancer.servers]]
      url = "http://xxx.xxx.xxx.xxx"
      port = 3900
-    [[http.services.garage-s3-service.loadBalancer.servers]]
+    [[http.services.my_garage_service.loadBalancer.servers]]
      url = "http://yyy.yyy.yyy.yyy"
      port = 3900
-    [[http.services.garage-s3-service.loadBalancer.servers]]
+    [[http.services.my_garage_service.loadBalancer.servers]]
      url = "http://zzz.zzz.zzz.zzz"
      port = 3900
    [[http.services.garage-web-service.loadBalancer.servers]]
      url = "http://xxx.xxx.xxx.xxx"
      port = 3902
    [[http.services.garage-web-service.loadBalancer.servers]]
      url = "http://yyy.yyy.yyy.yyy"
      port = 3902
    [[http.services.garage-web-service.loadBalancer.servers]]
      url = "http://zzz.zzz.zzz.zzz"
      port = 3902
 ```
 Traefik can remove unhealthy servers automatically with [a health check configuration](https://doc.traefik.io/traefik/routing/services/#health-check):
 ```
 [http.services]
-  [http.services.garage-s3-service.loadBalancer]
+  [http.services.my_garage_service.loadBalancer]
-    [http.services.garage-s3-service.loadBalancer.healthCheck]
+    [http.services.my_garage_service.loadBalancer.healthCheck]
-      path = "/health"
+      path = "/"
-      port = "3903"
+      interval = "60s"
-      #interval = "15s"
+      timeout = "5s"
      #timeout = "2s"
  [http.services.garage-web-service.loadBalancer]
    [http.services.garage-web-service.loadBalancer.healthCheck]
      path = "/health"
      port = "3903"
      #interval = "15s"
      #timeout = "2s"
 ```
 ### Adding a website
@ -235,15 +210,10 @@ To add a new website, add the following declaration to your Traefik configuratio
 ```toml
 [http.routers]
  [http.routers.garage-s3]
    rule = "Host(`s3.example.org`)"
    service = "garage-s3-service"
    entryPoints = ["websecure"]
  [http.routers.my_website]
    rule = "Host(`yoururl.example.org`)"
-    service = "garage-web-service"
+    service = "my_garage_service"
-    entryPoints = ["websecure"]
+    entryPoints = ["web"]
 ```
 Enable HTTPS access to your website with the following configuration section ([documentation](https://doc.traefik.io/traefik/https/overview/)):
@ -256,7 +226,7 @@ Enable HTTPS access to your website with the following configuration section ([d
 ...
 ```
-### Adding compression
+### Adding gzip compression
 Add the following configuration section [to compress response](https://doc.traefik.io/traefik/middlewares/http/compress/) using [gzip](https://developer.mozilla.org/en-US/docs/Glossary/GZip_compression) before sending them to the client:
@ -264,10 +234,10 @@ Add the following configuration section [to compress response](https://doc.traef
 [http.routers]
  [http.routers.my_website]
    ...
-    middlewares = ["compression"]
+    middlewares = ["gzip_compress"]
    ...
 [http.middlewares]
-  [http.middlewares.compression.compress]
+  [http.middlewares.gzip_compress.compress]
 ```
 ### Add caching response
@ -292,54 +262,27 @@ Traefik's caching middleware is only available on [entreprise version](https://d
    entryPoint = "web"
 [http.routers]
  [http.routers.garage-s3]
    rule = "Host(`s3.example.org`)"
    service = "garage-s3-service"
    entryPoints = ["websecure"]
  [http.routers.my_website]
    rule = "Host(`yoururl.example.org`)"
-    service = "garage-web-service"
+    service = "my_garage_service"
-    middlewares = ["compression"]
+    middlewares = ["gzip_compress"]
    entryPoints = ["websecure"]
 [http.services]
-  [http.services.garage-s3-service.loadBalancer]
+  [http.services.my_garage_service.loadBalancer]
-    [http.services.garage-s3-service.loadBalancer.healthCheck]
+    [http.services.my_garage_service.loadBalancer.healthCheck]
-      path = "/health"
+      path = "/"
-      port = "3903"
+      interval = "60s"
-      #interval = "15s"
+      timeout = "5s"
-      #timeout = "2s"
+    [[http.services.my_garage_service.loadBalancer.servers]]
  [http.services.garage-web-service.loadBalancer]
    [http.services.garage-web-service.loadBalancer.healthCheck]
      path = "/health"
      port = "3903"
      #interval = "15s"
      #timeout = "2s"
    [[http.services.garage-s3-service.loadBalancer.servers]]
      url = "http://xxx.xxx.xxx.xxx"
-      port = 3900
+    [[http.services.my_garage_service.loadBalancer.servers]]
    [[http.services.garage-s3-service.loadBalancer.servers]]
      url = "http://yyy.yyy.yyy.yyy"
-      port = 3900
+    [[http.services.my_garage_service.loadBalancer.servers]]
    [[http.services.garage-s3-service.loadBalancer.servers]]
      url = "http://zzz.zzz.zzz.zzz"
      port = 3900
    [[http.services.garage-web-service.loadBalancer.servers]]
      url = "http://xxx.xxx.xxx.xxx"
      port = 3902
    [[http.services.garage-web-service.loadBalancer.servers]]
      url = "http://yyy.yyy.yyy.yyy"
      port = 3902
    [[http.services.garage-web-service.loadBalancer.servers]]
      url = "http://zzz.zzz.zzz.zzz"
      port = 3902
 [http.middlewares]
-  [http.middlewares.compression.compress]
+  [http.middlewares.gzip_compress.compress]
 ```
 ## Caddy
@ -348,156 +291,18 @@ Your Caddy configuration can be as simple as:
 ```caddy
 s3.garage.tld, *.s3.garage.tld {
-	reverse_proxy localhost:3900 192.168.1.2:3900 example.tld:3900 {
+	reverse_proxy localhost:3900 192.168.1.2:3900 example.tld:3900
        health_uri       /health
        health_port      3903
        #health_interval 15s
        #health_timeout  5s
    }
 }
 *.web.garage.tld {
-	reverse_proxy localhost:3902 192.168.1.2:3902 example.tld:3902 {
+	reverse_proxy localhost:3902 192.168.1.2:3900 example.tld:3900
        health_uri       /health
        health_port      3903
        #health_interval 15s
        #health_timeout  5s
    }
 }
 admin.garage.tld {
-	reverse_proxy localhost:3903 {
+	reverse_proxy localhost:3903
        health_uri       /health
        health_port      3903
        #health_interval 15s
        #health_timeout  5s
    }
 }
 ```
 But at the same time, the `reverse_proxy` is very flexible.
 For a production deployment, you should [read its documentation](https://caddyserver.com/docs/caddyfile/directives/reverse_proxy) as it supports features like DNS discovery of upstreams, load balancing with checks, streaming parameters, etc.
 ### Caching
 Caddy can compiled with a
 [cache plugin](https://github.com/caddyserver/cache-handler) which can be used
 to provide a hot-cache at the webserver-level for static websites hosted by
 Garage.
 This can be configured as follows:
 ```caddy
 # Caddy global configuration section
 {
 	# Bare minimum configuration to enable cache.
 	order cache before rewrite
 	cache
 	#cache
 	#	allowed_http_verbs GET
 	#	default_cache_control public
 	#	ttl 8h
 	#}
 }
 # Site specific section
 https:// {
 	cache
 	#cache {
 	#	timeout {
 	#		backend 30s
 	#	}
 	#}
 	reverse_proxy ...
 }
 ```
 Caching is a complicated subject, and the reader is encouraged to study the
 available options provided by the plugin.
 ### On-demand TLS
 Caddy supports a technique called
 [on-demand TLS](https://caddyserver.com/docs/automatic-https#on-demand-tls), by
 which one can configure the webserver to provision TLS certificates when a
 client first connects to it.
 In order to prevent an attack vector whereby domains are simply pointed at your
 webserver and certificates are requested for them - Caddy can be configured to
 ask Garage if a domain is authorized for web hosting, before it then requests
 a TLS certificate.
 This 'check' endpoint, which is on the admin port (3903 by default), can be
 configured in Caddy's global section as follows:
 ```caddy
 {
 	...
 	on_demand_tls {
 		ask http://localhost:3903/check
 		interval 2m
 		burst 5
 	}
 	...
 }
 ```
 The host section can then be configured with (note that this uses the web
 endpoint instead):
 ```caddy
 # For a specific set of subdomains
 *.web.garage.tld {
 	tls {
 		on_demand
 	}
 	reverse_proxy localhost:3902 192.168.1.2:3902 example.tld:3902
 }
 # Accept all domains on HTTPS
 # Never configure this without global section above
 https:// {
 	tls {
 		on_demand
 	}
 	reverse_proxy localhost:3902 192.168.1.2:3902 example.tld:3902
 }
 ```
 More information on how this endpoint is implemented in Garage is available
 in the [Admin API Reference](@/documentation/reference-manual/admin-api.md) page.
 ### Fileserver browser
 Caddy's built-in
 [file_server](https://caddyserver.com/docs/caddyfile/directives/file_server)
 browser functionality can be extended with the
 [caddy-fs-s3](https://github.com/sagikazarmark/caddy-fs-s3) module.
 This can be configured to use Garage as a backend with the following
 configuration:
 ```caddy
 browse.garage.tld {
    file_server {
        fs s3 {
            bucket test-bucket
            region garage
            endpoint https://s3.garage.tld
            use_path_style
        }
        browse
    }
 }
 ```
 Caddy must also be configured with the required `AWS_ACCESS_KEY_ID` and
 `AWS_SECRET_ACCESS_KEY` environment variables to access the bucket.
--- a/doc/book/cookbook/systemd.md
+++ b/doc/book/cookbook/systemd.md
@ -33,20 +33,7 @@ NoNewPrivileges=true
 WantedBy=multi-user.target
 ```
-**A note on hardening:** Garage will be run as a non privileged user, its user
+*A note on hardening: garage will be run as a non privileged user, its user id is dynamically allocated by systemd. It cannot access (read or write) home folders (/home, /root and /run/user), the rest of the filesystem can only be read but not written, only the path seen as /var/lib/garage is writable as seen by the service (mapped to /var/lib/private/garage on your host). Additionnaly, the process can not gain new privileges over time.*
 id is dynamically allocated by systemd (set with `DynamicUser=true`). It cannot
 access (read or write) home folders (`/home`, `/root` and `/run/user`), the
 rest of the filesystem can only be read but not written, only the path seen as
 `/var/lib/garage` is writable as seen by the service. Additionnaly, the process
 can not gain new privileges over time.
 For this to work correctly, your `garage.toml` must be set with
 `metadata_dir=/var/lib/garage/meta` and `data_dir=/var/lib/garage/data`. This
 is mandatory to use the DynamicUser hardening feature of systemd, which
 autocreates these directories as virtual mapping. If the directory
 `/var/lib/garage` already exists before starting the server for the first time,
 the systemd service might not start correctly.  Note that in your host
 filesystem, Garage data will be held in `/var/lib/private/garage`.
 To start the service then automatically enable it at boot:
--- a/doc/book/cookbook/upgrading.md
+++ b/doc/book/cookbook/upgrading.md
@ -0,0 +1,50 @@
 +++
 title = "Upgrading Garage"
 weight = 60
 +++
 Garage is a stateful clustered application, where all nodes are communicating together and share data structures.
 It makes upgrade more difficult than stateless applications so you must be more careful when upgrading.
 On a new version release, there is 2 possibilities:
  - protocols and data structures remained the same ➡️ this is a **straightforward upgrade**
  - protocols or data structures changed  ➡️  this is an **advanced upgrade**
 You can quickly now what type of update you will have to operate by looking at the version identifier.
 Following the [SemVer ](https://semver.org/) terminology, if only the *patch* number changed, it will only need a straightforward upgrade.
 Example: an upgrade from v0.6.0 from v0.6.1 is a straightforward upgrade.
 If the *minor* or *major* number changed however, you will have to do an advanced upgrade. Example: from v0.6.1 to v0.7.0.
 Migrations are designed to be run only between contiguous versions (from a *major*.*minor* perspective, *patches* can be skipped).
 Example: migrations from v0.6.1 to v0.7.0 and from v0.6.0 to v0.7.0 are supported but migrations from v0.5.0 to v0.7.0 are not supported.
 ## Straightforward upgrades
 Straightforward upgrades do not imply cluster downtime.
 Before upgrading, you should still read [the changelog](https://git.deuxfleurs.fr/Deuxfleurs/garage/releases) and ideally test your deployment on a staging cluster before.
 When you are ready, start by checking the health of your cluster.
 You can force some checks with `garage repair`, we recommend at least running `garage repair --all-nodes --yes` that is very quick to run (less than a minute).
 You will see that the command correctly terminated in the logs of your daemon.
 Finally, you can simply upgrades nodes one by one. 
 For each node: stop it, install the new binary, edit the configuration if needed, restart it. 
 ## Advanced upgrades
 Advanced upgrades will imply cluster downtime.
 Before upgrading, you must read [the changelog](https://git.deuxfleurs.fr/Deuxfleurs/garage/releases) and you must test your deployment on a staging cluster before.
 From a high level perspective, an advanced upgrade looks like this:
  1. Make sure the health of your cluster is good (see `garage repair`)
  2. Disable API access (comment the configuration in your reverse proxy)
  3. Check that your cluster is idle
  4. Stop the whole cluster
  5. Backup the metadata folder of all your nodes, so that you will be able to restore it quickly if the upgrade fails (blocks being immutable, they should not be impacted)
  6. Install the new binary, update the configuration
  7. Start the whole cluster
  8. If needed, run the corresponding migration from `garage migrate`
  9. Make sure the health of your cluster is good
  10. Enable API access (uncomment the configuration in your reverse proxy)
  11. Monitor your cluster while load comes back, check that all your applications are happy with this new version
 We write guides for each advanced upgrade, they are stored under the "Working Documents" section of this documentation.
--- a/doc/book/design/_index.md
+++ b/doc/book/design/_index.md
@ -1,6 +1,6 @@
 +++
 title = "Design"
-weight = 70
+weight = 6
 sort_by = "weight"
 template = "documentation.html"
 +++
@ -20,16 +20,12 @@ and could not do, etc.
 We love to talk and hear about Garage, that's why we keep a log here:
  - [(en, 2023-01-18) Presentation of Garage with some details on CRDTs and data partitioning among nodes](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/4cff37397f626ef063dad29e5b5e97ab1206015d/doc/talks/2023-01-18-tocatta/talk.pdf)
  - [(fr, 2022-11-19) De l'auto-hébergement à l'entre-hébergement : Garage, pour conserver ses données ensemble](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/4cff37397f626ef063dad29e5b5e97ab1206015d/doc/talks/2022-11-19-Capitole-du-Libre/pr%C3%A9sentation.pdf)
  - [(en, 2022-06-23) General presentation of Garage](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/4cff37397f626ef063dad29e5b5e97ab1206015d/doc/talks/2022-06-23-stack/talk.pdf)
  - [(fr, 2021-11-13, video) Garage : Mille et une façons de stocker vos données](https://video.tedomum.net/w/moYKcv198dyMrT8hCS5jz9) and [slides (html)](https://rfid.deuxfleurs.fr/presentations/2021-11-13/garage/) - during [RFID#1](https://rfid.deuxfleurs.fr/programme/2021-11-13/) event
-  - [(en, 2021-04-28) Distributed object storage is centralised](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/b1f60579a13d3c5eba7f74b1775c84639ea9b51a/doc/talks/2021-04-28_spirals-team/talk.pdf)
+  - [(en, 2021-04-28) Distributed object storage is centralised](https://git.deuxfleurs.fr/Deuxfleurs/garage/raw/commit/b1f60579a13d3c5eba7f74b1775c84639ea9b51a/doc/talks/2021-04-28_spirals-team/talk.pdf)
-  - [(fr, 2020-12-02) Garage : jouer dans la cour des grands quand on est un hébergeur associatif](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/commit/b1f60579a13d3c5eba7f74b1775c84639ea9b51a/doc/talks/2020-12-02_wide-team/talk.pdf)
+  - [(fr, 2020-12-02) Garage : jouer dans la cour des grands quand on est un hébergeur associatif](https://git.deuxfleurs.fr/Deuxfleurs/garage/raw/commit/b1f60579a13d3c5eba7f74b1775c84639ea9b51a/doc/talks/2020-12-02_wide-team/talk.pdf)
 *Did you write or talk about Garage? [Open a pull request](https://git.deuxfleurs.fr/Deuxfleurs/garage/) to add a link here!*
--- a/doc/book/design/goals.md
+++ b/doc/book/design/goals.md
@ -42,28 +42,15 @@ locations. They use Garage themselves for the following tasks:
 - As a [Matrix media backend](https://github.com/matrix-org/synapse-s3-storage-provider)
 - To store personal data and shared documents through [Bagage](https://git.deuxfleurs.fr/Deuxfleurs/bagage), a homegrown WebDav-to-S3 proxy
 - In the Drone continuous integration platform to store task logs
 - As a Nix binary cache
- To store personal data and shared documents through [Bagage](https://git.deuxfleurs.fr/Deuxfleurs/bagage), a homegrown WebDav-to-S3 and SFTP-to-S3 proxy
+- As a backup target using `rclone`
 - As a backup target using `rclone` and `restic`
 The Deuxfleurs Garage cluster is a multi-site cluster currently composed of
-9 nodes in 3 physical locations.
+4 nodes in 2 physical locations. In the future it will be expanded to at
-
+least 3 physical locations to fully exploit Garage's potential for high
-### Triplebit
+availability.
 [Triplebit](https://www.triplebit.org) is a non-profit hosting provider and
 ISP focused on improving access to privacy-related services. They use
 Garage themselves for the following tasks:
 - Hosting of their homepage, [privacyguides.org](https://www.privacyguides.org/), and various other static sites
 - As a Mastodon object storage backend for [mstdn.party](https://mstdn.party/) and [mstdn.plus](https://mstdn.plus/)
 - As a PeerTube storage backend for [neat.tube](https://neat.tube/)
 - As a [Matrix media backend](https://github.com/matrix-org/synapse-s3-storage-provider)
 Triplebit's Garage cluster is a multi-site cluster currently composed of
 10 nodes in 3 physical locations.
--- a/doc/book/design/internals.md
+++ b/doc/book/design/internals.md
@ -61,7 +61,7 @@ Garage prioritizes which nodes to query according to a few criteria:
 For further reading on the cluster structure look at the [gateway](@/documentation/cookbook/gateways.md) 
-and [cluster layout management](@/documentation/operations/layout.md) pages.
+and [cluster layout management](@/documentation/reference-manual/layout.md) pages.
 ## Garbage collection
@ -97,7 +97,7 @@ delete a tombstone, the following condition has to be met:
  superseeded by the tombstone. This ensures that deleting the tombstone is
  safe and that no deleted value will come back in the system.
-Garage uses atomic database operations (such as compare-and-swap and
+Garage makes use of Sled's atomic operations (such as compare-and-swap and
 transactions) to ensure that only tombstones that have been correctly
 propagated to other nodes are ever deleted from the local entry tree.
--- a/doc/book/design/related-work.md
+++ b/doc/book/design/related-work.md
@ -67,12 +67,13 @@ Pithos has been abandonned and should probably not used yet, in the following we
 Pithos was relying as a S3 proxy in front of Cassandra (and was working with Scylla DB too).
 From its designers' mouth, storing data in Cassandra has shown its limitations justifying the project abandonment.
 They built a closed-source version 2 that does not store blobs in the database (only metadata) but did not communicate further on it.
-We considered their v2's design but concluded that it does not fit both our *Self-contained & lightweight* and *Simple* properties. It makes the development, the deployment and the operations more complicated while reducing the flexibility.
+We considered there v2's design but concluded that it does not fit both our *Self-contained & lightweight* and *Simple* properties. It makes the development, the deployment and the operations more complicated while reducing the flexibility.
 **[Riak CS](https://docs.riak.com/riak/cs/2.1.1/index.html):**
 *Not written yet*
-**[IPFS](https://ipfs.io/):** IPFS has design goals radically different from Garage, we have [a blog post](@/blog/2022-ipfs/index.md) talking about it.
+**[IPFS](https://ipfs.io/):**
 *Not written yet*
 ## Specific research papers
--- a/doc/book/development/_index.md
+++ b/doc/book/development/_index.md
@ -1,6 +1,6 @@
 +++
 title = "Development"
-weight = 80
+weight = 7
 sort_by = "weight"
 template = "documentation.html"
 +++
--- a/doc/book/development/devenv.md
+++ b/doc/book/development/devenv.md
@ -25,7 +25,7 @@ git clone https://git.deuxfleurs.fr/Deuxfleurs/garage
 cd garage
 ```
-*Optionally, you can use our nix.conf file to speed up compilations:*
+*Optionnaly, you can use our nix.conf file to speed up compilations:*
 ```bash
 sudo mkdir -p /etc/nix
@ -39,7 +39,7 @@ Now you can enter our nix-shell, all the required packages will be downloaded bu
 nix-shell
 ```
-You can use the traditional Rust development workflow:
+You can use the traditionnal Rust development workflow:
 ```bash
 cargo build  # compile the project
@ -80,7 +80,7 @@ nix-build \
  --git_version $(git rev-parse HEAD)
 ```
-*The result is located in `result/bin`. You can pass arguments to cross compile: check `.woodpecker/release.yml` for examples.*
+*The result is located in `result/bin`. You can pass arguments to cross compile: check `.drone.yml` for examples.*
 If you modify a `Cargo.toml` or regenerate any `Cargo.lock`, you must run `cargo2nix`:
--- a/doc/book/development/miscellaneous-notes.md
+++ b/doc/book/development/miscellaneous-notes.md
@ -81,9 +81,12 @@ Our cache will be checked.
 - http://www.lpenz.org/articles/nixchannel/index.html
-## Woodpecker
+## Drone
-Woodpecker can do parallelism both at the step and the pipeline level. At the step level, parallelism is restricted to the same runner.
+Do not try to set a build as trusted from the interface or the CLI tool,
 your request would be ignored. Instead, directly edit the database (table `repos`, column `repo_trusted`).
 Drone can do parallelism both at the step and the pipeline level. At the step level, parallelism is restricted to the same runner.
 ## Building Docker containers
@ -96,4 +99,3 @@ We were:
  - Unable to use the kaniko container provided by Google as we can't run arbitrary logic: we need to put our secret in .docker/config.json.
 Finally we chose to build kaniko through nix and use it in a `nix-shell`.
 We then switched to using kaniko from nixpkgs when it was packaged.
--- a/doc/book/development/release-process.md
+++ b/doc/book/development/release-process.md
@ -11,7 +11,7 @@ We define them as our release process.
 While we run some tests on every commits, we do not make a release for all of them.
 A release can be triggered manually by "promoting" a successful build.
-Otherwise, every night, a release build is triggered on the `main` branch.
+Otherwise, every weeks, a release build is triggered on the `main` branch.
 If the build is from a tag following the regex: `v[0-9]+\.[0-9]+\.[0-9]+`, it will be listed as stable.
 If it is a tag but with a different format, it will be listed as Extra.
@ -42,7 +42,7 @@ and the docker containers on Docker Hub.
 ## Automation
-We automated our release process with Nix and Woodpecker to make it more reliable.
+We automated our release process with Nix and Drone to make it more reliable.
 Here we describe how we have done in case you want to debug or improve it.
 ### Caching build steps
@ -62,31 +62,52 @@ Sending to the cache is done through `nix copy`, for example:
 nix copy --to 's3://nix?endpoint=garage.deuxfleurs.fr&region=garage&secret-key=/etc/nix/signing-key.sec' result
 ```
-*The signing key possessed by the Garage maintainers is required to update the Nix cache.*
+*Note that you need the signing key. In our case, it is stored as a secret in Drone.*
-The previous command will only send the built package and not its dependencies.
+The previous command will only send the built packet and not its dependencies.
-In the case of our CI pipeline, we want to cache all intermediate build steps
+To send its dependency, a tool named `nix-copy-closure` has been created but it is not compatible with the S3 protocol.
-as well. This can be done using this quite involved command (here as an example
+
-for the `pkgs.amd64.relase` package):
+Instead, you can use the following commands to list all the runtime dependencies:
 ```bash
-nix copy -j8 \
+nix copy \
-    --to 's3://nix?endpoint=garage.deuxfleurs.fr&region=garage&secret-key=/etc/nix/nix-signing-key.sec' \
+  --to 's3://nix?endpoint=garage.deuxfleurs.fr&region=garage&secret-key=/etc/nix/signing-key.sec' \
-    $(nix path-info pkgs.amd64.release --file default.nix --derivation --recursive | sed 's/\.drv$/.drv^*/')
+  $(nix-store -qR result/)
 ```
-This command will simultaneously build all of the required Nix paths (using at
+*We could also write this expression with xargs but this tool is not available in our container.*
 most 8 parallel Nix builder jobs) and send the resulting objects to the cache.
-This can be run for all the Garage packages we build using the following command:
+But in certain cases, we want to cache compile time dependencies also.
 For example, the Nix project does not provide binaries for cross compiling to i686 and thus we need to compile gcc on our own.
 We do not want to compile gcc each time, so even if it is a compile time dependency, we want to cache it.
 This time, the command is a bit more involved:
 ```bash
 nix copy --to \
  's3://nix?endpoint=garage.deuxfleurs.fr&region=garage&secret-key=/etc/nix/signing-key.sec' \
   $(nix-store -qR --include-outputs \
     $(nix-instantiate))
 ```
 This is the command we use in our CI as we expect the final binary to change, so we mainly focus on
 caching our development dependencies.
 *Currently there is no automatic garbage collection of the cache: we should monitor its growth.
 Hopefully, we can erase it totally without breaking any build, the next build will only be slower.*
 In practise, we concluded that we do not want to cache all the compilation dependencies.
 Instead, we want to cache the toolchain we use to build Garage each time we change it.
 So we removed from Drone any automatic update of the cache and instead handle them manually with:
 ```
 source ~/.awsrc
-nix-shell --attr cache --run 'refresh_cache'
+nix-shell --run 'refresh_toolchain'
 ```
-We don't automate this step at each CI build, as *there is currently no automatic garbage collection of the cache.*
+Internally, it will run `nix-build` on  `nix/toolchain.nix` and send the output plus its depedencies to the cache.
-This means we should also monitor the cache's size; if it ever becomes too big we can erase it with:
+
 To erase the cache:
 ```
 mc rm --recursive --force 'garage/nix/'
@ -136,9 +157,9 @@ nix-shell --run refresh_index
 If you want to compile for different architectures, you will need to repeat all these commands for each architecture.
-**In practice, and except for debugging, you will never directly run these commands. Release is handled by Woodpecker.**
+**In practise, and except for debugging, you will never directly run these commands. Release is handled by drone**
-### Drone (obsolete)
+### Drone
 Our instance is available at [https://drone.deuxfleurs.fr](https://drone.deuxfleurs.fr).  
 You need an account on [https://git.deuxfleurs.fr](https://git.deuxfleurs.fr) to use it.
--- a/doc/book/operations/_index.md
+++ b/doc/book/operations/_index.md
@ -1,23 +0,0 @@
 +++
 title = "Operations & Maintenance"
 weight = 50
 sort_by = "weight"
 template = "documentation.html"
 +++
 This section contains a number of important information on how to best operate a Garage cluster,
 to ensure integrity and availability of your data:
 - **[Upgrading Garage](@/documentation/operations/upgrading.md):** General instructions on how to
  upgrade your cluster from one version to the next. Instructions specific for each version upgrade
  can bef ound in the [working documents](@/documentation/working-documents/_index.md) section.
 - **[Layout management](@/documentation/operations/layout.md):** Best practices for using the `garage layout`
  commands when adding or removing nodes from your cluster.
 - **[Durability and repairs](@/documentation/operations/durability-repairs.md):** How to check for small things
  that might be going wrong, and how to recover from such failures.
 - **[Recovering from failures](@/documentation/operations/recovering.md):** Garage's first selling point is resilience
  to hardware failures. This section explains how to recover from such a failure in the
  best possible way.
--- a/doc/book/operations/durability-repairs.md
+++ b/doc/book/operations/durability-repairs.md
@ -1,147 +0,0 @@
 +++
 title = "Durability & Repairs"
 weight = 30
 +++
 To ensure the best durability of your data and to fix any inconsistencies that may
 pop up in a distributed system, Garage provides a series of repair operations.
 This guide will explain the meaning of each of them and when they should be applied.
 # General syntax of repair operations
 Repair operations described below are of the form `garage repair <repair_name>`.
 These repairs will not launch without the `--yes` flag, which should
 be added as follows: `garage repair --yes <repair_name>`.
 By default these repair procedures will only run on the Garage node your CLI is
 connecting to. To run on all nodes, add the `-a` flag as follows:
 `garage repair -a --yes <repair_name>`.
 # Data block operations
 ## Data store scrub {#scrub}
 Scrubbing the data store means examining each individual data block to check that
 their content is correct, by verifying their hash. Any block found to be corrupted
 (e.g. by bitrot or by an accidental manipulation of the datastore) will be
 restored from another node that holds a valid copy.
 Scrubs are automatically scheduled by Garage to run every 25-35 days (the
 actual time is randomized to spread load across nodes). The next scheduled run
 can be viewed with `garage worker get`.
 A scrub can also be launched manually using `garage repair scrub start`.
 To view the status of an ongoing scrub, first find the task ID of the scrub worker
 using `garage worker list`. Then, run `garage worker info <scrub_task_id>` to
 view detailed runtime statistics of the scrub. To gather cluster-wide information,
 this command has to be run on each individual node.
 A scrub is a very disk-intensive operation that might slow down your cluster.
 You may pause an ongoing scrub using `garage repair scrub pause`, but note that
 the scrub will resume automatically 24 hours later as Garage will not let your
 cluster run without a regular scrub. If the scrub procedure is too intensive
 for your servers and is slowing down your workload, the recommended solution
 is to increase the "scrub tranquility" using `garage repair scrub set-tranquility`.
 A higher tranquility value will make Garage take longer pauses between two block
 verifications. Of course, scrubbing the entire data store will also take longer.
 ## Block check and resync
 In some cases, nodes hold a reference to a block but do not actually have the block
 stored on disk. Conversely, they may also have on-disk blocks that are not referenced
 any more. To fix both cases, a block repair may be run with `garage repair blocks`.
 This will scan the entire block reference counter table to check that the blocks
 exist on disk, and will scan the entire disk store to check that stored blocks
 are referenced.
 It is recommended to run this procedure when changing your cluster layout,
 after the metadata tables have finished synchronizing between nodes
 (usually a few hours after `garage layout apply`).
 ## Inspecting lost blocks
 In extremely rare situations, data blocks may be unavailable from the entire cluster.
 This means that even using `garage repair blocks`, some nodes may be unable
 to fetch data blocks for which they hold a reference.
 These errors are stored on each node in a list of "block resync errors", i.e.
 blocks for which the last resync operation failed.
 This list can be inspected using `garage block list-errors`.
 These errors usually fall into one of the following categories:
 1. a block is still referenced but the object was deleted, this is a case
   of metadata reference inconsistency (see below for the fix)
 2. a block is referenced by a non-deleted object, but could not be fetched due
   to a transient error such as a network failure
 3. a block is referenced by a non-deleted object, but could not be fetched due
   to a permanent error such as there not being any valid copy of the block on the
   entire cluster
 To help make the difference between cases 1 and cases 2 and 3, you may use the
 `garage block info` command to see which objects hold a reference to each block.
 In the second case (transient errors), Garage will try to fetch the block again
 after a certain time, so the error should disappear naturally. You can also
 request Garage to try to fetch the block immediately using `garage block retry-now`
 if you have fixed the transient issue.
 If you are confident that you are in the third scenario and that your data block
 is definitely lost, then there is no other choice than to declare your S3 objects
 as unrecoverable, and to delete them properly from the data store. This can be done
 using the `garage block purge` command.
 ## Rebalancing data directories
 In [multi-HDD setups](@/documentation/operations/multi-hdd.md), to ensure that
 data blocks are well balanced between storage locations, you may run a
 rebalance operation using `garage repair rebalance`. This is useful when
 adding storage locations or when capacities of the storage locations have been
 changed.  Once this is finished, Garage will know for each block of a single
 possible location where it can be, which can increase access speed.  This
 operation will also move out all data from locations marked as read-only.
 # Metadata operations
 ## Metadata snapshotting
 It is good practice to setup automatic snapshotting of your metadata database
 file, to recover from situations where it becomes corrupted on disk. This can
 be done at the filesystem level if you are using ZFS or BTRFS.
 Since Garage v0.9.4, Garage is able to take snapshots of the metadata database
 itself. This basically amounts to copying the database file, except that it can
 be run live while Garage is running without the risk of corruption or
 inconsistencies.  This can be setup to run automatically on a schedule using
 [`metadata_auto_snapshot_interval`](@/documentation/reference-manual/configuration.md#metadata_auto_snapshot_interval).
 A snapshot can also be triggered manually using the `garage meta snapshot`
 command. Note that taking a snapshot using this method is very intensive as it
 requires making a full copy of the database file, so you might prefer using
 filesystem-level snapshots if possible. To recover a corrupted node from such a
 snapshot, read the instructions
 [here](@/documentation/operations/recovering.md#corrupted_meta).
 ## Metadata table resync
 Garage automatically resyncs all entries stored in the metadata tables every hour,
 to ensure that all nodes have the most up-to-date version of all the information
 they should be holding.
 The resync procedure is based on a Merkle tree that allows to efficiently find
 differences between nodes.
 In some special cases, e.g. before an upgrade, you might want to run a table
 resync manually. This can be done using `garage repair tables`.
 ## Metadata table reference fixes
 In some very rare cases where nodes are unavailable, some references between objects
 are broken. For instance, if an object is deleted, the underlying versions or data
 blocks may still be held by Garage. If you suspect that such corruption has occurred
 in your cluster, you can run one of the following repair procedures:
 - `garage repair versions`: checks that all versions belong to a non-deleted object, and purges any orphan version
 - `garage repair block-refs`: checks that all block references belong to a non-deleted object version, and purges any orphan block reference (this will then allow the blocks to be garbage-collected)
 - `garage repair block-rc`: checks that the reference counters for blocks are in sync with the actual number of non-deleted entries in the block reference table
--- a/doc/book/operations/layout.md
+++ b/doc/book/operations/layout.md
@ -1,274 +0,0 @@
 +++
 title = "Cluster layout management"
 weight = 20
 +++
 The cluster layout in Garage is a table that assigns to each node a role in
 the cluster. The role of a node in Garage can either be a storage node with
 a certain capacity, or a gateway node that does not store data and is only
 used as an API entry point for faster cluster access.
 An introduction to building cluster layouts can be found in the [production deployment](@/documentation/cookbook/real-world.md) page.
 In Garage, all of the data that can be stored in a given cluster is divided
 into slices which we call *partitions*. Each partition is stored by
 one or several nodes in the cluster
 (see [`replication_factor`](@/documentation/reference-manual/configuration.md#replication_factor)).
 The layout determines the correspondence between these partitions,
 which exist on a logical level, and actual storage nodes.
 ## How cluster layouts work in Garage
 A cluster layout is composed of the following components:
 - a table of roles assigned to nodes, defined by the user
 - an optimal assignation of partitions to nodes, computed by an algorithm that is ran once when calling `garage layout apply` or the ApplyClusterLayout API endpoint
 - a version number
 Garage nodes will always use the cluster layout with the highest version number.
 Garage nodes also maintain and synchronize between them a set of proposed role
 changes that haven't yet been applied. These changes will be applied (or
 canceled) in the next version of the layout.
 All operations on the layout can be realized using the `garage` CLI or using the
 [administration API endpoint](@/documentation/reference-manual/admin-api.md).
 We give here a description of CLI commands, the admin API semantics are very similar.
 The following commands insert modifications to the set of proposed role changes
 for the next layout version (but they do not create the new layout immediately):
 ```bash
 garage layout assign [...]
 garage layout remove [...]
 ```
 The following command can be used to inspect the layout that is currently set in the cluster
 and the changes proposed for the next layout version, if any:
 ```bash
 garage layout show
 ```
 The following commands create a new layout with the specified version number,
 that either takes into account the proposed changes or cancels them:
 ```bash
 garage layout apply --version <new_version_number>
 garage layout revert --version <new_version_number>
 ```
 The version number of the new layout to create must be 1 + the version number
 of the previous layout that existed in the cluster.  The `apply` and `revert`
 commands will fail otherwise.
 ## Warnings about Garage cluster layout management
 **⚠️ Never make several calls to `garage layout apply` or `garage layout
 revert` with the same value of the `--version` flag. Doing so can lead to the
 creation of several different layouts with the same version number, in which
 case your Garage cluster will become inconsistent until fixed.** If a call to
 `garage layout apply` or `garage layout revert` has failed and `garage layout
 show` indicates that a new layout with the given version number has not been
 set in the cluster, then it is fine to call the command again with the same
 version number.
 If you are using the `garage` CLI by typing individual commands in your
 shell, you shouldn't have much issues as long as you run commands one after
 the other and take care of checking the output of `garage layout show`
 before applying any changes.
 If you are using the `garage` CLI or the admin API to script layout changes,
 follow the following recommendations:
 - If using the CLI, make all of your `garage` CLI calls to the same RPC host.
  If using the admin API, make all of your API calls to the same Garage node. Do
  not connect to individual nodes to send them each a piece of the layout changes
  you are making, as the changes propagate asynchronously between nodes and might
  not all be taken into account at the time when the new layout is applied.
 - **Only call `garage layout apply`/ApplyClusterLayout once**, and call it
  **strictly after** all of the `layout assign` and `layout remove`
  commands/UpdateClusterLayout API calls have returned.
 ## Understanding unexpected layout calculations
 When adding, removing or modifying nodes in a cluster layout, sometimes
 unexpected assignations of partitions to node can occur. These assignations
 are in fact normal and logical, given the objectives of the algorithm.  Indeed,
 **the layout algorithm prioritizes moving less data between nodes over
 achieving equal distribution of load. It also tries to use all links between
 pairs of nodes in equal proportions when moving data.**  This section presents
 two examples and illustrates how one can control Garage's behavior to obtain
 the desired results.
 ### Example 1
 In this example, a cluster is originally composed of 3 nodes in 3 different
 zones (data centers).  The three nodes are of equal capacity, therefore they
 are all fully exploited and all store a copy of all of the data in the cluster.
 Then, a fourth node of the same size is added in the datacenter `dc1`.
 As illustrated by the following, **Garage will by default not store any data on the new node**:
 ```
 $ garage layout show
 ==== CURRENT CLUSTER LAYOUT ====
 ID                Tags   Zone  Capacity   Usable capacity
 b10c110e4e854e5a  node1  dc1   1000.0 MB  1000.0 MB (100.0%)
 a235ac7695e0c54d  node2  dc2   1000.0 MB  1000.0 MB (100.0%)
 62b218d848e86a64  node3  dc3   1000.0 MB  1000.0 MB (100.0%)
 Zone redundancy: maximum
 Current cluster layout version: 6
 ==== STAGED ROLE CHANGES ====
 ID                Tags   Zone  Capacity
 a11c7cf18af29737  node4  dc1   1000.0 MB
 ==== NEW CLUSTER LAYOUT AFTER APPLYING CHANGES ====
 ID                Tags   Zone  Capacity   Usable capacity
 b10c110e4e854e5a  node1  dc1   1000.0 MB  1000.0 MB (100.0%)
 a11c7cf18af29737  node4  dc1   1000.0 MB  0 B (0.0%)
 a235ac7695e0c54d  node2  dc2   1000.0 MB  1000.0 MB (100.0%)
 62b218d848e86a64  node3  dc3   1000.0 MB  1000.0 MB (100.0%)
 Zone redundancy: maximum
 ==== COMPUTATION OF A NEW PARTITION ASSIGNATION ====
 Partitions are replicated 3 times on at least 3 distinct zones.
 Optimal partition size:                     3.9 MB (3.9 MB in previous layout)
 Usable capacity / total cluster capacity:   3.0 GB / 4.0 GB (75.0 %)
 Effective capacity (replication factor 3):  1000.0 MB
 A total of 0 new copies of partitions need to be transferred.
 dc1                 Tags   Partitions        Capacity   Usable capacity
  b10c110e4e854e5a  node1  256 (0 new)       1000.0 MB  1000.0 MB (100.0%)
  a11c7cf18af29737  node4  0 (0 new)         1000.0 MB  0 B (0.0%)
  TOTAL                    256 (256 unique)  2.0 GB     1000.0 MB (50.0%)
 dc2                 Tags   Partitions        Capacity   Usable capacity
  a235ac7695e0c54d  node2  256 (0 new)       1000.0 MB  1000.0 MB (100.0%)
  TOTAL                    256 (256 unique)  1000.0 MB  1000.0 MB (100.0%)
 dc3                 Tags   Partitions        Capacity   Usable capacity
  62b218d848e86a64  node3  256 (0 new)       1000.0 MB  1000.0 MB (100.0%)
  TOTAL                    256 (256 unique)  1000.0 MB  1000.0 MB (100.0%)
 ```
 While unexpected, this is logical because of the following facts:
 - storing some data on the new node does not help increase the total quantity
  of data that can be stored on the cluster, as the two other zones (`dc2` and
  `dc3`) still need to store a full copy of everything, and their capacity is
  still the same;
 - there is therefore no need to move any data on the new node as this would be pointless;
 - moving data to the new node has a cost which the algorithm decides to not pay if not necessary.
 This distribution of data can however not be what the administrator wanted: if
 they added a new node to `dc1`, it might be because the existing node is too
 slow, and they wish to divide its load by half. In that case, what they need to
 do to force Garage to distribute the data between the two nodes is to attribute
 only half of the capacity to each node in `dc1` (in our example, 500M instead of 1G).
 In that case, Garage would determine that to be able to store 1G in total, it
 would need to store 500M on the old node and 500M on the added one.
 ### Example 2
 The following example is a slightly different scenario, where `dc1` had two
 nodes that were used at 50%, and `dc2` and `dc3` each have one node that is
 100% used. All node capacities are the same.
 Then, a node from `dc1` is moved into `dc3`. One could expect that the roles of
 `dc1` and `dc3` would simply be swapped: the remaining node in `dc1` would be
 used at 100%, and the two nodes now in `dc3` would be used at 50%. Instead,
 this happens:
 ```
 ==== CURRENT CLUSTER LAYOUT ====
 ID                Tags   Zone  Capacity   Usable capacity
 b10c110e4e854e5a  node1  dc1   1000.0 MB  500.0 MB (50.0%)
 a11c7cf18af29737  node4  dc1   1000.0 MB  500.0 MB (50.0%)
 a235ac7695e0c54d  node2  dc2   1000.0 MB  1000.0 MB (100.0%)
 62b218d848e86a64  node3  dc3   1000.0 MB  1000.0 MB (100.0%)
 Zone redundancy: maximum
 Current cluster layout version: 8
 ==== STAGED ROLE CHANGES ====
 ID                Tags   Zone  Capacity
 a11c7cf18af29737  node4  dc3   1000.0 MB
 ==== NEW CLUSTER LAYOUT AFTER APPLYING CHANGES ====
 ID                Tags   Zone  Capacity   Usable capacity
 b10c110e4e854e5a  node1  dc1   1000.0 MB  1000.0 MB (100.0%)
 a235ac7695e0c54d  node2  dc2   1000.0 MB  1000.0 MB (100.0%)
 62b218d848e86a64  node3  dc3   1000.0 MB  753.9 MB (75.4%)
 a11c7cf18af29737  node4  dc3   1000.0 MB  246.1 MB (24.6%)
 Zone redundancy: maximum
 ==== COMPUTATION OF A NEW PARTITION ASSIGNATION ====
 Partitions are replicated 3 times on at least 3 distinct zones.
 Optimal partition size:                     3.9 MB (3.9 MB in previous layout)
 Usable capacity / total cluster capacity:   3.0 GB / 4.0 GB (75.0 %)
 Effective capacity (replication factor 3):  1000.0 MB
 A total of 128 new copies of partitions need to be transferred.
 dc1                 Tags   Partitions        Capacity   Usable capacity
  b10c110e4e854e5a  node1  256 (128 new)     1000.0 MB  1000.0 MB (100.0%)
  TOTAL                    256 (256 unique)  1000.0 MB  1000.0 MB (100.0%)
 dc2                 Tags   Partitions        Capacity   Usable capacity
  a235ac7695e0c54d  node2  256 (0 new)       1000.0 MB  1000.0 MB (100.0%)
  TOTAL                    256 (256 unique)  1000.0 MB  1000.0 MB (100.0%)
 dc3                 Tags   Partitions        Capacity   Usable capacity
  62b218d848e86a64  node3  193 (0 new)       1000.0 MB  753.9 MB (75.4%)
  a11c7cf18af29737  node4  63 (0 new)        1000.0 MB  246.1 MB (24.6%)
  TOTAL                    256 (256 unique)  2.0 GB     1000.0 MB (50.0%)
 ```
 As we can see, the node that was moved to `dc3` (node4) is only used at 25% (approximatively),
 whereas the node that was already in `dc3` (node3) is used at 75%.
 This can be explained by the following:
 - node1 will now be the only node remaining in `dc1`, thus it has to store all
  of the data in the cluster. Since it was storing only half of it before, it has
  to retrieve the other half from other nodes in the cluster.
 - The data which it does not have is entirely stored by the other node that was
  in `dc1` and that is now in `dc3` (node4). There is also a copy of it on node2
  and node3 since both these nodes have a copy of everything.
 - node3 and node4 are the two nodes that will now be in a datacenter that is
 under-utilized (`dc3`), this means that those are the two candidates from which
 data can be removed to be moved to node1.
 - Garage will move data in equal proportions from all possible sources, in this
  case it means that it will tranfer 25% of the entire data set from node3 to
  node1 and another 25% from node4 to node1.
 This explains why node3 ends with 75% utilization (100% from before minus 25%
 that is moved to node1), and node4 ends with 25% (50% from before minus 25%
 that is moved to node1).
 This illustrates the second principle of the layout computation: **if there is
 a choice in moving data out of some nodes, then all links between pairs of
 nodes are used in equal proportions** (this is approximately true, there is
 randomness in the algorithm to achieve this so there might be some small
 fluctuations, as we see above).
--- a/doc/book/operations/multi-hdd.md
+++ b/doc/book/operations/multi-hdd.md
@ -1,101 +0,0 @@
 +++
 title = "Multi-HDD support"
 weight = 15
 +++
 Since v0.9, Garage natively supports nodes that have several storage drives
 for storing data blocks (not for metadata storage).
 ## Initial setup
 To set up a new Garage storage node with multiple HDDs,
 format and mount all your drives in different directories,
 and use a Garage configuration as follows:
 ```toml
 data_dir = [
    { path = "/path/to/hdd1", capacity = "2T" },
    { path = "/path/to/hdd2", capacity = "4T" },
 ]
 ```
 Garage will automatically balance all blocks stored by the node
 among the different specified directories, proportionnally to the
 specified capacities.
 ## Updating the list of storage locations
 If you add new storage locations to your `data_dir`,
 Garage will not rebalance existing data between storage locations.
 Newly written blocks will be balanced proportionnally to the specified capacities,
 and existing data may be moved between drives to improve balancing,
 but only opportunistically when a data block is re-written (e.g. an object
 is re-uploaded, or an object with a duplicate block is uploaded).
 To understand precisely what is happening, we need to dive in to how Garage
 splits data among the different storage locations.
 First of all, Garage divides the set of all possible block hashes
 in a fixed number of slices (currently 1024), and assigns
 to each slice a primary storage location among the specified data directories.
 The number of slices having their primary location in each data directory
 is proportionnal to the capacity specified in the config file.
 When Garage receives a block to write, it will always write it in the primary
 directory of the slice that contains its hash.
 Now, to be able to not lose existing data blocks when storage locations
 are added, Garage also keeps a list of secondary data directories
 for all of the hash slices. Secondary data directories for a slice indicates
 storage locations that once were primary directories for that slice, i.e. where
 Garage knows that data blocks of that slice might be stored.
 When Garage is requested to read a certain data block,
 it will first look in the primary storage directory of its slice,
 and if it doesn't find it there it goes through all of the secondary storage
 locations until it finds it. This allows Garage to continue operating
 normally when storage locations are added, without having to shuffle
 files between drives to place them in the correct location.
 This relatively simple strategy works well but does not ensure that data
 is correctly balanced among drives according to their capacity.
 To rebalance data, two strategies can be used:
 - Lazy rebalancing: when a block is re-written (e.g. the object is re-uploaded),
  Garage checks whether the existing copy is in the primary directory of the slice
  or in a secondary directory. If the current copy is in a secondary directory,
  Garage re-writes a copy in the primary directory and deletes the one from the
  secondary directory. This might never end up rebalancing everything if there
  are data blocks that are only read and never written.
 - Active rebalancing: an operator of a Garage node can explicitly launch a repair
  procedure that rebalances the data directories, moving all blocks to their
  primary location. Once done, all secondary locations for all hash slices are
  removed so that they won't be checked anymore when looking for a data block.
 ## Read-only storage locations
 If you would like to move all data blocks from an existing data directory to one
 or several new data directories, mark the old directory as read-only:
 ```toml
 data_dir = [
    { path = "/path/to/old_data", read_only = true },
    { path = "/path/to/new_hdd1", capacity = "2T" },
    { path = "/path/to/new_hdd2", capacity = "4T" },
 ]
 ```
 Garage will be able to read requested blocks from the read-only directory.
 Garage will also move data out of the read-only directory either progressively
 (lazy rebalancing) or if requested explicitly (active rebalancing).
 Once an active rebalancing has finished, your read-only directory should be empty:
 it might still contain subdirectories, but no data files. You can check that
 it contains no files using:
 ```bash
 find -type f /path/to/old_data      # should not print anything
 ```
 at which point it can be removed from the `data_dir` list in your config file.
--- a/doc/book/operations/upgrading.md
+++ b/doc/book/operations/upgrading.md
@ -1,97 +0,0 @@
 +++
 title = "Upgrading Garage"
 weight = 10
 +++
 Garage is a stateful clustered application, where all nodes are communicating together and share data structures.
 It makes upgrade more difficult than stateless applications so you must be more careful when upgrading.
 On a new version release, there is 2 possibilities:
  - protocols and data structures remained the same ➡️ this is a **minor upgrade**
  - protocols or data structures changed  ➡️  this is a **major upgrade**
 You can quickly know what type of update you will have to operate by looking at the version identifier:
 when we require our users to do a major upgrade, we will always bump the first nonzero component of the version identifier
 (e.g. from v0.7.2 to v0.8.0).
 Conversely, for versions that only require a minor upgrade, the first nonzero component will always stay the same (e.g. from v0.8.0 to v0.8.1).
 Major upgrades are designed to be run only between contiguous versions.
 Example: migrations from v0.7.1 to v0.8.0 and from v0.7.0 to v0.8.2 are supported but migrations from v0.6.0 to v0.8.0 are not supported.
 The `garage_build_info`
 [Prometheus metric](@/documentation/reference-manual/monitoring.md) provides
 an overview for which Garage versions are currently in use within a cluster.
 ## Minor upgrades
 Minor upgrades do not imply cluster downtime.
 Before upgrading, you should still read [the changelog](https://git.deuxfleurs.fr/Deuxfleurs/garage/releases) and ideally test your deployment on a staging cluster before.
 When you are ready, start by checking the health of your cluster.
 You can force some checks with `garage repair`, we recommend at least running `garage repair --all-nodes --yes tables` which is very quick to run (less than a minute).
 You will see that the command correctly terminated in the logs of your daemon, or using `garage worker list` (the repair workers should be in the `Done` state).
 Finally, you can simply upgrade nodes one by one.
 For each node: stop it, install the new binary, edit the configuration if needed, restart it.
 ## Major upgrades
 Major upgrades can be done with minimal downtime with a bit of preparation, but the simplest way is usually to put the cluster offline for the duration of the migration.
 Before upgrading, you must read [the changelog](https://git.deuxfleurs.fr/Deuxfleurs/garage/releases) and you must test your deployment on a staging cluster before.
 We write guides for each major upgrade, they are stored under the "Working Documents" section of this documentation.
 ### Major upgrades with full downtime
 From a high level perspective, a major upgrade looks like this:
  1. Disable API access (for instance in your reverse proxy, or by commenting the corresponding section in your Garage configuration file and restarting Garage)
  2. Check that your cluster is idle
  3. Make sure the health of your cluster is good (see `garage repair`)
  4. Stop the whole cluster
  5. Back up the metadata folder of all your nodes, so that you will be able to restore it if the upgrade fails (data blocks being immutable, they should not be impacted)
  6. Install the new binary, update the configuration
  7. Start the whole cluster
  8. If needed, run the corresponding migration from `garage migrate`
  9. Make sure the health of your cluster is good
  10. Enable API access (reverse step 1)
  11. Monitor your cluster while load comes back, check that all your applications are happy with this new version
 ### Major upgarades with minimal downtime
 There is only one operation that has to be coordinated cluster-wide: the switch of one version of the internal RPC protocol to the next.
 This means that an upgrade with very limited downtime can simply be performed from one major version to the next by restarting all nodes
 simultaneously in the new version.
 The downtime will simply be the time required for all nodes to stop and start again, which should be less than a minute.
 If all nodes fail to stop and restart simultaneously, some nodes might be temporarily shut out from the cluster as nodes using different RPC protocol
 versions are prevented to talk to one another.
 The entire procedure would look something like this:
 1. Make sure the health of your cluster is good (see `garage repair`)
 2. Take each node offline individually to back up its metadata folder, bring them back online once the backup is done.
  You can do all of the nodes in a single zone at once as that won't impact global cluster availability.
  Do not try to make a backup of the metadata folder of a running node.
  **Since Garage v0.9.4,** you can use the `garage meta snapshot --all` command
  to take a simultaneous snapshot of the metadata database files of all your
  nodes.  This avoids the tedious process of having to take them down one by
  one before upgrading. Be careful that if automatic snapshotting is enabled,
  Garage only keeps the last two snapshots and deletes older ones, so you might
  want to disable automatic snapshotting in your upgraded configuration file
  until you have confirmed that the upgrade ran successfully.  In addition to
  snapshotting the metadata databases of your nodes, you should back-up at
  least the `cluster_layout` file of one of your Garage instances (this file
  should be the same on all nodes and you can copy it safely while Garage is
  running).
 3. Prepare your binaries and configuration files for the new Garage version
 4. Restart all nodes simultaneously in the new version
 5. If any specific migration procedure is required, it is usually in one of the two cases:
  - It can be run on online nodes after the new version has started, during regular cluster operation.
  - it has to be run offline, in which case you will have to again take all nodes offline one after the other to run the repair
   For this last step, please refer to the specific documentation pertaining to the version upgrade you are doing.
--- a/doc/book/quick-start/_index.md
+++ b/doc/book/quick-start/_index.md
@ -1,6 +1,6 @@
 +++
 title = "Quick Start"
-weight = 10
+weight = 0
 sort_by = "weight"
 template = "documentation.html"
 +++
@ -35,20 +35,10 @@ Place this binary somewhere in your `$PATH` so that you can invoke the `garage`
 command directly (for instance you can copy the binary in `/usr/local/bin`
 or in `~/.local/bin`).
 You may also check whether your distribution already includes a
 [binary package for Garage](@/documentation/cookbook/binary-packages.md).
 If a binary of the last version is not available for your architecture,
 or if you want a build customized for your system,
 you can [build Garage from source](@/documentation/cookbook/from-source.md).
 If none of these option work for you, you can also run Garage in a Docker
 container.  When using Docker, the commands used in this guide will not work
 anymore.  We recommend reading the tutorial on [configuring a
 multi-node cluster](@/documentation/cookbook/real-world.md) to learn about
 using Garage as a Docker container. For simplicity, a minimal command to launch
 Garage using Docker is provided in this quick start guide as well.
 ## Configuring and starting Garage
@ -64,9 +54,9 @@ to generate unique and private secrets for security reasons:
 cat > garage.toml <<EOF
 metadata_dir = "/tmp/meta"
 data_dir = "/tmp/data"
-db_engine = "sqlite"
+db_engine = "lmdb"
-replication_factor = 1
+replication_mode = "none"
 rpc_bind_addr = "[::]:3901"
 rpc_public_addr = "127.0.0.1:3901"
@ -86,17 +76,14 @@ index = "index.html"
 api_bind_addr = "[::]:3904"
 [admin]
-api_bind_addr = "[::]:3903"
+api_bind_addr = "0.0.0.0:3903"
 admin_token = "$(openssl rand -base64 32)"
 metrics_token = "$(openssl rand -base64 32)"
 EOF
 ```
-See the [Configuration file format](https://garagehq.deuxfleurs.fr/documentation/reference-manual/configuration/)
+Now that your configuration file has been created, you can put
-for complete options and values.
+it in the right place. By default, garage looks at **`/etc/garage.toml`.**
 Now that your configuration file has been created, you may save it to the directory of your choice.
 By default, Garage looks for **`/etc/garage.toml`.**
 You can also store it somewhere else, but you will have to specify `-c path/to/garage.toml`
 at each invocation of the `garage` binary (for example: `garage -c ./garage.toml server`, `garage -c ./garage.toml status`).
@ -113,39 +100,16 @@ your data to be persisted properly.
 ### Launching the Garage server
-Use the following command to launch the Garage server:
+Use the following command to launch the Garage server with our configuration file:
 ```
-garage -c path/to/garage.toml server
+garage server
 ```
-If you have placed the `garage.toml` file in `/etc` (its default location), you can simply run `garage server`.
+You can tune Garage's verbosity as follows (from less verbose to more verbose):
 Alternatively, if you cannot or do not wish to run the Garage binary directly,
 you may use Docker to run Garage in a container using the following command:
 ```bash
 docker run \
  -d \
  --name garaged \
  -p 3900:3900 -p 3901:3901 -p 3902:3902 -p 3903:3903 \
  -v /etc/garage.toml:/path/to/garage.toml \
  -v /var/lib/garage/meta:/path/to/garage/meta \
  -v /var/lib/garage/data:/path/to/garage/data \
  dxflrs/garage:v0.9.4
 ```
-
+RUST_LOG=garage=info garage server
 Under Linux, you can substitute `--network host` for `-p 3900:3900 -p 3901:3901 -p 3902:3902 -p 3903:3903`
 #### Troubleshooting
 Ensure your configuration file, `metadata_dir` and `data_dir`  are readable by the user running the `garage` server or Docker.
 You can tune Garage's verbosity by setting the `RUST_LOG=` environment variable. \
 Available log levels are (from less verbose to more verbose): `error`, `warn`, `info` *(default)*, `debug` and `trace`.
 ```bash
 RUST_LOG=garage=info garage server # default
 RUST_LOG=garage=debug garage server
 RUST_LOG=garage=trace garage server
 ```
@ -159,10 +123,7 @@ Log level `debug` can help you check why your S3 API calls are not working.
 The `garage` utility is also used as a CLI tool to configure your Garage deployment.
 It uses values from the TOML configuration file to find the Garage daemon running on the
 local node, therefore if your configuration file is not at `/etc/garage.toml` you will
-again have to specify `-c path/to/garage.toml` at each invocation.
+again have to specify `-c path/to/garage.toml`.
 If you are running Garage in a Docker container, you can set `alias garage="docker exec -ti <container name> /garage"`
 to use the Garage binary inside your container.
 If the `garage` CLI is able to correctly detect the parameters of your local Garage node,
 the following command should be enough to show the status of your cluster:
@ -176,7 +137,7 @@ This should show something like this:
 ```
 ==== HEALTHY NODES ====
 ID                 Hostname  Address         Tag                   Zone  Capacity
-563e1ac825ee3323   linuxbox  127.0.0.1:3901  NO ROLE ASSIGNED
+563e1ac825ee3323…  linuxbox  127.0.0.1:3901  NO ROLE ASSIGNED
 ```
 ## Creating a cluster layout
@ -189,12 +150,12 @@ For our test deployment, we are using only one node. The way in which we configu
 it does not matter, you can simply write:
 ```bash
-garage layout assign -z dc1 -c 1G <node_id>
+garage layout assign -z dc1 -c 1 <node_id>
 ```
 where `<node_id>` corresponds to the identifier of the node shown by `garage status` (first column).
 You can enter simply a prefix of that identifier.
-For instance here you could write just `garage layout assign -z dc1 -c 1G 563e`.
+For instance here you could write just `garage layout assign -z dc1 -c 1 563e`.
 The layout then has to be applied to the cluster, using:
@ -245,7 +206,7 @@ one key can access multiple buckets, multiple keys can access one bucket.
 Create an API key using the following command:
 ```
-garage key create nextcloud-app-key
+garage key new --name nextcloud-app-key
 ```
 The output should look as follows:
@ -284,7 +245,7 @@ garage bucket info nextcloud-bucket
 ```
-## Uploading and downloading from Garage
+## Uploading and downlading from Garage
 To download and upload files on garage, we can use a third-party tool named `awscli`.
@ -305,14 +266,12 @@ named `~/.awsrc` with this content:
 export AWS_ACCESS_KEY_ID=xxxx      # put your Key ID here
 export AWS_SECRET_ACCESS_KEY=xxxx  # put your Secret key here
 export AWS_DEFAULT_REGION='garage'
-export AWS_ENDPOINT_URL='http://localhost:3900'
+export AWS_ENDPOINT='http://localhost:3900'
 function aws { command aws --endpoint-url $AWS_ENDPOINT $@ ; }
 aws --version
 ```
 Note you need to have at least `awscli` `>=1.29.0` or `>=2.13.0`, otherwise you
 need to specify `--endpoint-url` explicitly on each `awscli` invocation.
 Now, each time you want to use `awscli` on this target, run:
 ```bash
@ -331,13 +290,13 @@ sourcing the right file.*
 aws s3 ls
 # list objects of a bucket
-aws s3 ls s3://nextcloud-bucket
+aws s3 ls s3://my_files
 # copy from your filesystem to garage
-aws s3 cp /proc/cpuinfo s3://nextcloud-bucket/cpuinfo.txt
+aws s3 cp /proc/cpuinfo s3://my_files/cpuinfo.txt
 # copy from garage to your filesystem
-aws s3 cp s3://nextcloud-bucket/cpuinfo.txt /tmp/cpuinfo.txt
+aws s3 cp s3/my_files/cpuinfo.txt /tmp/cpuinfo.txt
 ```
 Note that you can use `awscli` for more advanced operations like
--- a/doc/book/reference-manual/_index.md
+++ b/doc/book/reference-manual/_index.md
@ -1,6 +1,6 @@
 +++
 title = "Reference Manual"
-weight = 60
+weight = 5
 sort_by = "weight"
 template = "documentation.html"
 +++
--- a/doc/book/reference-manual/admin-api.md
+++ b/doc/book/reference-manual/admin-api.md
@ -1,6 +1,6 @@
 +++
 title = "Administration API"
-weight = 40
+weight = 60
 +++
 The Garage administration API is accessible through a dedicated server whose
@ -8,21 +8,18 @@ listen address is specified in the `[admin]` section of the configuration
 file (see [configuration file
 reference](@/documentation/reference-manual/configuration.md))
-**WARNING.** At this point, there is no commitment to the stability of the APIs described in this document.
+**WARNING.** At this point, there is no comittement to stability of the APIs described in this document.
-We will bump the version numbers prefixed to each API endpoint each time the syntax
+We will bump the version numbers prefixed to each API endpoint at each time the syntax
 or semantics change, meaning that code that relies on these endpoint will break
 when changes are introduced.
-Versions:
+The Garage administration API was introduced in version 0.7.2, this document
- - Before Garage 0.7.2 - no admin API
+does not apply to older versions of Garage.
 - Garage 0.7.2 - admin APIv0
 - Garage 0.9.0 - admin APIv1, deprecate admin APIv0
 ## Access control
-The admin API uses two different tokens for access control, that are specified in the config file's `[admin]` section:
+The admin API uses two different tokens for acces control, that are specified in the config file's `[admin]` section:
 - `metrics_token`: the token for accessing the Metrics endpoint (if this token
  is not set in the config file, the Metrics endpoint can be accessed without
@ -42,101 +39,15 @@ Authorization: Bearer <token>
 ## Administration API endpoints
-### Metrics `GET /metrics`
+### Metrics-related endpoints
 #### Metrics `GET /metrics`
 Returns internal Garage metrics in Prometheus format.
 The metrics are directly documented when returned by the API.
 **Example:**
 ```
 $ curl -i http://localhost:3903/metrics
 HTTP/1.1 200 OK
 content-type: text/plain; version=0.0.4
 content-length: 12145
 date: Tue, 08 Aug 2023 07:25:05 GMT
 # HELP api_admin_error_counter Number of API calls to the various Admin API endpoints that resulted in errors
 # TYPE api_admin_error_counter counter
 api_admin_error_counter{api_endpoint="CheckWebsiteEnabled",status_code="400"} 1
 api_admin_error_counter{api_endpoint="CheckWebsiteEnabled",status_code="404"} 3
 # HELP api_admin_request_counter Number of API calls to the various Admin API endpoints
 # TYPE api_admin_request_counter counter
 api_admin_request_counter{api_endpoint="CheckWebsiteEnabled"} 7
 api_admin_request_counter{api_endpoint="Health"} 3
 # HELP api_admin_request_duration Duration of API calls to the various Admin API endpoints
 ...
 ```
 ### Health `GET /health`
 Returns `200 OK` if enough nodes are up to have a quorum (ie. serve requests),
 otherwise returns `503 Service Unavailable`.
 **Example:**
 ```
 $ curl -i http://localhost:3903/health
 HTTP/1.1 200 OK
 content-type: text/plain
 content-length: 102
 date: Tue, 08 Aug 2023 07:22:38 GMT
 Garage is fully operational
 Consult the full health check API endpoint at /v0/health for more details
 ```
 ### On-demand TLS `GET /check`
 To prevent abuse for on-demand TLS, Caddy developers have specified an endpoint that can be queried by the reverse proxy
 to know if a given domain is allowed to get a certificate. Garage implements these endpoints to tell if a given domain is handled by Garage or is garbage.
 Garage responds with the following logic:
 - If the domain matches the pattern `<bucket-name>.<s3_api.root_domain>`, returns 200 OK
 - If the domain matches the pattern `<bucket-name>.<s3_web.root_domain>` and website is configured for `<bucket>`, returns 200 OK
 - If the domain matches the pattern `<bucket-name>` and website is configured for `<bucket>`, returns 200 OK
 - Otherwise, returns 404 Not Found, 400 Bad Request or 5xx requests.
 *Note 1: because in the path-style URL mode, there is only one domain that is not known by Garage, hence it is not supported by this API endpoint.
 You must manually declare the domain in your reverse-proxy. Idem for K2V.*
 *Note 2: buckets in a user's namespace are not supported yet by this endpoint. This is a limitation of this endpoint currently.*
 **Example:** Suppose a Garage instance is configured with `s3_api.root_domain = .s3.garage.localhost` and `s3_web.root_domain = .web.garage.localhost`.
 With a private `media` bucket (name in the global namespace, website is disabled), the endpoint will feature the following behavior:
 ```
 $ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=media.s3.garage.localhost
 200
 $ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=media
 400
 $ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=media.web.garage.localhost
 400
 ```
 With a public `example.com` bucket (name in the global namespace, website is activated), the endpoint will feature the following behavior:
 ```
 $ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=example.com.s3.garage.localhost
 200
 $ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=example.com
 200
 $ curl -so /dev/null -w "%{http_code}" http://localhost:3903/check?domain=example.com.web.garage.localhost
 200
 ```
 **References:**
 - [Using On-Demand TLS](https://caddyserver.com/docs/automatic-https#using-on-demand-tls)
 - [Add option for a backend check to approve use of on-demand TLS](https://github.com/caddyserver/caddy/pull/1939)
 - [Serving tens of thousands of domains over HTTPS with Caddy](https://caddy.community/t/serving-tens-of-thousands-of-domains-over-https-with-caddy/11179)
 ### Cluster operations
-These endpoints have a dedicated OpenAPI spec.
+These endpoints are defined on a dedicated [Redocly page](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.html). You can also download its [OpenAPI specification](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.yml).
 - APIv1 - [HTML spec](https://garagehq.deuxfleurs.fr/api/garage-admin-v1.html) - [OpenAPI YAML](https://garagehq.deuxfleurs.fr/api/garage-admin-v1.yml)
 - APIv0 (deprecated) - [HTML spec](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.html) - [OpenAPI YAML](https://garagehq.deuxfleurs.fr/api/garage-admin-v0.yml)
 Requesting the API from the command line can be as simple as running:
--- a/doc/book/reference-manual/configuration.md
+++ b/doc/book/reference-manual/configuration.md
@ -3,61 +3,42 @@ title = "Configuration file format"
 weight = 20
 +++
 ## Full example
 Here is an example `garage.toml` configuration file that illustrates all of the possible options:
 ```toml
 replication_factor = 3
 consistency_mode = "consistent"
 metadata_dir = "/var/lib/garage/meta"
 data_dir = "/var/lib/garage/data"
 metadata_fsync = true
 data_fsync = false
 disable_scrub = false
 metadata_auto_snapshot_interval = "6h"
 db_engine = "lmdb"
-block_size = "1M"
+block_size = 1048576
 block_ram_buffer_max = "256MiB"
-lmdb_map_size = "1T"
+sled_cache_capacity = 134217728
 sled_flush_every_ms = 2000
 replication_mode = "3"
 compression_level = 1
 rpc_secret = "4425f5c26c5e11581d3223904324dcb5b5d5dfb14e5e7f35e38c595424f5f1e6"
 rpc_bind_addr = "[::]:3901"
 rpc_bind_outgoing = false
 rpc_public_addr = "[fc00:1::1]:3901"
 # or set rpc_public_adr_subnet to filter down autodiscovery to a subnet:
 # rpc_public_addr_subnet = "2001:0db8:f00:b00:/64"
 allow_world_readable_secrets = false
 bootstrap_peers = [
    "563e1ac825ee3323aa441e72c26d1030d6d4414aeb3dd25287c531e7fc2bc95d@[fc00:1::1]:3901",
-    "86f0f26ae4afbd59aaf9cfb059eefac844951efd5b8caeec0d53f4ed6c85f332@[fc00:1::2]:3901",
+    "86f0f26ae4afbd59aaf9cfb059eefac844951efd5b8caeec0d53f4ed6c85f332[fc00:1::2]:3901",
    "681456ab91350f92242e80a531a3ec9392cb7c974f72640112f90a600d7921a4@[fc00:B::1]:3901",
    "212fd62eeaca72c122b45a7f4fa0f55e012aa5e24ac384a72a3016413fa724ff@[fc00:F::1]:3901",
 ]
 [consul_discovery]
 api = "catalog"
 consul_http_addr = "http://127.0.0.1:8500"
 service_name = "garage-daemon"
 ca_cert = "/etc/consul/consul-ca.crt"
 client_cert = "/etc/consul/consul-client.crt"
 client_key = "/etc/consul/consul-key.crt"
 # for `agent` API mode, unset client_cert and client_key, and optionally enable `token`
 # token = "abcdef-01234-56789"
 tls_skip_verify = false
 tags = [ "dns-enabled" ]
 meta = { dns-acl = "allow trusted" }
 [kubernetes_discovery]
 namespace = "garage"
@ -76,8 +57,8 @@ root_domain = ".web.garage"
 [admin]
 api_bind_addr = "0.0.0.0:3903"
-metrics_token = "BCAdFjoa9G0KJR0WXnHHm7fs1ZAbfpI8iIZ+Z/a2NgI="
+metrics_token = "cacce0b2de4bc2d9f5b5fdff551e01ac1496055aed248202d415398987e35f81"
-admin_token = "UkLeGWEvHnXBqnueR3ISEMWpOnm40jH2tM2HnnL/0F4="
+admin_token = "ae8cb40ea7368bbdbb6430af11cca7da833d3458a5f52086f4e805a570fb5c2a"
 trace_sink = "http://localhost:4317"
 ```
@ -85,187 +66,7 @@ The following gives details about each available configuration option.
 ## Available configuration options
-### Index
+### `metadata_dir`
 [Environment variables](#env_variables).
 Top-level configuration options:
 [`allow_world_readable_secrets`](#allow_world_readable_secrets),
 [`block_ram_buffer_max`](#block_ram_buffer_max),
 [`block_size`](#block_size),
 [`bootstrap_peers`](#bootstrap_peers),
 [`compression_level`](#compression_level),
 [`data_dir`](#data_dir),
 [`data_fsync`](#data_fsync),
 [`db_engine`](#db_engine),
 [`disable_scrub`](#disable_scrub),
 [`lmdb_map_size`](#lmdb_map_size),
 [`metadata_auto_snapshot_interval`](#metadata_auto_snapshot_interval),
 [`metadata_dir`](#metadata_dir),
 [`metadata_fsync`](#metadata_fsync),
 [`replication_factor`](#replication_factor),
 [`consistency_mode`](#consistency_mode),
 [`rpc_bind_addr`](#rpc_bind_addr),
 [`rpc_bind_outgoing`](#rpc_bind_outgoing),
 [`rpc_public_addr`](#rpc_public_addr),
 [`rpc_public_addr_subnet`](#rpc_public_addr_subnet)
 [`rpc_secret`/`rpc_secret_file`](#rpc_secret).
 The `[consul_discovery]` section:
 [`api`](#consul_api),
 [`ca_cert`](#consul_ca_cert),
 [`client_cert`](#consul_client_cert_and_key),
 [`client_key`](#consul_client_cert_and_key),
 [`consul_http_addr`](#consul_http_addr),
 [`meta`](#consul_tags_and_meta),
 [`service_name`](#consul_service_name),
 [`tags`](#consul_tags_and_meta),
 [`tls_skip_verify`](#consul_tls_skip_verify),
 [`token`](#consul_token).
 The `[kubernetes_discovery]` section:
 [`namespace`](#kube_namespace),
 [`service_name`](#kube_service_name),
 [`skip_crd`](#kube_skip_crd).
 The `[s3_api]` section:
 [`api_bind_addr`](#s3_api_bind_addr),
 [`root_domain`](#s3_root_domain),
 [`s3_region`](#s3_region).
 The `[s3_web]` section:
 [`bind_addr`](#web_bind_addr),
 [`root_domain`](#web_root_domain).
 The `[admin]` section:
 [`api_bind_addr`](#admin_api_bind_addr),
 [`metrics_token`/`metrics_token_file`](#admin_metrics_token),
 [`admin_token`/`admin_token_file`](#admin_token),
 [`trace_sink`](#admin_trace_sink),
 ### Environment variables {#env_variables}
 The following configuration parameter must be specified as an environment
 variable, it does not exist in the configuration file:
 - `GARAGE_LOG_TO_SYSLOG` (since v0.9.4): set this to `1` or `true` to make the
  Garage daemon send its logs to `syslog` (using the libc `syslog` function)
  instead of printing to stderr.
 The following environment variables can be used to override the corresponding
 values in the configuration file:
 - [`GARAGE_ALLOW_WORLD_READABLE_SECRETS`](#allow_world_readable_secrets)
 - [`GARAGE_RPC_SECRET` and `GARAGE_RPC_SECRET_FILE`](#rpc_secret)
 - [`GARAGE_ADMIN_TOKEN` and `GARAGE_ADMIN_TOKEN_FILE`](#admin_token)
 - [`GARAGE_METRICS_TOKEN` and `GARAGE_METRICS_TOKEN`](#admin_metrics_token)
 ### Top-level configuration options
 #### `replication_factor` {#replication_factor}
 The replication factor can be any positive integer smaller or equal the node count in your cluster.
 The chosen replication factor has a big impact on the cluster's failure tolerancy and performance characteristics.
 - `1`: data stored on Garage is stored on a single node. There is no
  redundancy, and data will be unavailable as soon as one node fails or its
  network is disconnected.  Do not use this for anything else than test
  deployments.
 - `2`: data stored on Garage will be stored on two different nodes, if possible
  in different zones. Garage tolerates one node failure, or several nodes
  failing but all in a single zone (in a deployment with at least two zones),
  before losing data. Data remains available in read-only mode when one node is
  down, but write operations will fail.
 - `3`: data stored on Garage will be stored on three different nodes, if
  possible each in a different zones.  Garage tolerates two node failure, or
  several node failures but in no more than two zones (in a deployment with at
  least three zones), before losing data. As long as only a single node fails,
  or node failures are only in a single zone, reading and writing data to
  Garage can continue normally.
 - `5`, `7`, ...: When setting the replication factor above 3, it is most useful to
  choose an uneven value, since for every two copies added, one more node can fail
  before losing the ability to write and read to the cluster.
 Note that in modes `2` and `3`,
 if at least the same number of zones are available, an arbitrary number of failures in
 any given zone is tolerated as copies of data will be spread over several zones.
 **Make sure `replication_factor` is the same in the configuration files of all nodes.
 Never run a Garage cluster where that is not the case.**
 It is technically possible to change the replication factor although it's a
 dangerous operation that is not officially supported.  This requires you to
 delete the existing cluster layout and create a new layout from scratch,
 meaning that a full rebalancing of your cluster's data will be needed.  To do
 it, shut down your cluster entirely, delete the `custer_layout` files in the
 meta directories of all your nodes, update all your configuration files with
 the new `replication_factor` parameter, restart your cluster, and then create a
 new layout with all the nodes you want to keep.  Rebalancing data will take
 some time, and data might temporarily appear unavailable to your users.
 It is recommended to shut down public access to the cluster while rebalancing
 is in progress.  In theory, no data should be lost as rebalancing is a
 routine operation for Garage, although we cannot guarantee you that everything
 will go right in such an extreme scenario.
 #### `consistency_mode` {#consistency_mode}
 The consistency mode setting determines the read and write behaviour of your cluster.
  - `consistent`: The default setting. This is what the paragraph above describes.
    The read and write quorum will be determined so that read-after-write consistency
    is guaranteed.
  - `degraded`: Lowers the read
    quorum to `1`, to allow you to read data from your cluster when several
    nodes (or nodes in several zones) are unavailable.  In this mode, Garage
    does not provide read-after-write consistency anymore.
    The write quorum stays the same as in the `consistent` mode, ensuring that
    data successfully written to Garage is stored on multiple nodes (depending
    the replication factor).
  - `dangerous`: This mode lowers both the read
    and write quorums to `1`, to allow you to both read and write to your
    cluster when several nodes (or nodes in several zones) are unavailable.  It
    is the least consistent mode of operation proposed by Garage, and also one
    that should probably never be used.
 Changing the `consistency_mode` between modes while leaving the `replication_factor` untouched
 (e.g. setting your node's `consistency_mode` to `degraded` when it was previously unset, or from
 `dangerous` to `consistent`), can be done easily by just changing the `consistency_mode`
 parameter in your config files and restarting all your Garage nodes.
 The consistency mode can be used together with various replication factors, to achieve
 a wide range of read and write characteristics. Some examples:
  - Replication factor `2`, consistency mode `degraded`: While this mode
    technically exists, its properties are the same as with consistency mode `consistent`,
    since the read quorum with replication factor `2`, consistency mode `consistent` is already 1.
  - Replication factor `2`, consistency mode `dangerous`: written objects are written to
    the second replica asynchronously. This means that Garage will return `200
    OK` to a PutObject request before the second copy is fully written (or even
    before it even starts being written).  This means that data can more easily
    be lost if the node crashes before a second copy can be completed.  This
    also means that written objects might not be visible immediately in read
    operations.  In other words, this configuration severely breaks the consistency and
    durability guarantees of standard Garage cluster operation.  Benefits of
    this configuration: you can still write to your cluster when one node is
    unavailable.
 The quorums associated with each replication mode are described below:
 | `consistency_mode` | `replication_factor` | Write quorum | Read quorum | Read-after-write consistency? |
 | ------------------ | -------------------- | ------------ | ----------- | ----------------------------- |
 | `consistent`       | 1                    | 1            | 1           | yes                           |
 | `consistent`       | 2                    | 2            | 1           | yes                           |
 | `dangerous`        | 2                    | 1            | 1           | NO                            |
 | `consistent`       | 3                    | 2            | 2           | yes                           |
 | `degraded`         | 3                    | 2            | 1           | NO                            |
 | `dangerous`        | 3                    | 1            | 1           | NO                            |
 #### `metadata_dir` {#metadata_dir}
 The directory in which Garage will store its metadata. This contains the node identifier,
 the network configuration and the peer list, the list of buckets and keys as well
@ -273,165 +74,59 @@ as the index of all objects, object version and object blocks.
 Store this folder on a fast SSD drive if possible to maximize Garage's performance.
-#### `data_dir` {#data_dir}
+### `data_dir`
 The directory in which Garage will store the data blocks of objects.
 This folder can be placed on an HDD. The space available for `data_dir`
 should be counted to determine a node's capacity
 when [adding it to the cluster layout](@/documentation/cookbook/real-world.md).
-Since `v0.9.0`, Garage supports multiple data directories with the following syntax:
+### `db_engine` (since `v0.8.0`)
-```toml
+By default, Garage uses the Sled embedded database library
-data_dir = [
+to store its metadata on-disk. Since `v0.8.0`, Garage can use alternative storage backends as follows:
    { path = "/path/to/old_data", read_only = true },
    { path = "/path/to/new_hdd1", capacity = "2T" },
    { path = "/path/to/new_hdd2", capacity = "4T" },
 ]
 ```
 See [the dedicated documentation page](@/documentation/operations/multi-hdd.md)
 on how to operate Garage in such a setup.
 #### `db_engine` (since `v0.8.0`) {#db_engine}
 Since `v0.8.0`, Garage can use alternative storage backends as follows:
 | DB engine | `db_engine` value | Database path |
 | --------- | ----------------- | ------------- |
-| [LMDB](https://www.symas.com/lmdb) (since `v0.8.0`, default since `v0.9.0`) | `"lmdb"` | `<metadata_dir>/db.lmdb/` |
+| [Sled](https://sled.rs) | `"sled"` | `<metadata_dir>/db/` |
-| [Sqlite](https://sqlite.org) (since `v0.8.0`) | `"sqlite"` | `<metadata_dir>/db.sqlite` |
+| [LMDB](https://www.lmdb.tech) | `"lmdb"` | `<metadata_dir>/db.lmdb/` |
-| [Sled](https://sled.rs) (old default, removed since `v1.0`) | `"sled"` | `<metadata_dir>/db/` |
+| [Sqlite](https://sqlite.org) | `"sqlite"` | `<metadata_dir>/db.sqlite` |
 Sled was supported until Garage v0.9.x, and was removed in Garage v1.0.
 You can still use an older binary of Garage (e.g. v0.9.4) to migrate
 old Sled metadata databases to another engine.
 Performance characteristics of the different DB engines are as follows:
- LMDB: the recommended database engine for high-performance distributed clusters.
+- Sled: the default database engine, which tends to produce
-LMDB works very well, but is known to have the following limitations:
+  large data files and also has performance issues, especially when the metadata folder
  is on a traditionnal HDD and not on SSD.
 - LMDB: the recommended alternative on 64-bit systems,
  much more space-efficiant and slightly faster. Note that the data format of LMDB is not portable
  between architectures, so for instance the Garage database of an x86-64
  node cannot be moved to an ARM64 node. Also note that, while LMDB can technically be used on 32-bit systems,
  this will limit your node to very small database sizes due to how LMDB works; it is therefore not recommended.
 - Sqlite: Garage supports Sqlite as a storage backend for metadata,
  however it may have issues and is also very slow in its current implementation,
  so it is not recommended to be used for now.
-  - The data format of LMDB is not portable between architectures, so for
+It is possible to convert Garage's metadata directory from one format to another with a small utility named `convert_db`,
-    instance the Garage database of an x86-64 node cannot be moved to an ARM64
+which can be downloaded at the following locations:
-    node.
+[for amd64](https://garagehq.deuxfleurs.fr/_releases/convert_db/amd64/convert_db),
-
+[for i386](https://garagehq.deuxfleurs.fr/_releases/convert_db/i386/convert_db),
-  - While LMDB can technically be used on 32-bit systems, this will limit your
+[for arm64](https://garagehq.deuxfleurs.fr/_releases/convert_db/arm64/convert_db),
-    node to very small database sizes due to how LMDB works; it is therefore
+[for arm](https://garagehq.deuxfleurs.fr/_releases/convert_db/arm/convert_db).
-    not recommended.
+The `convert_db` utility is used as folows:
  - Several users have reported corrupted LMDB database files after an unclean
    shutdown (e.g. a power outage). This situation can generally be recovered
    from if your cluster is geo-replicated (by rebuilding your metadata db from
    other nodes), or if you have saved regular snapshots at the filesystem
    level.
  - Keys in LMDB are limited to 511 bytes. This limit translates to limits on
    object keys in S3 and sort keys in K2V that are limted to 479 bytes.
 - Sqlite: Garage supports Sqlite as an alternative storage backend for
  metadata, which does not have the issues listed above for LMDB.
  On versions 0.8.x and earlier, Sqlite should be avoided due to abysmal
  performance, which was fixed with the addition of `metadata_fsync`.
  Sqlite is still probably slower than LMDB due to the way we use it,
  so it is not the best choice for high-performance storage clusters,
  but it should work fine in many cases.
 It is possible to convert Garage's metadata directory from one format to another
 using the `garage convert-db` command, which should be used as follows:
 ```
-garage convert-db -a <input db engine> -i <input db path> \
+convert-db -a <input db engine> -i <input db path> \
  		   -b <output db engine> -o <output db path>
 ```
-Make sure to specify the full database path as presented in the table above
+Make sure to specify the full database path as presented in the table above,
-(third colummn), and not just the path to the metadata directory.
+and not just the path to the metadata directory.
-#### `metadata_fsync` {#metadata_fsync}
+### `block_size`
 Whether to enable synchronous mode for the database engine or not.
 This is disabled (`false`) by default.
 This reduces the risk of metadata corruption in case of power failures,
 at the cost of a significant drop in write performance,
 as Garage will have to pause to sync data to disk much more often
 (several times for API calls such as PutObject).
 Using this option reduces the risk of simultaneous metadata corruption on several
 cluster nodes, which could lead to data loss.
 If multi-site replication is used, this option is most likely not necessary, as
 it is extremely unlikely that two nodes in different locations will have a
 power failure at the exact same time.
 (Metadata corruption on a single node is not an issue, the corrupted data file
 can always be deleted and reconstructed from the other nodes in the cluster.)
 Here is how this option impacts the different database engines:
 | Database | `metadata_fsync = false` (default) | `metadata_fsync = true`       |
 |----------|------------------------------------|-------------------------------|
 | Sqlite   | `PRAGMA synchronous = OFF`         | `PRAGMA synchronous = NORMAL` |
 | LMDB     | `MDB_NOMETASYNC` + `MDB_NOSYNC`    | `MDB_NOMETASYNC`              |
 Note that the Sqlite database is always ran in `WAL` mode (`PRAGMA journal_mode = WAL`).
 #### `data_fsync` {#data_fsync}
 Whether to `fsync` data blocks and their containing directory after they are
 saved to disk.
 This is disabled (`false`) by default.
 This might reduce the risk that a data block is lost in rare
 situations such as simultaneous node losing power,
 at the cost of a moderate drop in write performance.
 Similarly to `metatada_fsync`, this is likely not necessary
 if geographical replication is used.
 #### `metadata_auto_snapshot_interval` (since Garage v0.9.4) {#metadata_auto_snapshot_interval}
 If this value is set, Garage will automatically take a snapshot of the metadata
 DB file at a regular interval and save it in the metadata directory.
 This parameter can take any duration string that can be parsed by
 the [`parse_duration`](https://docs.rs/parse_duration/latest/parse_duration/#syntax) crate.
 Snapshots can allow to recover from situations where the metadata DB file is
 corrupted, for instance after an unclean shutdown.  See [this
 page](@/documentation/operations/recovering.md#corrupted_meta) for details.
 Garage keeps only the two most recent snapshots of the metadata DB and deletes
 older ones automatically.
 Note that taking a metadata snapshot is a relatively intensive operation as the
 entire data file is copied. A snapshot being taken might have performance
 impacts on the Garage node while it is running. If the cluster is under heavy
 write load when a snapshot operation is running, this might also cause the
 database file to grow in size significantly as pages cannot be recycled easily.
 For this reason, it might be better to use filesystem-level snapshots instead
 if possible.
 #### `disable_scrub` {#disable_scrub}
 By default, Garage runs a scrub of the data directory approximately once per
 month, with a random delay to avoid all nodes running at the same time.  When
 it scrubs the data directory, Garage will read all of the data files stored on
 disk to check their integrity, and will rebuild any data files that it finds
 corrupted, using the remaining valid copies stored on other nodes.
 See [this page](@/documentation/operations/durability-repairs.md#scrub) for details.
 Set the `disable_scrub` configuration value to `true` if you don't need Garage
 to scrub the data directory, for instance if you are already scrubbing at the
 filesystem level. Note that in this case, if you find a corrupted data file,
 you should delete it from the data directory and then call `garage repair
 blocks` on the node to ensure that it re-obtains a copy from another node on
 the network.
 #### `block_size` {#block_size}
 Garage splits stored objects in consecutive chunks of size `block_size`
-(except the last one which might be smaller). The default size is 1MiB and
+(except the last one which might be smaller). The default size is 1MB and
-should work in most cases. We recommend increasing it to e.g. 10MiB if
+should work in most cases. We recommend increasing it to e.g. 10MB if
 you are using Garage to store large files and have fast network connections
 between all nodes (e.g. 1gbps).
@ -442,46 +137,105 @@ files will remain available. This however means that chunks from existing files
 will not be deduplicated with chunks from newly uploaded files, meaning you
 might use more storage space that is optimally possible.
-#### `block_ram_buffer_max` (since v0.9.4) {#block_ram_buffer_max}
+### `sled_cache_capacity`
-A limit on the total size of data blocks kept in RAM by S3 API nodes awaiting
+This parameter can be used to tune the capacity of the cache used by
-to be sent to storage nodes asynchronously.
+[sled](https://sled.rs), the database Garage uses internally to store metadata.
 Tune this to fit the RAM you wish to make available to your Garage instance.
 This value has a conservative default (128MB) so that Garage doesn't use too much
 RAM by default, but feel free to increase this for higher performance.
-Explanation: since Garage wants to tolerate node failures, it uses quorum
+### `sled_flush_every_ms`
 writes to send data blocks to storage nodes: try to write the block to three
 nodes, and return ok as soon as two writes complete. So even if all three nodes
 are online, the third write always completes asynchronously.  In general, there
 are not many writes to a cluster, and the third asynchronous write can
 terminate early enough so as to not cause unbounded RAM growth.  However, if
 the S3 API node is continuously receiving large quantities of data and the
 third node is never able to catch up, many data blocks will be kept buffered in
 RAM as they are awaiting transfer to the third node.
-The `block_ram_buffer_max` sets a limit to the size of buffers that can be kept
+This parameters can be used to tune the flushing interval of sled.
-in RAM in this process.  When the limit is reached, backpressure is applied
+Increase this if sled is thrashing your SSD, at the risk of losing more data in case
-back to the S3 client.
+of a power outage (though this should not matter much as data is replicated on other
 nodes). The default value, 2000ms, should be appropriate for most use cases.
-Note that this only counts buffers that have arrived to a certain stage of
+### `replication_mode`
 processing (received from the client + encrypted and/or compressed as
 necessary) and are ready to send to the storage nodes. Many other buffers will
 not be counted and this is not a hard limit on RAM consumption.  In particular,
 if many clients send requests simultaneously with large objects, the RAM
 consumption will always grow linearly with the number of concurrent requests,
 as each request will use a few buffers of size `block_size` for receiving and
 intermediate processing before even trying to send the data to the storage
 node.
-The default value is 256MiB.
+Garage supports the following replication modes:
-#### `lmdb_map_size` {#lmdb_map_size}
+- `none` or `1`: data stored on Garage is stored on a single node. There is no
  redundancy, and data will be unavailable as soon as one node fails or its
  network is disconnected.  Do not use this for anything else than test
  deployments.
-This parameters can be used to set the map size used by LMDB,
+- `2`: data stored on Garage will be stored on two different nodes, if possible
-which is the size of the virtual memory region used for mapping the database file.
+  in different zones. Garage tolerates one node failure, or several nodes
-The value of this parameter is the maximum size the metadata database can take.
+  failing but all in a single zone (in a deployment with at least two zones),
-This value is not bound by the physical RAM size of the machine running Garage.
+  before losing data. Data remains available in read-only mode when one node is
-If not specified, it defaults to 1GiB on 32-bit machines and 1TiB on 64-bit machines.
+  down, but write operations will fail.
-#### `compression_level` {#compression_level}
+  - `2-dangerous`: a variant of mode `2`, where written objects are written to
    the second replica asynchronously. This means that Garage will return `200
    OK` to a PutObject request before the second copy is fully written (or even
    before it even starts being written).  This means that data can more easily
    be lost if the node crashes before a second copy can be completed.  This
    also means that written objects might not be visible immediately in read
    operations.  In other words, this mode severely breaks the consistency and
    durability guarantees of standard Garage cluster operation.  Benefits of
    this mode: you can still write to your cluster when one node is
    unavailable.
 - `3`: data stored on Garage will be stored on three different nodes, if
  possible each in a different zones.  Garage tolerates two node failure, or
  several node failures but in no more than two zones (in a deployment with at
  least three zones), before losing data. As long as only a single node fails,
  or node failures are only in a single zone, reading and writing data to
  Garage can continue normally.
  - `3-degraded`: a variant of replication mode `3`, that lowers the read
    quorum to `1`, to allow you to read data from your cluster when several
    nodes (or nodes in several zones) are unavailable.  In this mode, Garage
    does not provide read-after-write consistency anymore.  The write quorum is
    still 2, ensuring that data successfully written to Garage is stored on at
    least two nodes.
  - `3-dangerous`: a variant of replication mode `3` that lowers both the read
    and write quorums to `1`, to allow you to both read and write to your
    cluster when several nodes (or nodes in several zones) are unavailable.  It
    is the least consistent mode of operation proposed by Garage, and also one
    that should probably never be used.
 Note that in modes `2` and `3`,
 if at least the same number of zones are available, an arbitrary number of failures in 
 any given zone is tolerated as copies of data will be spread over several zones.
 **Make sure `replication_mode` is the same in the configuration files of all nodes.
 Never run a Garage cluster where that is not the case.**
 The quorums associated with each replication mode are described below:
 | `replication_mode` | Number of replicas | Write quorum | Read quorum | Read-after-write consistency? |
 | ------------------ | ------------------ | ------------ | ----------- | ----------------------------- |
 | `none` or `1`      | 1                  | 1            | 1           | yes                           |
 | `2`                | 2                  | 2            | 1           | yes                           |
 | `2-dangerous`      | 2                  | 1            | 1           | NO                            |
 | `3`                | 3                  | 2            | 2           | yes                           |
 | `3-degraded`       | 3                  | 2            | 1           | NO                            |
 | `3-dangerous`      | 3                  | 1            | 1           | NO                            |
 Changing the `replication_mode` between modes with the same number of replicas
 (e.g. from `3` to `3-degraded`, or from `2-dangerous` to `2`), can be done easily by
 just changing the `replication_mode` parameter in your config files and restarting all your
 Garage nodes.
 It is also technically possible to change the replication mode to a mode with a
 different numbers of replicas, although it's a dangerous operation that is not
 officially supported.  This requires you to delete the existing cluster layout
 and create a new layout from scratch, meaning that a full rebalancing of your
 cluster's data will be needed.  To do it, shut down your cluster entirely,
 delete the `custer_layout` files in the meta directories of all your nodes,
 update all your configuration files with the new `replication_mode` parameter,
 restart your cluster, and then create a new layout with all the nodes you want
 to keep.  Rebalancing data will take some time, and data might temporarily
 appear unavailable to your users.  It is recommended to shut down public access
 to the cluster while rebalancing is in progress.  In theory, no data should be
 lost as rebalancing is a routine operation for Garage, although we cannot
 guarantee you that everything will go right in such an extreme scenario.
 ### `compression_level`
 Zstd compression level to use for storing blocks.
@ -505,22 +259,15 @@ Compression is done synchronously, setting a value too high will add latency to
 This value can be different between nodes, compression is done by the node which receive the
 API call.
-#### `rpc_secret`, `rpc_secret_file` or `GARAGE_RPC_SECRET`, `GARAGE_RPC_SECRET_FILE` (env) {#rpc_secret}
+### `rpc_secret`
-Garage uses a secret key, called an RPC secret, that is shared between all
+Garage uses a secret key that is shared between all nodes of the cluster
-nodes of the cluster in order to identify these nodes and allow them to
+in order to identify these nodes and allow them to communicate together.
-communicate together. The RPC secret is a 32-byte hex-encoded random string,
+This key should be specified here in the form of a 32-byte hex-encoded
-which can be generated with a command such as `openssl rand -hex 32`.
+random string. Such a string can be generated with a command
 such as `openssl rand -hex 32`.
-The RPC secret should be specified in the `rpc_secret` configuration variable.
+### `rpc_bind_addr`
 Since Garage `v0.8.2`, the RPC secret can also be stored in a file whose path is
 given in the configuration variable `rpc_secret_file`, or specified as an
 environment variable `GARAGE_RPC_SECRET`.
 Since Garage `v0.8.5` and `v0.9.1`, you can also specify the path of a file
 storing the secret as the `GARAGE_RPC_SECRET_FILE` environment variable.
 #### `rpc_bind_addr` {#rpc_bind_addr}
 The address and port on which to bind for inter-cluster communcations
 (reffered to as RPC for remote procedure calls).
@ -529,33 +276,14 @@ the node, even in the case of a NAT: the NAT should be configured to forward the
 port number to the same internal port nubmer. This means that if you have several nodes running
 behind a NAT, they should each use a different RPC port number.
-#### `rpc_bind_outgoing`(since v0.9.2) {#rpc_bind_outgoing}
+### `rpc_public_addr`
 If enabled, pre-bind all sockets for outgoing connections to the same IP address
 used for listening (the IP address specified in `rpc_bind_addr`) before
 trying to connect to remote nodes.
 This can be necessary if a node has multiple IP addresses,
 but only one is allowed or able to reach the other nodes,
 for instance due to firewall rules or specific routing configuration.
 Disabled by default.
 #### `rpc_public_addr` {#rpc_public_addr}
 The address and port that other nodes need to use to contact this node for
 RPC calls.  **This parameter is optional but recommended.** In case you have
 a NAT that binds the RPC port to a port that is different on your public IP,
 this field might help making it work.
-#### `rpc_public_addr_subnet` {#rpc_public_addr_subnet}
+### `bootstrap_peers`
 In case `rpc_public_addr` is not set, but autodiscovery is used, this allows
 filtering the list of automatically discovered IPs to a specific subnet.
 For example, if nodes should pick *their* IP inside a specific subnet, but you
 don't want to explicitly write the IP down (as it's dynamic, or you want to
 share configs across nodes), you can use this option.
 #### `bootstrap_peers` {#bootstrap_peers}
 A list of peer identifiers on which to contact other Garage peers of this cluster.
 These peer identifiers have the following syntax:
@ -571,118 +299,75 @@ be obtained by running `garage node id` and then included directly in the
 key will be returned by `garage node id` and you will have to add the IP
 yourself.
 ### `allow_world_readable_secrets` or `GARAGE_ALLOW_WORLD_READABLE_SECRETS` (env) {#allow_world_readable_secrets}
-Garage checks the permissions of your secret files to make sure they're not
+## The `[consul_discovery]` section
 world-readable. In some cases, the check might fail and consider your files as
 world-readable even if they're not, for instance when using Posix ACLs.
 Setting `allow_world_readable_secrets` to `true` bypass this
 permission verification.
 Alternatively, you can set the `GARAGE_ALLOW_WORLD_READABLE_SECRETS`
 environment variable to `true` to bypass the permissions check.
 ### The `[consul_discovery]` section
 Garage supports discovering other nodes of the cluster using Consul.  For this
 to work correctly, nodes need to know their IP address by which they can be
 reached by other nodes of the cluster, which should be set in `rpc_public_addr`.
-#### `consul_http_addr` {#consul_http_addr}
+### `consul_http_addr` and `service_name`
 The `consul_http_addr` parameter should be set to the full HTTP(S) address of the Consul server.
-#### `api` {#consul_api}
+### `service_name`
 Two APIs for service registration are supported: `catalog`  and `agent`. `catalog`, the default, will register a service using
 the `/v1/catalog` endpoints, enabling mTLS if `client_cert` and `client_key` are provided. The `agent` API uses the
 `v1/agent` endpoints instead, where an optional `token` may be provided.
 #### `service_name` {#consul_service_name}
 `service_name` should be set to the service name under which Garage's
 RPC ports are announced.
-#### `client_cert`, `client_key` {#consul_client_cert_and_key}
+### `client_cert`, `client_key`
 TLS client certificate and client key to use when communicating with Consul over TLS. Both are mandatory when doing so.
 Only available when `api = "catalog"`.
-#### `ca_cert` {#consul_ca_cert}
+### `ca_cert`
 TLS CA certificate to use when communicating with Consul over TLS.
-#### `tls_skip_verify` {#consul_tls_skip_verify}
+### `tls_skip_verify`
 Skip server hostname verification in TLS handshake.
 `ca_cert` is ignored when this is set.
 #### `token` {#consul_token}
-Uses the provided token for communication with Consul. Only available when `api = "agent"`.
+## The `[kubernetes_discovery]` section
 The policy assigned to this token should at least have these rules:
 ```hcl
 // the `service_name` specified above
 service "garage" {
  policy = "write"
 }
 service_prefix "" {
  policy = "read"
 }
 node_prefix "" {
  policy = "read"
 }
 ```
 #### `tags` and `meta` {#consul_tags_and_meta}
 Additional list of tags and map of service meta to add during service registration.
 ### The `[kubernetes_discovery]` section
 Garage supports discovering other nodes of the cluster using kubernetes custom
 resources. For this to work, a `[kubernetes_discovery]` section must be present
 with at least the `namespace` and `service_name` parameters.
-#### `namespace` {#kube_namespace}
+### `namespace`
 `namespace` sets the namespace in which the custom resources are
 configured.
-#### `service_name` {#kube_service_name}
+### `service_name`
 `service_name` is added as a label to the advertised resources to
 filter them, to allow for multiple deployments in a single namespace.
-#### `skip_crd` {#kube_skip_crd}
+### `skip_crd`
 `skip_crd` can be set to true to disable the automatic creation and
 patching of the `garagenodes.deuxfleurs.fr` CRD. You will need to create the CRD
 manually.
-### The `[s3_api]` section
+## The `[s3_api]` section
-#### `api_bind_addr` {#s3_api_bind_addr}
+### `api_bind_addr`
 The IP and port on which to bind for accepting S3 API calls.
 This endpoint does not suport TLS: a reverse proxy should be used to provide it.
-Alternatively, since `v0.8.5`, a path can be used to create a unix socket with 0222 mode.
+### `s3_region`
 #### `s3_region` {#s3_region}
 Garage will accept S3 API calls that are targetted to the S3 region defined here.
 API calls targetted to other regions will fail with a AuthorizationHeaderMalformed error
 message that redirects the client to the correct region.
-#### `root_domain` {#s3_root_domain}
+### `root_domain` {#root_domain}
-The optional suffix to access bucket using vhost-style in addition to path-style request.
+The optionnal suffix to access bucket using vhost-style in addition to path-style request.
 Note path-style requests are always enabled, whether or not vhost-style is configured.
 Configuring vhost-style S3 required a wildcard DNS entry, and possibly a wildcard TLS certificate,
 but might be required by softwares not supporting path-style requests.
@ -692,67 +377,54 @@ using the hostname `my-bucket.s3.garage.eu`.
-### The `[s3_web]` section
+## The `[s3_web]` section
 Garage allows to publish content of buckets as websites. This section configures the
 behaviour of this module.
-#### `bind_addr` {#web_bind_addr}
+### `bind_addr`
 The IP and port on which to bind for accepting HTTP requests to buckets configured
 for website access.
 This endpoint does not suport TLS: a reverse proxy should be used to provide it.
-Alternatively, since `v0.8.5`, a path can be used to create a unix socket with 0222 mode.
+### `root_domain`
-#### `root_domain` {#web_root_domain}
+The optionnal suffix appended to bucket names for the corresponding HTTP Host.
 The optional suffix appended to bucket names for the corresponding HTTP Host.
 For instance, if `root_domain` is `web.garage.eu`, a bucket called `deuxfleurs.fr`
 will be accessible either with hostname `deuxfleurs.fr.web.garage.eu`
 or with hostname `deuxfleurs.fr`.
-### The `[admin]` section
+## The `[admin]` section
 Garage has a few administration capabilities, in particular to allow remote monitoring. These features are detailed below.
-#### `api_bind_addr` {#admin_api_bind_addr}
+### `api_bind_addr`
 If specified, Garage will bind an HTTP server to this port and address, on
 which it will listen to requests for administration features.
 See [administration API reference](@/documentation/reference-manual/admin-api.md) to learn more about these features.
-Alternatively, since `v0.8.5`, a path can be used to create a unix socket. Note that for security reasons,
+### `metrics_token` (since version 0.7.2)
 the socket will have 0220 mode. Make sure to set user and group permissions accordingly.
-#### `metrics_token`, `metrics_token_file` or `GARAGE_METRICS_TOKEN`, `GARAGE_METRICS_TOKEN_FILE` (env) {#admin_metrics_token}
+The token for accessing the Metrics endpoint. If this token is not set in
 the config file, the Metrics endpoint can be accessed without access
 control.
-The token for accessing the Metrics endpoint. If this token is not set, the
+You can use any random string for this value. We recommend generating a random token with `openssl rand -hex 32`.
 Metrics endpoint can be accessed without access control.
-You can use any random string for this value. We recommend generating a random token with `openssl rand -base64 32`.
+### `admin_token` (since version 0.7.2)
 `metrics_token` was introduced in Garage `v0.7.2`.
 `metrics_token_file` and the `GARAGE_METRICS_TOKEN` environment variable are supported since Garage `v0.8.2`.
 `GARAGE_METRICS_TOKEN_FILE` is supported since `v0.8.5` / `v0.9.1`.
 #### `admin_token`, `admin_token_file` or `GARAGE_ADMIN_TOKEN`, `GARAGE_ADMIN_TOKEN_FILE` (env) {#admin_token}
 The token for accessing all of the other administration endpoints.  If this
-token is not set, access to these endpoints is disabled entirely.
+token is not set in the config file, access to these endpoints is disabled
 entirely.
-You can use any random string for this value. We recommend generating a random token with `openssl rand -base64 32`.
+You can use any random string for this value. We recommend generating a random token with `openssl rand -hex 32`.
-`admin_token` was introduced in Garage `v0.7.2`.
+### `trace_sink`
 `admin_token_file` and the `GARAGE_ADMIN_TOKEN` environment variable are supported since Garage `v0.8.2`.
-`GARAGE_ADMIN_TOKEN_FILE` is supported since `v0.8.5` / `v0.9.1`.
+Optionnally, the address of an Opentelemetry collector.  If specified,
-
+Garage will send traces in the Opentelemetry format to this endpoint. These
 #### `trace_sink` {#admin_trace_sink}
 Optionally, the address of an OpenTelemetry collector.  If specified,
 Garage will send traces in the OpenTelemetry format to this endpoint. These
 trace allow to inspect Garage's operation when it handles S3 API requests.
--- a/doc/book/reference-manual/features.md
+++ b/doc/book/reference-manual/features.md
@ -35,22 +35,7 @@ This makes setting up and administering storage clusters, we hope, as easy as it
 A Garage cluster can very easily evolve over time, as storage nodes are added or removed.
 Garage will automatically rebalance data between nodes as needed to ensure the desired number of copies.
-Read about cluster layout management [here](@/documentation/operations/layout.md).
+Read about cluster layout management [here](@/documentation/reference-manual/layout.md).
 ### Several replication modes
 Garage supports a variety of replication modes, with configurable replica count,
 and with various levels of consistency, in order to adapt to a variety of usage scenarios.
 Read our reference page on [supported replication modes](@/documentation/reference-manual/configuration.md#replication_factor)
 to select the replication mode best suited to your use case (hint: in most cases, `replication_factor = 3` is what you want).
 ### Compression and deduplication
 All data stored in Garage is deduplicated, and optionnally compressed using
 Zstd.  Objects uploaded to Garage are chunked in blocks of constant sizes (see
 [`block_size`](@/documentation/reference-manual/configuration.md#block_size)),
 and the hashes of individual blocks are used to dispatch them to storage nodes
 and to deduplicate them.
 ### No RAFT slowing you down
@ -63,6 +48,13 @@ As a consequence, requests can be handled much faster, even in cases where laten
 between cluster nodes is important (see our [benchmarks](@/documentation/design/benchmarks/index.md) for data on this).
 This is particularly usefull when nodes are far from one another and talk to one other through standard Internet connections.
 ### Several replication modes
 Garage supports a variety of replication modes, with 1 copy, 2 copies or 3 copies of your data,
 and with various levels of consistency, in order to adapt to a variety of usage scenarios.
 Read our reference page on [supported replication modes](@/documentation/reference-manual/configuration.md#replication-mode)
 to select the replication mode best suited to your use case (hint: in most cases, `replication_mode = "3"` is what you want).
 ### Web server for static websites
 A storage bucket can easily be configured to be served directly by Garage as a static web site.
--- a/doc/book/reference-manual/k2v.md
+++ b/doc/book/reference-manual/k2v.md
@ -1,9 +1,9 @@
 +++
 title = "K2V"
-weight = 100
+weight = 70
 +++
-Starting with version 0.7.2, Garage introduces an optional feature, K2V,
+Starting with version 0.7.2, Garage introduces an optionnal feature, K2V,
 which is an alternative storage API designed to help efficiently store
 many small values in buckets (in opposition to S3 which is more designed
 to store large blobs).
@ -16,7 +16,7 @@ the `k2v` feature flag enabled can be obtained from our download page under
 with `-k2v` (example: `v0.7.2-k2v`).
 The specification of the K2V API can be found
-[here](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/branch/main/doc/drafts/k2v-spec.md).
+[here](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/branch/k2v/doc/drafts/k2v-spec.md).
 This document also includes a high-level overview of K2V's design.
 The K2V API uses AWSv4 signatures for authentification, same as the S3 API.
--- a/doc/book/reference-manual/layout.md
+++ b/doc/book/reference-manual/layout.md
@ -0,0 +1,77 @@
 +++
 title = "Cluster layout management"
 weight = 50
 +++
 The cluster layout in Garage is a table that assigns to each node a role in
 the cluster. The role of a node in Garage can either be a storage node with
 a certain capacity, or a gateway node that does not store data and is only
 used as an API entry point for faster cluster access.
 An introduction to building cluster layouts can be found in the [production deployment](@/documentation/cookbook/real-world.md) page.
 ## How cluster layouts work in Garage
 In Garage, a cluster layout is composed of the following components:
 - a table of roles assigned to nodes
 - a version number
 Garage nodes will always use the cluster layout with the highest version number.
 Garage nodes also maintain and synchronize between them a set of proposed role
 changes that haven't yet been applied. These changes will be applied (or
 canceled) in the next version of the layout
 The following commands insert modifications to the set of proposed role changes
 for the next layout version (but they do not create the new layout immediately):
 ```bash
 garage layout assign [...]
 garage layout remove [...]
 ```
 The following command can be used to inspect the layout that is currently set in the cluster
 and the changes proposed for the next layout version, if any:
 ```bash
 garage layout show
 ```
 The following commands create a new layout with the specified version number,
 that either takes into account the proposed changes or cancels them:
 ```bash
 garage layout apply --version <new_version_number>
 garage layout revert --version <new_version_number>
 ```
 The version number of the new layout to create must be 1 + the version number
 of the previous layout that existed in the cluster.  The `apply` and `revert`
 commands will fail otherwise.
 ## Warnings about Garage cluster layout management
 **Warning: never make several calls to `garage layout apply` or `garage layout
 revert` with the same value of the `--version` flag. Doing so can lead to the
 creation of several different layouts with the same version number, in which
 case your Garage cluster will become inconsistent until fixed.** If a call to
 `garage layout apply` or `garage layout revert` has failed and `garage layout
 show` indicates that a new layout with the given version number has not been
 set in the cluster, then it is fine to call the command again with the same
 version number.
 If you are using the `garage` CLI by typing individual commands in your
 shell, you shouldn't have much issues as long as you run commands one after
 the other and take care of checking the output of `garage layout show`
 before applying any changes.
 If you are using the `garage` CLI to script layout changes, follow the following recommendations:
 - Make all of your `garage` CLI calls to the same RPC host. Do not use the
  `garage` CLI to connect to individual nodes to send them each a piece of the
  layout changes you are making, as the changes propagate asynchronously
  between nodes and might not all be taken into account at the time when the
  new layout is applied.
 - **Only call `garage layout apply` once**, and call it **strictly after** all
  of the `layout assign` and `layout remove` commands have returned.
--- a/doc/book/reference-manual/monitoring.md
+++ b/doc/book/reference-manual/monitoring.md
@ -1,402 +0,0 @@
 +++
 title = "Monitoring"
 weight = 60
 +++
 For information on setting up monitoring, see our [dedicated page](@/documentation/cookbook/monitoring.md) in the Cookbook section.
 ## List of exported metrics
 ### Garage system metrics
 #### `garage_build_info` (counter)
 Exposes the Garage version number running on a node.
 ```
 garage_build_info{version="1.0"} 1
 ```
 #### `garage_replication_factor` (counter)
 Exposes the Garage replication factor configured on the node
 ```
 garage_replication_factor 3
 ```
 #### `garage_local_disk_avail` and `garage_local_disk_total` (gauge)
 Reports the available and total disk space on each node, for data and metadata separately.
 ```
 garage_local_disk_avail{volume="data"} 540341960704
 garage_local_disk_avail{volume="metadata"} 540341960704
 garage_local_disk_total{volume="data"} 763063566336
 garage_local_disk_total{volume="metadata"} 763063566336
 ```
 ### Cluster health status metrics
 #### `cluster_healthy` (gauge)
 Whether all storage nodes are connected (0 or 1)
 ```
 cluster_healthy 0
 ```
 #### `cluster_available` (gauge)
 Whether all requests can be served, even if some storage nodes are disconnected
 ```
 cluster_available 1
 ```
 #### `cluster_connected_nodes` (gauge)
 Number of nodes currently connected
 ```
 cluster_connected_nodes 3
 ```
 #### `cluster_known_nodes` (gauge)
 Number of nodes already seen once in the cluster
 ```
 cluster_known_nodes 3
 ```
 #### `cluster_layout_node_connected` (gauge)
 Connection status for individual nodes of the cluster layout
 ```
 cluster_layout_node_connected{id="62b218d848e86a64",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 1
 cluster_layout_node_connected{id="a11c7cf18af29737",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 0
 cluster_layout_node_connected{id="a235ac7695e0c54d",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 1
 cluster_layout_node_connected{id="b10c110e4e854e5a",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 1
 ```
 #### `cluster_layout_node_disconnected_time` (gauge)
 Time (in seconds) since last connection to individual nodes of the cluster layout
 ```
 cluster_layout_node_disconnected_time{id="62b218d848e86a64",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 0
 cluster_layout_node_disconnected_time{id="a235ac7695e0c54d",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 0
 cluster_layout_node_disconnected_time{id="b10c110e4e854e5a",role_capacity="1000000000",role_gateway="0",role_zone="dc1"} 0
 ```
 #### `cluster_storage_nodes` (gauge)
 Number of storage nodes declared in the current layout
 ```
 cluster_storage_nodes 4
 ```
 #### `cluster_storage_nodes_ok` (gauge)
 Number of storage nodes currently connected
 ```
 cluster_storage_nodes_ok 3
 ```
 #### `cluster_partitions` (gauge)
 Number of partitions in the layout (this is always 256)
 ```
 cluster_partitions 256
 ```
 #### `cluster_partitions_all_ok` (gauge)
 Number of partitions for which all storage nodes are connected
 ```
 cluster_partitions_all_ok 64
 ```
 #### `cluster_partitions_quorum` (gauge)
 Number of partitions for which we have a quorum of connected nodes and all requests can be served
 ```
 cluster_partitions_quorum 256
 ```
 ### Metrics of the API endpoints
 #### `api_admin_request_counter` (counter)
 Counts the number of requests to a given endpoint of the administration API. Example:
 ```
 api_admin_request_counter{api_endpoint="Metrics"} 127041
 ```
 #### `api_admin_request_duration` (histogram)
 Evaluates the duration of API calls to the various administration API endpoint. Example:
 ```
 api_admin_request_duration_bucket{api_endpoint="Metrics",le="0.5"} 127041
 api_admin_request_duration_sum{api_endpoint="Metrics"} 605.250344830999
 api_admin_request_duration_count{api_endpoint="Metrics"} 127041
 ```
 #### `api_s3_request_counter` (counter)
 Counts the number of requests to a given endpoint of the S3 API. Example:
 ```
 api_s3_request_counter{api_endpoint="CreateMultipartUpload"} 1
 ```
 #### `api_s3_error_counter` (counter)
 Counts the number of requests to a given endpoint of the S3 API that returned an error. Example:
 ```
 api_s3_error_counter{api_endpoint="GetObject",status_code="404"} 39
 ```
 #### `api_s3_request_duration` (histogram)
 Evaluates the duration of API calls to the various S3 API endpoints. Example:
 ```
 api_s3_request_duration_bucket{api_endpoint="CreateMultipartUpload",le="0.5"} 1
 api_s3_request_duration_sum{api_endpoint="CreateMultipartUpload"} 0.046340762
 api_s3_request_duration_count{api_endpoint="CreateMultipartUpload"} 1
 ```
 #### `api_k2v_request_counter` (counter), `api_k2v_error_counter` (counter), `api_k2v_error_duration` (histogram)
 Same as for S3, for the K2V API.
 ### Metrics of the Web endpoint
 #### `web_request_counter` (counter)
 Number of requests to the web endpoint
 ```
 web_request_counter{method="GET"} 80
 ```
 #### `web_request_duration` (histogram)
 Duration of requests to the web endpoint
 ```
 web_request_duration_bucket{method="GET",le="0.5"} 80
 web_request_duration_sum{method="GET"} 1.0528433229999998
 web_request_duration_count{method="GET"} 80
 ```
 #### `web_error_counter` (counter)
 Number of requests to the web endpoint resulting in errors
 ```
 web_error_counter{method="GET",status_code="404 Not Found"} 64
 ```
 ### Metrics of the data block manager
 #### `block_bytes_read`, `block_bytes_written` (counter)
 Number of bytes read/written to/from disk in the data storage directory.
 ```
 block_bytes_read 120586322022
 block_bytes_written 3386618077
 ```
 #### `block_ram_buffer_free_kb` (gauge)
 Kibibytes available for buffering blocks that have to be sent to remote nodes.
 When clients send too much data to this node and a storage node is not receiving
 data fast enough due to slower network conditions, this will decrease down to
 zero and backpressure will be applied.
 ```
 block_ram_buffer_free_kb 219829
 ```
 #### `block_compression_level` (counter)
 Exposes the block compression level configured for the Garage node.
 ```
 block_compression_level 3
 ```
 #### `block_read_duration`, `block_write_duration` (histograms)
 Evaluates the duration of the reading/writing of individual data blocks in the data storage directory.
 ```
 block_read_duration_bucket{le="0.5"} 169229
 block_read_duration_sum 2761.6902550310056
 block_read_duration_count 169240
 block_write_duration_bucket{le="0.5"} 3559
 block_write_duration_sum 195.59170078500006
 block_write_duration_count 3571
 ```
 #### `block_delete_counter` (counter)
 Counts the number of data blocks that have been deleted from storage.
 ```
 block_delete_counter 122
 ```
 #### `block_resync_counter` (counter), `block_resync_duration` (histogram)
 Counts the number of resync operations the node has executed, and evaluates their duration.
 ```
 block_resync_counter 308897
 block_resync_duration_bucket{le="0.5"} 308892
 block_resync_duration_sum 139.64204196100016
 block_resync_duration_count 308897
 ```
 #### `block_resync_queue_length` (gauge)
 The number of block hashes currently queued for a resync.
 This is normal to be nonzero for long periods of time.
 ```
 block_resync_queue_length 0
 ```
 #### `block_resync_errored_blocks` (gauge)
 The number of block hashes that we were unable to resync last time we tried.
 **THIS SHOULD BE ZERO, OR FALL BACK TO ZERO RAPIDLY, IN A HEALTHY CLUSTER.**
 Persistent nonzero values indicate that some data is likely to be lost.
 ```
 block_resync_errored_blocks 0
 ```
 ### Metrics related to RPCs (remote procedure calls) between nodes
 #### `rpc_netapp_request_counter` (counter)
 Number of RPC requests emitted
 ```
 rpc_request_counter{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>"} 176
 ```
 #### `rpc_netapp_error_counter` (counter)
 Number of communication errors (errors in the Netapp library, generally due to disconnected nodes)
 ```
 rpc_netapp_error_counter{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>"} 354
 ```
 #### `rpc_timeout_counter` (counter)
 Number of RPC timeouts, should be close to zero in a healthy cluster.
 ```
 rpc_timeout_counter{from="<this node>",rpc_endpoint="garage_rpc/membership.rs/SystemRpc",to="<remote node>"} 1
 ```
 #### `rpc_duration` (histogram)
 The duration of internal RPC calls between Garage nodes.
 ```
 rpc_duration_bucket{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>",le="0.5"} 166
 rpc_duration_sum{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>"} 35.172253716
 rpc_duration_count{from="<this node>",rpc_endpoint="garage_block/manager.rs/Rpc",to="<remote node>"} 174
 ```
 ### Metrics of the metadata table manager
 #### `table_gc_todo_queue_length` (gauge)
 Table garbage collector TODO queue length
 ```
 table_gc_todo_queue_length{table_name="block_ref"} 0
 ```
 #### `table_get_request_counter` (counter), `table_get_request_duration` (histogram)
 Number of get/get_range requests internally made on each table, and their duration.
 ```
 table_get_request_counter{table_name="bucket_alias"} 315
 table_get_request_duration_bucket{table_name="bucket_alias",le="0.5"} 315
 table_get_request_duration_sum{table_name="bucket_alias"} 0.048509778000000024
 table_get_request_duration_count{table_name="bucket_alias"} 315
 ```
 #### `table_put_request_counter` (counter), `table_put_request_duration` (histogram)
 Number of insert/insert_many requests internally made on this table, and their duration
 ```
 table_put_request_counter{table_name="block_ref"} 677
 table_put_request_duration_bucket{table_name="block_ref",le="0.5"} 677
 table_put_request_duration_sum{table_name="block_ref"} 61.617528636
 table_put_request_duration_count{table_name="block_ref"} 677
 ```
 #### `table_internal_delete_counter` (counter)
 Number of value deletions in the tree (due to GC or repartitioning)
 ```
 table_internal_delete_counter{table_name="block_ref"} 2296
 ```
 #### `table_internal_update_counter` (counter)
 Number of value updates where the value actually changes (includes creation of new key and update of existing key)
 ```
 table_internal_update_counter{table_name="block_ref"} 5996
 ```
 #### `table_merkle_updater_todo_queue_length` (gauge)
 Merkle tree updater TODO queue length (should fall to zero rapidly)
 ```
 table_merkle_updater_todo_queue_length{table_name="block_ref"} 0
 ```
 #### `table_sync_items_received`, `table_sync_items_sent` (counters)
 Number of data items sent to/recieved from other nodes during resync procedures
 ```
 table_sync_items_received{from="<remote node>",table_name="bucket_v2"} 3
 table_sync_items_sent{table_name="block_ref",to="<remote node>"} 2
 ```
--- a/doc/book/reference-manual/s3-compatibility.md
+++ b/doc/book/reference-manual/s3-compatibility.md
@ -1,6 +1,6 @@
 +++
 title = "S3 Compatibility status"
-weight = 70
+weight = 40
 +++
 ## DISCLAIMER
@ -33,7 +33,6 @@ Feel free to open a PR to suggest fixes this table. Minio is missing because the
 | [URL path-style](https://docs.aws.amazon.com/AmazonS3/latest/userguide/VirtualHosting.html#path-style-access) (eg. `host.tld/bucket/key`) |  ✅ Implemented | ✅ |  ✅ | ❓| ✅ |
 | [URL vhost-style](https://docs.aws.amazon.com/AmazonS3/latest/userguide/VirtualHosting.html#virtual-hosted-style-access) URL (eg. `bucket.host.tld/key`) |  ✅ Implemented | ❌| ✅| ✅ | ✅ |
 | [Presigned URLs](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ShareObjectPreSignedURL.html) |  ✅ Implemented | ❌|  ✅ | ✅ |  ✅(❓) |
 | [SSE-C encryption](https://docs.aws.amazon.com/AmazonS3/latest/userguide/ServerSideEncryptionCustomerKeys.html) |  ✅ Implemented | ❓ |  ✅ | ❌ |  ✅ |
 *Note:* OpenIO does not says if it supports presigned URLs. Because it is part
 of signature v4 and they claim they support it without additional precisions,
@ -77,13 +76,16 @@ but these endpoints are documented in [Red Hat Ceph Storage - Chapter 2. Ceph Ob
 | Endpoint                     | Garage                           | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) |
 |------------------------------|----------------------------------|-----------------|---------------|---------|-----|
 | [AbortMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_AbortMultipartUpload.html)         | ✅ Implemented                      |  ✅ | ✅ | ✅ | ✅ |
-| [CompleteMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CompleteMultipartUpload.html)   | ✅ Implemented  | ✅ | ✅ | ✅ | ✅ |
+| [CompleteMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CompleteMultipartUpload.html)   | ✅ Implemented (see details below)                      | ✅ | ✅ | ✅ | ✅ |
 | [CreateMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_CreateMultipartUpload.html)        | ✅ Implemented                      | ✅| ✅ | ✅ | ✅ |
 | [ListMultipartUpload](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListMultipartUpload.html)          | ✅ Implemented                      | ✅ | ✅ | ✅ | ✅ |
 | [ListParts](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListParts.html)                    | ✅ Implemented                      | ✅ | ✅ | ✅ | ✅ |
-| [UploadPart](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPart.html)                  | ✅ Implemented             | ✅ | ✅| ✅ | ✅ |
+| [UploadPart](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPart.html)                  | ✅ Implemented (see details below)                      | ✅ | ✅| ✅ | ✅ |
 | [UploadPartCopy](https://docs.aws.amazon.com/AmazonS3/latest/API/API_UploadPartCopy.html)               | ✅ Implemented                      | ✅ | ✅ | ✅ | ✅ |
 Our implementation of Multipart Upload is currently a bit more restrictive than Amazon's one in some edge cases.
 For more information, please refer to our [issue tracker](https://git.deuxfleurs.fr/Deuxfleurs/garage/issues/204).
 ### Website endpoints
 | Endpoint                     | Garage                           | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) |
@ -125,22 +127,15 @@ If you need this feature, please [share your use case in our dedicated issue](ht
 | Endpoint                     | Garage                           | [Openstack Swift](https://docs.openstack.org/swift/latest/s3_compat.html) | [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/) | [Riak CS](https://docs.riak.com/riak/cs/2.1.1/references/apis/storage/s3/index.html) | [OpenIO](https://docs.openio.io/latest/source/arch-design/s3_compliancy.html) |
 |------------------------------|----------------------------------|-----------------|---------------|---------|-----|
-| [DeleteBucketLifecycle](https://docs.aws.amazon.com/AmazonS3/latest/API/API_DeleteBucketLifecycle.html) | ✅ Implemented | ❌| ✅| ❌| ✅|
+| [DeleteBucketLifecycle](https://docs.aws.amazon.com/AmazonS3/latest/API/API_DeleteBucketLifecycle.html) | ❌ Missing | ❌| ✅| ❌| ✅|
-| [GetBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_GetBucketLifecycleConfiguration.html) | ✅ Implemented | ❌| ✅ | ❌| ✅|
+| [GetBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_GetBucketLifecycleConfiguration.html) | ❌ Missing | ❌| ✅ | ❌| ✅|
-| [PutBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_PutBucketLifecycleConfiguration.html) | ⚠ Partially implemented (see below) | ❌| ✅ | ❌| ✅|
+| [PutBucketLifecycleConfiguration](https://docs.aws.amazon.com/AmazonS3/latest/API/API_PutBucketLifecycleConfiguration.html) | ❌ Missing | ❌| ✅ | ❌| ✅|
 | [GetBucketVersioning](https://docs.aws.amazon.com/AmazonS3/latest/API/API_GetBucketVersioning.html)          | ❌ Stub (see below)       | ✅| ✅ | ❌| ✅|
 | [ListObjectVersions](https://docs.aws.amazon.com/AmazonS3/latest/API/API_ListObjectVersions.html) | ❌ Missing | ❌| ✅ | ❌| ✅|
 | [PutBucketVersioning](https://docs.aws.amazon.com/AmazonS3/latest/API/API_PutBucketVersioning.html) | ❌ Missing | ❌| ✅| ❌| ✅|
 **PutBucketLifecycleConfiguration:** The only actions supported are
 `AbortIncompleteMultipartUpload` and `Expiration` (without the
 `ExpiredObjectDeleteMarker` field).  All other operations are dependent on
 either bucket versionning or storage classes which Garage currently does not
 implement. The deprecated `Prefix` member directly in the the `Rule`
 structure/XML tag is not supported, specified prefixes must be inside the
 `Filter` structure/XML tag.
-**GetBucketVersioning:** Stub implementation which always returns "versionning not enabled", since Garage does not yet support bucket versionning.
+**GetBucketVersioning:** Stub implementation (Garage does not yet support versionning so this always returns "versionning not enabled").
 ### Replication endpoints
--- a/doc/book/working-documents/_index.md
+++ b/doc/book/working-documents/_index.md
@ -1,6 +1,6 @@
 +++
 title = "Working Documents"
-weight = 90
+weight = 8
 sort_by = "weight"
 template = "documentation.html"
 +++
--- a/doc/book/working-documents/migration-08.md
+++ b/doc/book/working-documents/migration-08.md
@ -12,15 +12,13 @@ back up all your data before attempting it!**
 Garage v0.8 introduces new data tables that allow the counting of objects in buckets in order to implement bucket quotas.
 A manual migration step is required to first count objects in Garage buckets and populate these tables with accurate data.
 ## Simple migration procedure (takes cluster offline for a while)
 The migration steps are as follows:
 1. Disable API and web access. Garage v0.7 does not support disabling
   these endpoints but you can change the port number or stop your reverse proxy for instance.
 2. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`,
   check the logs and check that all data seems to be synced correctly between
-   nodes. If you have time, do additional checks (`versions`, `block_refs`, etc.)
+   nodes. If you have time, do additional checks (`scrub`, `block_refs`, etc.)
 3. Check that queues are empty: run `garage stats` to query them or inspect metrics in the Grafana dashboard.
 4. Turn off Garage v0.7
 5. **Backup the metadata folder of all your nodes!** For instance, use the following command
@ -34,24 +32,3 @@ The migration steps are as follows:
 10. Your upgraded cluster should be in a working state. Re-enable API and Web
    access and check that everything went well.
 11. Monitor your cluster in the next hours to see if it works well under your production load, report any issue.
 ## Minimal downtime migration procedure
 The migration to Garage v0.8 can be done with almost no downtime,
 by restarting all nodes at once in the new version. The only limitation with this
 method is that bucket sizes and item counts will not be estimated correctly
 until all nodes have had a chance to run their offline migration procedure.
 The migration steps are as follows:
 1. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`,
   check the logs and check that all data seems to be synced correctly between
   nodes. If you have time, do additional checks (`versions`, `block_refs`, etc.)
 2. Turn off each node individually; back up its metadata folder (see above); turn it back on again. This will allow you to take a backup of all nodes without impacting global cluster availability. You can do all nodes of a single zone at once as this does not impact the availability of Garage.
 3. Prepare your binaries and configuration files for Garage v0.8
 4. Shut down all v0.7 nodes simultaneously, and restart them all simultaneously in v0.8. Use your favorite deployment tool (Ansible, Kubernetes, Nomad) to achieve this as fast as possible.
 5. At this point, Garage will indicate invalid values for the size and number of objects in each bucket (most likely, it will indicate zero). To fix this, take each node offline individually to do the offline migration step: `garage offline-repair --yes object_counters`. Again you can do all nodes of a single zone at once.
--- a/doc/book/working-documents/migration-09.md
+++ b/doc/book/working-documents/migration-09.md
@ -1,72 +0,0 @@
 +++
 title = "Migrating from 0.8 to 0.9"
 weight = 12
 +++
 **This guide explains how to migrate to 0.9 if you have an existing 0.8 cluster.
 We don't recommend trying to migrate to 0.9 directly from 0.7 or older.**
 This migration procedure has been tested on several clusters without issues.
 However, it is still a *critical procedure* that might cause issues.
 **Make sure to back up all your data before attempting it!**
 You might also want to read our [general documentation on upgrading Garage](@/documentation/operations/upgrading.md).
 The following are **breaking changes** in Garage v0.9 that require your attention when migrating:
 - LMDB is now the default metadata db engine and Sled is deprecated. If you were using Sled, make sure to specify `db_engine = "sled"` in your configuration file, or take the time to [convert your database](https://garagehq.deuxfleurs.fr/documentation/reference-manual/configuration/#db-engine-since-v0-8-0).
 - Capacity values are now in actual byte units. The translation from the old layout will assign 1 capacity = 1Gb by default, which might be wrong for your cluster. This does not cause any data to be moved around, but you might want to re-assign correct capacity values post-migration.
 - Multipart uploads that were started in Garage v0.8 will not be visible in Garage v0.9 and will have to be restarted from scratch.
 - Changes to the admin API: some `v0/` endpoints have been replaced by `v1/` counterparts with updated/uniformized syntax. All other endpoints have also moved to `v1/` by default, without syntax changes, but are still available under `v0/` for compatibility.
 ## Simple migration procedure (takes cluster offline for a while)
 The migration steps are as follows:
 1. Disable API and web access. You may do this by stopping your reverse proxy or by commenting out
   the `api_bind_addr` values in your `config.toml` file and restarting Garage.
 2. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`,
   check the logs and check that all data seems to be synced correctly between
   nodes. If you have time, do additional checks (`versions`, `block_refs`, etc.)
 3. Check that the block resync queue and Merkle queue are empty:
   run `garage stats -a` to query them or inspect metrics in the Grafana dashboard.
 4. Turn off Garage v0.8
 5. **Backup the metadata folder of all your nodes!** For instance, use the following command
 	if your metadata directory is `/var/lib/garage/meta`: `cd /var/lib/garage ; tar -acf meta-v0.8.tar.zst meta/`
 6. Install Garage v0.9
 7. Update your configuration file if necessary.
 8. Turn on Garage v0.9
 9. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`.
   Wait for a full table sync to run.
 10. Your upgraded cluster should be in a working state. Re-enable API and Web
    access and check that everything went well.
 11. Monitor your cluster in the next hours to see if it works well under your production load, report any issue.
 12. You might want to assign correct capacity values to all your nodes. Doing so might cause data to be moved
    in your cluster, which should also be monitored carefully.
 ## Minimal downtime migration procedure
 The migration to Garage v0.9 can be done with almost no downtime,
 by restarting all nodes at once in the new version.
 The migration steps are as follows:
 1. Do `garage repair --all-nodes --yes tables` and `garage repair --all-nodes --yes blocks`,
   check the logs and check that all data seems to be synced correctly between
   nodes. If you have time, do additional checks (`versions`, `block_refs`, etc.)
 2. Turn off each node individually; back up its metadata folder (see above); turn it back on again.
   This will allow you to take a backup of all nodes without impacting global cluster availability.
   You can do all nodes of a single zone at once as this does not impact the availability of Garage.
 3. Prepare your binaries and configuration files for Garage v0.9
 4. Shut down all v0.8 nodes simultaneously, and restart them all simultaneously in v0.9.
   Use your favorite deployment tool (Ansible, Kubernetes, Nomad) to achieve this as fast as possible.
   Garage v0.9 should be in a working state as soon as it starts.
 5. Proceed with repair and monitoring as described in steps 9-12 above.
--- a/doc/book/working-documents/migration-1.md
+++ b/doc/book/working-documents/migration-1.md
@ -1,77 +0,0 @@
 +++
 title = "Migrating from 0.9 to 1.0"
 weight = 11
 +++
 **This guide explains how to migrate to 1.0 if you have an existing 0.9 cluster.
 We don't recommend trying to migrate to 1.0 directly from 0.8 or older.**
 This migration procedure has been tested on several clusters without issues.
 However, it is still a *critical procedure* that might cause issues.
 **Make sure to back up all your data before attempting it!**
 You might also want to read our [general documentation on upgrading Garage](@/documentation/operations/upgrading.md).
 ## Changes introduced in v1.0
 The following are **breaking changes** in Garage v1.0 that require your attention when migrating:
 - The Sled metadata db engine has been **removed**. If your cluster was still
  using Sled, you will need to **use a Garage v0.9.x binary** to convert the
  database using the `garage convert-db` subcommand. See
  [here](@/documentation/reference-manual/configuration.md#db_engine) for the
  details of the procedure.
 The following syntax changes have been made to the configuration file:
 - The `replication_mode` parameter has been split into two parameters:
  [`replication_factor`](@/documentation/reference-manual/configuration.md#replication_factor)
  and
  [`consistency_mode`](@/documentation/reference-manual/configuration.md#consistency_mode).
  The old syntax using `replication_mode` is still supported for legacy
  reasons and can still be used.
 - The parameters `sled_cache_capacity` and `sled_flush_every_ms` have been removed.
 ## Migration procedure
 The migration to Garage v1.0 can be done with almost no downtime,
 by restarting all nodes at once in the new version.
 The migration steps are as follows:
 1. Do a `garage repair --all-nodes --yes tables`, check the logs and check that
   all data seems to be synced correctly between nodes. If you have time, do
   additional `garage repair` procedures (`blocks`, `versions`, `block_refs`,
   etc.)
 2. Ensure you have a snapshot of your Garage installation that you can restore
   to in case the upgrade goes wrong:
   - If you are running Garage v0.9.4 or later, use the `garage meta snapshot
     --all` to make a backup snapshot of the metadata directories of your nodes
     for backup purposes, and save a copy of the following files in the
     metadata directories of your nodes: `cluster_layout`, `data_layout`,
     `node_key`, `node_key.pub`.
   - If you are running a filesystem such as ZFS or BTRFS that support
     snapshotting, you can create a filesystem-level snapshot to be used as a
     restoration point if needed.
   - In other cases, make a backup using the old procedure: turn off each node
     individually; back up its metadata folder (for instance, use the following
     command if your metadata directory is `/var/lib/garage/meta`: `cd
     /var/lib/garage ; tar -acf meta-v0.9.tar.zst meta/`); turn it back on
     again.  This will allow you to take a backup of all nodes without
     impacting global cluster availability.  You can do all nodes of a single
     zone at once as this does not impact the availability of Garage.
 3. Prepare your updated binaries and configuration files for Garage v1.0
 4. Shut down all v0.9 nodes simultaneously, and restart them all simultaneously
   in v1.0.  Use your favorite deployment tool (Ansible, Kubernetes, Nomad) to
   achieve this as fast as possible.  Garage v1.0 should be in a working state
   as soon as enough nodes have started.
 5. Monitor your cluster in the following hours to see if it works well under
   your production load.
--- a/doc/drafts/admin-api.md
+++ b/doc/drafts/admin-api.md
@ -8,9 +8,9 @@ listen address is specified in the `[admin]` section of the configuration
 file (see [configuration file
 reference](@/documentation/reference-manual/configuration.md))
-**WARNING.** At this point, there is no commitment to the stability of the APIs described in this document.
+**WARNING.** At this point, there is no comittement to stability of the APIs described in this document.
-We will bump the version numbers prefixed to each API endpoint each time the syntax
+We will bump the version numbers prefixed to each API endpoint at each time the syntax
-or semantics change, meaning that code that relies on these endpoints will break
+or semantics change, meaning that code that relies on these endpoint will break
 when changes are introduced.
 The Garage administration API was introduced in version 0.7.2, this document
@ -19,7 +19,7 @@ does not apply to older versions of Garage.
 ## Access control
-The admin API uses two different tokens for access control, that are specified in the config file's `[admin]` section:
+The admin API uses two different tokens for acces control, that are specified in the config file's `[admin]` section:
 - `metrics_token`: the token for accessing the Metrics endpoint (if this token
  is not set in the config file, the Metrics endpoint can be accessed without
@ -52,11 +52,11 @@ Returns an HTTP status 200 if the node is ready to answer user's requests,
 and an HTTP status 503 (Service Unavailable) if there are some partitions
 for which a quorum of nodes is not available.
 A simple textual message is also returned in a body with content-type `text/plain`.
-See `/v1/health` for an API that also returns JSON output.
+See `/v0/health` for an API that also returns JSON output.
 ### Cluster operations
-#### GetClusterStatus `GET /v1/status`
+#### GetClusterStatus `GET /v0/status`
 Returns the cluster's current status in JSON, including:
@ -69,121 +69,87 @@ Example response body:
 ```json
 {
-  "node": "b10c110e4e854e5aa3f4637681befac755154b20059ec163254ddbfae86b09df",
+  "node": "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f",
-  "garageVersion": "v1.0.1",
+  "garage_version": "git:v0.8.0",
-  "garageFeatures": [
+  "knownNodes": {
-    "k2v",
+    "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f": {
-    "lmdb",
+      "addr": "10.0.0.11:3901",
-    "sqlite",
+      "is_up": true,
-    "metrics",
+      "last_seen_secs_ago": 9,
-    "bundled-libs"
+      "hostname": "node1"
-  ],
+    },
-  "rustVersion": "1.68.0",
+    "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff": {
-  "dbEngine": "LMDB (using Heed crate)",
+      "addr": "10.0.0.12:3901",
-  "layoutVersion": 5,
+      "is_up": true,
-  "nodes": [
+      "last_seen_secs_ago": 1,
-    {
+      "hostname": "node2"
-      "id": "62b218d848e86a64f7fe1909735f29a4350547b54c4b204f91246a14eb0a1a8c",
+    },
-      "role": {
+    "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27": {
-        "id": "62b218d848e86a64f7fe1909735f29a4350547b54c4b204f91246a14eb0a1a8c",
+      "addr": "10.0.0.21:3901",
      "is_up": true,
      "last_seen_secs_ago": 7,
      "hostname": "node3"
    },
    "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b": {
      "addr": "10.0.0.22:3901",
      "is_up": true,
      "last_seen_secs_ago": 1,
      "hostname": "node4"
    }
  },
  "layout": {
    "version": 12,
    "roles": {
      "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f": {
        "zone": "dc1",
-        "capacity": 100000000000,
+        "capacity": 4,
-        "tags": []
+        "tags": [
-      },
+          "node1"
      "addr": "10.0.0.3:3901",
      "hostname": "node3",
      "isUp": true,
      "lastSeenSecsAgo": 12,
      "draining": false,
      "dataPartition": {
        "available": 660270088192,
        "total": 873862266880
      },
      "metadataPartition": {
        "available": 660270088192,
        "total": 873862266880
      }
    },
    {
      "id": "a11c7cf18af297379eff8688360155fe68d9061654449ba0ce239252f5a7487f",
      "role": null,
      "addr": "10.0.0.2:3901",
      "hostname": "node2",
      "isUp": true,
      "lastSeenSecsAgo": 11,
      "draining": true,
      "dataPartition": {
        "available": 660270088192,
        "total": 873862266880
      },
      "metadataPartition": {
        "available": 660270088192,
        "total": 873862266880
      }
    },
    {
      "id": "a235ac7695e0c54d7b403943025f57504d500fdcc5c3e42c71c5212faca040a2",
      "role": {
        "id": "a235ac7695e0c54d7b403943025f57504d500fdcc5c3e42c71c5212faca040a2",
        "zone": "dc1",
        "capacity": 100000000000,
        "tags": []
      },
      "addr": "127.0.0.1:3904",
      "hostname": "lindy",
      "isUp": true,
      "lastSeenSecsAgo": 2,
      "draining": false,
      "dataPartition": {
        "available": 660270088192,
        "total": 873862266880
      },
      "metadataPartition": {
        "available": 660270088192,
        "total": 873862266880
      }
    },
    {
      "id": "b10c110e4e854e5aa3f4637681befac755154b20059ec163254ddbfae86b09df",
      "role": {
        "id": "b10c110e4e854e5aa3f4637681befac755154b20059ec163254ddbfae86b09df",
        "zone": "dc1",
        "capacity": 100000000000,
        "tags": []
      },
      "addr": "10.0.0.1:3901",
      "hostname": "node1",
      "isUp": true,
      "lastSeenSecsAgo": 3,
      "draining": false,
      "dataPartition": {
        "available": 660270088192,
        "total": 873862266880
      },
      "metadataPartition": {
        "available": 660270088192,
        "total": 873862266880
      }
    }
        ]
      },
      "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff": {
        "zone": "dc1",
        "capacity": 6,
        "tags": [
          "node2"
        ]
      },
      "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27": {
        "zone": "dc2",
        "capacity": 10,
        "tags": [
          "node3"
        ]
      }
    },
    "stagedRoleChanges": {
      "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b": {
        "zone": "dc2",
        "capacity": 5,
        "tags": [
          "node4"
        ]
      }
    }
  }
 }
 ```
-#### GetClusterHealth `GET /v1/health`
+#### GetClusterHealth `GET /v0/health`
 Returns the cluster's current health in JSON format, with the following variables:
- `status`: one of `healthy`, `degraded` or `unavailable`:
+- `status`: one of `Healthy`, `Degraded` or `Unavailable`:
-  - healthy: Garage node is connected to all storage nodes
+  - Healthy: Garage node is connected to all storage nodes
-  - degraded: Garage node is not connected to all storage nodes, but a quorum of write nodes is available for all partitions
+  - Degraded: Garage node is not connected to all storage nodes, but a quorum of write nodes is available for all partitions
-  - unavailable: a quorum of write nodes is not available for some partitions
+  - Unavailable: a quorum of write nodes is not available for some partitions
- `knownNodes`: the number of nodes this Garage node has had a TCP connection to since the daemon started
+- `known_nodes`: the number of nodes this Garage node has had a TCP connection to since the daemon started
- `connectedNodes`: the nubmer of nodes this Garage node currently has an open connection to
+- `connected_nodes`: the nubmer of nodes this Garage node currently has an open connection to
- `storageNodes`: the number of storage nodes currently registered in the cluster layout
+- `storage_nodes`: the number of storage nodes currently registered in the cluster layout
- `storageNodesOk`: the number of storage nodes to which a connection is currently open
+- `storage_nodes_ok`: the number of storage nodes to which a connection is currently open
 - `partitions`: the total number of partitions of the data (currently always 256)
- `partitionsQuorum`: the number of partitions for which a quorum of write nodes is available
+- `partitions_quorum`: the number of partitions for which a quorum of write nodes is available
- `partitionsAllOk`: the number of partitions for which we are connected to all storage nodes responsible of storing it
+- `partitions_all_ok`: the number of partitions for which we are connected to all storage nodes responsible of storing it
 Contrarily to `GET /health`, this endpoint always returns a 200 OK HTTP response code.
@ -191,18 +157,18 @@ Example response body:
 ```json
 {
-  "status": "degraded",
+    "status": "Degraded",
-  "knownNodes": 3,
+    "known_nodes": 3,
-  "connectedNodes": 3,
+    "connected_nodes": 2,
-  "storageNodes": 4,
+    "storage_nodes": 3,
-  "storageNodesOk": 3,
+    "storage_nodes_ok": 2,
    "partitions": 256,
-  "partitionsQuorum": 256,
+    "partitions_quorum": 256,
-  "partitionsAllOk": 64
+    "partitions_all_ok": 0
 }
 ```
-#### ConnectClusterNodes `POST /v1/connect`
+#### ConnectClusterNodes `POST /v0/connect`
 Instructs this Garage node to connect to other Garage nodes at specified addresses.
@ -232,7 +198,7 @@ Example response:
 ]
 ```
-#### GetClusterLayout `GET /v1/layout`
+#### GetClusterLayout `GET /v0/layout`
 Returns the cluster's current layout in JSON, including:
@ -246,54 +212,42 @@ Example response body:
 ```json
 {
  "version": 12,
-  "roles": [
+  "roles": {
-    {
+    "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f": {
      "id": "ec79480e0ce52ae26fd00c9da684e4fa56658d9c64cdcecb094e936de0bfe71f",
      "zone": "dc1",
-      "capacity": 10737418240,
+      "capacity": 4,
      "tags": [
        "node1"
      ]
    },
-    {
+    "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff": {
      "id": "4a6ae5a1d0d33bf895f5bb4f0a418b7dc94c47c0dd2eb108d1158f3c8f60b0ff",
      "zone": "dc1",
-      "capacity": 10737418240,
+      "capacity": 6,
      "tags": [
        "node2"
      ]
    },
-    {
+    "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27": {
      "id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27",
      "zone": "dc2",
-      "capacity": 10737418240,
+      "capacity": 10,
      "tags": [
        "node3"
      ]
    }
-  ],
+  },
-  "stagedRoleChanges": [
+  "stagedRoleChanges": {
-    {
+    "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b": {
      "id": "e2ee7984ee65b260682086ec70026165903c86e601a4a5a501c1900afe28d84b",
      "remove": false,
      "zone": "dc2",
-      "capacity": 10737418240,
+      "capacity": 5,
      "tags": [
        "node4"
      ]
    }
    {
      "id": "23ffd0cdd375ebff573b20cc5cef38996b51c1a7d6dbcf2c6e619876e507cf27",
      "remove": true,
      "zone": null,
      "capacity": null,
      "tags": null,
  }
  ]
 }
 ```
-#### UpdateClusterLayout `POST /v1/layout`
+#### UpdateClusterLayout `POST /v0/layout`
 Send modifications to the cluster layout. These modifications will
 be included in the staged role changes, visible in subsequent calls
@ -305,9 +259,8 @@ the layout.
 Request body format:
 ```json
 [
 {
-    "id": <node_id>,
+  <node_id>: {
    "capacity": <new_capacity>,
    "zone": <new_zone>,
    "tags": [
@ -315,22 +268,17 @@ Request body format:
      ...
    ]
  },
-  {
+  <node_id_to_remove>: null,
-    "id": <node_id_to_remove>,
+  ...
    "remove": true
 }
 ]
 ```
 Contrary to the CLI that may update only a subset of the fields
 `capacity`, `zone` and `tags`, when calling this API all of these
 values must be specified.
 This returns the new cluster layout with the proposed staged changes,
 as returned by GetClusterLayout.
-
+#### ApplyClusterLayout `POST /v0/layout/apply`
 #### ApplyClusterLayout `POST /v1/layout/apply`
 Applies to the cluster the layout changes currently registered as
 staged layout changes.
@ -347,10 +295,7 @@ Similarly to the CLI, the body must include the version of the new layout
 that will be created, which MUST be 1 + the value of the currently
 existing layout in the cluster.
-This returns the message describing all the calculations done to compute the new
+#### RevertClusterLayout `POST /v0/layout/revert`
 layout, as well as the description of the layout as returned by GetClusterLayout.
 #### RevertClusterLayout `POST /v1/layout/revert`
 Clears all of the staged layout changes.
@ -368,13 +313,10 @@ Similarly to the CLI, the body must include the incremented
 version number, which MUST be 1 + the value of the currently
 existing layout in the cluster.
 This returns the new cluster layout with all changes reverted,
 as returned by GetClusterLayout.
 ### Access key operations
-#### ListKeys `GET /v1/key`
+#### ListKeys `GET /v0/key`
 Returns all API access keys in the cluster.
@ -393,8 +335,34 @@ Example response:
 ]
 ```
-#### GetKeyInfo `GET /v1/key?id=<acces key id>`
+#### CreateKey `POST /v0/key`
-#### GetKeyInfo `GET /v1/key?search=<pattern>`
+
 Creates a new API access key.
 Request body format:
 ```json
 {
    "name": "NameOfMyKey"
 }
 ```
 #### ImportKey `POST /v0/key/import`
 Imports an existing API key.
 Request body format:
 ```json
 {
    "accessKeyId": "GK31c2f218a2e44f485b94239e",
    "secretAccessKey": "b892c0665f0ada8a4755dae98baa3b133590e11dae3bcc1f9d769d67f16c3835",
    "name": "NameOfMyKey"
 }
 ```
 #### GetKeyInfo `GET /v0/key?id=<acces key id>`
 #### GetKeyInfo `GET /v0/key?search=<pattern>`
 Returns information about the requested API access key.
@ -402,9 +370,6 @@ If `id` is set, the key is looked up using its exact identifier (faster).
 If `search` is set, the key is looked up using its name or prefix
 of identifier (slower, all keys are enumerated to do this).
 Optionnally, the query parameter `showSecretKey=true` can be set to reveal the
 associated secret access key.
 Example response:
 ```json
@ -468,40 +433,11 @@ Example response:
 }
 ```
-#### CreateKey `POST /v1/key`
+#### DeleteKey `DELETE /v0/key?id=<acces key id>`
-Creates a new API access key.
+Deletes an API access key.
-Request body format:
+#### UpdateKey `POST /v0/key?id=<acces key id>`
 ```json
 {
    "name": "NameOfMyKey"
 }
 ```
 This returns the key info, including the created secret key,
 in the same format as the result of GetKeyInfo.
 #### ImportKey `POST /v1/key/import`
 Imports an existing API key.
 This will check that the imported key is in the valid format, i.e.
 is a key that could have been generated by Garage.
 Request body format:
 ```json
 {
    "accessKeyId": "GK31c2f218a2e44f485b94239e",
    "secretAccessKey": "b892c0665f0ada8a4755dae98baa3b133590e11dae3bcc1f9d769d67f16c3835",
    "name": "NameOfMyKey"
 }
 ```
 This returns the key info in the same format as the result of GetKeyInfo.
 #### UpdateKey `POST /v1/key?id=<acces key id>`
 Updates information about the specified API access key.
@ -517,20 +453,14 @@ Request body format:
 }
 ```
-All fields (`name`, `allow` and `deny`) are optional.
+All fields (`name`, `allow` and `deny`) are optionnal.
 If they are present, the corresponding modifications are applied to the key, otherwise nothing is changed.
 The possible flags in `allow` and `deny` are: `createBucket`.
 This returns the key info in the same format as the result of GetKeyInfo.
 #### DeleteKey `DELETE /v1/key?id=<acces key id>`
 Deletes an API access key.
 ### Bucket operations
-#### ListBuckets `GET /v1/bucket`
+#### ListBuckets `GET /v0/bucket`
 Returns all storage buckets in the cluster.
@ -572,8 +502,8 @@ Example response:
 ]
 ```
-#### GetBucketInfo `GET /v1/bucket?id=<bucket id>`
+#### GetBucketInfo `GET /v0/bucket?id=<bucket id>`
-#### GetBucketInfo `GET /v1/bucket?globalAlias=<alias>`
+#### GetBucketInfo `GET /v0/bucket?globalAlias=<alias>`
 Returns information about the requested storage bucket.
@ -605,10 +535,7 @@ Example response:
        ],
        "objects": 14827,
        "bytes": 13189855625,
-        "unfinishedUploads": 1,
+        "unfinshedUploads": 0,
        "unfinishedMultipartUploads": 1,
        "unfinishedMultipartUploadParts": 11,
        "unfinishedMultipartUploadBytes": 41943040,
        "quotas": {
            "maxSize": null,
            "maxObjects": null
@ -616,7 +543,7 @@ Example response:
 }
 ```
-#### CreateBucket `POST /v1/bucket`
+#### CreateBucket `POST /v0/bucket`
 Creates a new storage bucket.
@ -656,7 +583,13 @@ or no alias at all.
 Technically, you can also specify both `globalAlias` and `localAlias` and that would create
 two aliases, but I don't see why you would want to do that.
-#### UpdateBucket `PUT /v1/bucket?id=<bucket id>`
+#### DeleteBucket `DELETE /v0/bucket?id=<bucket id>`
 Deletes a storage bucket. A bucket cannot be deleted if it is not empty.
 Warning: this will delete all aliases associated with the bucket!
 #### UpdateBucket `PUT /v0/bucket?id=<bucket id>`
 Updates configuration of the given bucket.
@ -676,7 +609,7 @@ Request body format:
 }
 ```
-All fields (`websiteAccess` and `quotas`) are optional.
+All fields (`websiteAccess` and `quotas`) are optionnal.
 If they are present, the corresponding modifications are applied to the bucket, otherwise nothing is changed.
 In `websiteAccess`: if `enabled` is `true`, `indexDocument` must be specified.
@ -688,16 +621,9 @@ In `quotas`: new values of `maxSize` and `maxObjects` must both be specified, or
 to remove the quotas. An absent value will be considered the same as a `null`. It is not possible
 to change only one of the two quotas.
 #### DeleteBucket `DELETE /v1/bucket?id=<bucket id>`
 Deletes a storage bucket. A bucket cannot be deleted if it is not empty.
 Warning: this will delete all aliases associated with the bucket!
 ### Operations on permissions for keys on buckets
-#### BucketAllowKey `POST /v1/bucket/allow`
+#### BucketAllowKey `POST /v0/bucket/allow`
 Allows a key to do read/write/owner operations on a bucket.
@ -718,7 +644,7 @@ Request body format:
 Flags in `permissions` which have the value `true` will be activated.
 Other flags will remain unchanged.
-#### BucketDenyKey `POST /v1/bucket/deny`
+#### BucketDenyKey `POST /v0/bucket/deny`
 Denies a key from doing read/write/owner operations on a bucket.
@ -742,19 +668,19 @@ Other flags will remain unchanged.
 ### Operations on bucket aliases
-#### GlobalAliasBucket `PUT /v1/bucket/alias/global?id=<bucket id>&alias=<global alias>`
+#### GlobalAliasBucket `PUT /v0/bucket/alias/global?id=<bucket id>&alias=<global alias>`
 Empty body. Creates a global alias for a bucket.
-#### GlobalUnaliasBucket `DELETE /v1/bucket/alias/global?id=<bucket id>&alias=<global alias>`
+#### GlobalUnaliasBucket `DELETE /v0/bucket/alias/global?id=<bucket id>&alias=<global alias>`
 Removes a global alias for a bucket.
-#### LocalAliasBucket `PUT /v1/bucket/alias/local?id=<bucket id>&accessKeyId=<access key ID>&alias=<local alias>`
+#### LocalAliasBucket `PUT /v0/bucket/alias/local?id=<bucket id>&accessKeyId=<access key ID>&alias=<local alias>`
 Empty body. Creates a local alias for a bucket in the namespace of a specific access key.
-#### LocalUnaliasBucket `DELETE /v1/bucket/alias/local?id=<bucket id>&accessKeyId<access key ID>&alias=<local alias>`
+#### LocalUnaliasBucket `DELETE /v0/bucket/alias/local?id=<bucket id>&accessKeyId<access key ID>&alias=<local alias>`
 Removes a local alias for a bucket in the namespace of a specific access key.
--- a/doc/drafts/k2v-spec.md
+++ b/doc/drafts/k2v-spec.md
@ -146,7 +146,7 @@ in a bucket, as the partition key becomes the sort key in the index.
 How indexing works:
 - Each node keeps a local count of how many items it stores for each partition,
-  in a local database tree that is updated atomically when an item is modified.
+  in a local Sled tree that is updated atomically when an item is modified.
 - These local counters are asynchronously stored in the index table which is
  a regular Garage table spread in the network. Counters are stored as LWW values,
  so basically the final table will have the following structure:
@ -706,73 +706,6 @@ HTTP/1.1 200 OK
 ]
 ```
 **PollRange: `POST /<bucket>/<partition key>?poll_range`**, or alternatively<br/>
 **PollRange: `SEARCH /<bucket>/<partition key>?poll_range`**
 Polls a range of items for changes.
 The query body is a JSON object consisting of the following fields:
 | name            | default value | meaning                                                                                |
 |-----------------|---------------|----------------------------------------------------------------------------------------|
 | `prefix`        | `null`        | Restrict items to poll to those whose sort keys start with this prefix                 |
 | `start`         | `null`        | The sort key of the first item to poll                                                 |
 | `end`           | `null`        | The sort key of the last item to poll (excluded)                                       |
 | `timeout`       | 300           | The timeout before 304 NOT MODIFIED is returned if no value in the range is updated    |
 | `seenMarker`    | `null`        | An opaque string returned by a previous PollRange call, that represents items already seen |
 The timeout can be set to any number of seconds, with a maximum of 600 seconds (10 minutes).
 The response is either:
 - A HTTP 304 NOT MODIFIED response with an empty body, if the timeout expired and no changes occurred
 - A HTTP 200 response, indicating that some changes have occurred since the last PollRange call, in which case a JSON object is returned in the body with the following fields:
 | name            | meaning                                                                                |
 |-----------------|----------------------------------------------------------------------------------------|
 | `seenMarker`    | An opaque string that represents items already seen for future PollRange calls         |
 | `items`         | The list of items that have changed since last PollRange call, in the same format as ReadBatch |
 If no seen marker is known by the caller, it can do a PollRange call
 without specifying `seenMarker`. In this case, the PollRange call will
 complete immediately, and return the current content of the range (which
 can be empty) and a seen marker to be used in further PollRange calls. This
 is the only case in which PollRange might return an HTTP 200 with an empty
 set of items.
 A seen marker returned as a response to a PollRange query can be used for further PollRange
 queries on the same range, or for PollRange queries in a subrange of the initial range.
 It may not be used for PollRange queries on ranges larger or outside of the initial range.
 Example query:
 ```json
 SEARCH /my_bucket?poll_range HTTP/1.1
 {
  "prefix": "0391.",
  "start": "0391.000001973107",
  "seenMarker": "opaquestring123",
 }
 ```
 Example response:
 ```json
 HTTP/1.1 200 OK
 Content-Type: application/json
 {
  "seenMarker": "opaquestring456",
  "items": [
    { sk: "0391.000001973221", ct: "opaquetoken123", v: ["b64cryptoblob123", "b64cryptoblob'123"] },
    { sk: "0391.000001974191", ct: "opaquetoken456", v: ["b64cryptoblob456", "b64cryptoblob'456"] },
  ]
 }
 ```
 ## Internals: causality tokens
--- a/doc/logo/garage_hires_crop.png
+++ b/doc/logo/garage_hires_crop.png
--- a/doc/optimal_layout_report/.gitignore
+++ b/doc/optimal_layout_report/.gitignore
@ -1,13 +0,0 @@
 optimal_layout.aux
 optimal_layout.log
 optimal_layout.synctex.gz
 optimal_layout.bbl
 optimal_layout.blg
 geodistrib.aux
 geodistrib.bbl
 geodistrib.blg
 geodistrib.log
 geodistrib.out
 geodistrib.synctex.gz
--- a/doc/optimal_layout_report/figures/flow.pdf
+++ b/doc/optimal_layout_report/figures/flow.pdf
--- a/doc/optimal_layout_report/figures/flow.svg
+++ b/doc/optimal_layout_report/figures/flow.svg
--- a/doc/optimal_layout_report/figures/flow_graph_param.pdf
+++ b/doc/optimal_layout_report/figures/flow_graph_param.pdf
--- a/doc/optimal_layout_report/figures/flow_graph_param.svg
+++ b/doc/optimal_layout_report/figures/flow_graph_param.svg
--- a/doc/optimal_layout_report/figures/mini_node.pdf
+++ b/doc/optimal_layout_report/figures/mini_node.pdf
--- a/doc/optimal_layout_report/figures/mini_node.svg
+++ b/doc/optimal_layout_report/figures/mini_node.svg
--- a/doc/optimal_layout_report/figures/mini_zone.pdf
+++ b/doc/optimal_layout_report/figures/mini_zone.pdf
--- a/doc/optimal_layout_report/figures/mini_zone.svg
+++ b/doc/optimal_layout_report/figures/mini_zone.svg
--- a/doc/optimal_layout_report/figures/naive.pdf
+++ b/doc/optimal_layout_report/figures/naive.pdf
--- a/doc/optimal_layout_report/figures/naive.svg
+++ b/doc/optimal_layout_report/figures/naive.svg
--- a/doc/optimal_layout_report/geodistrib.pdf
+++ b/doc/optimal_layout_report/geodistrib.pdf
--- a/doc/optimal_layout_report/geodistrib.tex
+++ b/doc/optimal_layout_report/geodistrib.tex
@ -1,317 +0,0 @@
 \documentclass[]{article}
 \usepackage{amsmath,amssymb}
 \usepackage{amsthm}
 \usepackage{stmaryrd}
 \usepackage{graphicx,xcolor}
 \usepackage{hyperref}
 \usepackage{algorithm,algpseudocode,float} 
 \renewcommand\thesubsubsection{\Alph{subsubsection})}
 \newtheorem{proposition}{Proposition}
 %opening
 \title{An algorithm for geo-distributed and redundant storage in Garage}
 \author{Mendes Oulamara \\ \emph{mendes@deuxfleurs.fr}}
 \date{}
 \begin{document}
 \maketitle
 \begin{abstract}
 	Garage
 \end{abstract}
 \section{Introduction}
 Garage\footnote{\url{https://garagehq.deuxfleurs.fr/}} is an open-source distributed object storage service tailored for self-hosting. It was designed by the Deuxfleurs association\footnote{\url{https://deuxfleurs.fr/}} to enable small structures (associations, collectives, small companies) to share storage resources to reliably self-host their data, possibly with old and non-reliable machines.
 To achieve these reliability and availability goals, the data is broken into \emph{partitions} and every partition is replicated over 3 different machines (that we call \emph{nodes}). When the data is queried, a consensus algorithm allows to fetch it from one of the nodes. A \emph{replication factor} of 3 ensures the best guarantees in the consensus algorithm \cite{ADD RREF}, but this parameter can be different.
 Moreover, if the nodes are spread over different \emph{zones} (different houses, offices, cities\dots), we can ask the data to be replicated over nodes belonging to different zones, to improve the storage robustness against zone failure (such as power outage). To do so, we set a \emph{redundancy parameter}, that is no more than the replication factor, and we ask that any partition is replicated over this number of zones at least.
 In this work, we propose a repartition algorithm that, given the nodes specifications and the replication and redundancy parameters, computes an optimal assignation of partitions to nodes. We say that the assignation is optimal in the sense that it maximizes the size of the partitions, and hence the effective storage capacity of the system.
 Moreover, when a former assignation exists, which is not optimal anymore due to nodes or zones updates, our algorithm computes a new optimal assignation that minimizes the amount of data to be transferred during the assignation update (the \emph{transfer load}).
 We call the set of nodes cooperating to store the data a \emph{cluster}, and a description of the nodes, zones and the assignation of partitions to nodes a \emph{cluster layout}
 \subsection{Notations}
 Let $k$ be some fixed parameter value, typically 8, that we call the ``partition bits''.
 Every object to be stored in the system is split into data blocks of fixed size. We compute a hash $h(\mathbf{b})$ of every such block $\mathbf{b}$, and we define the $k$ last bits of this hash to be the partition number $p(\mathbf{b})$ of the block. This label can take $P=2^k$ different values, and hence there are $P$ different partitions. We denote $\mathbf{P}$ the set of partition labels (i.e. $\mathbf{P}=\llbracket1,P\rrbracket$).
 We are given a set $\mathbf{N}$ of $N$ nodes  and a set  $\mathbf{Z}$ of $Z$ zones. Every node $n$ has a non-negative storage capacity $c_n\ge 0$ and belongs to a zone $z_n\in \mathbf{Z}$. We are also given a replication parameter $\rho_\mathbf{N}$ and a redundancy parameter $\rho_\mathbf{Z}$ such that  $1\le \rho_\mathbf{Z} \le \rho_\mathbf{N}$ (typical values would be $\rho_N=3$ and $\rho_Z=2$).
 Our goal is to compute an assignment $\alpha = (\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}})_{p\in \mathbf{P}}$ such that every partition $p$ is associated to $\rho_\mathbf{N}$ distinct nodes $\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}} \in \mathbf{N}$ and these nodes belong to at least $\rho_\mathbf{Z}$ distinct zones. Among the possible assignations, we choose one that \emph{maximizes} the effective storage capacity of the cluster. If the layout contained a previous assignment $\alpha'$, we \emph{minimize} the amount of data to transfer during the layout update by making $\alpha$ as close as possible to $\alpha'$. These maximization and minimization are described more formally in the following section.
 \subsection{Optimization parameters}
 To link the effective storage capacity of the cluster to partition assignment, we make the following assumption:
 \begin{equation}
 	\tag{H1}
 	\text{\emph{All partitions have the same size $s$.}}
 \end{equation}
 This assumption is justified by the dispersion of the hashing function, when the number of partitions is small relative to the number of stored blocks.
 Every node $n$ wille store some number $p_n$ of partitions (it is the number of partitions $p$ such that $n$ appears in the $\alpha_p$). Hence the partitions stored by $n$ (and hence all partitions by our assumption) have there size bounded by $c_n/p_n$. This remark leads us to define the optimal size that we will want to maximize:
 \begin{equation}
 	\label{eq:optimal}
 	\tag{OPT}
 s^* = \min_{n \in N} \frac{c_n}{p_n}.
 \end{equation}
 When the capacities of the nodes are updated (this includes adding or removing a node), we want to update the assignment as well. However, transferring the data between nodes has a cost and we would like to limit the number of changes in the assignment. We make the following assumption:
 \begin{equation}
 	\tag{H2}
 	\text{\emph{Nodes updates happen rarely relatively to block operations.}}
 \end{equation}
 This assumption justifies that when we compute the new assignment $\alpha$, it is worth to optimize the partition size \eqref{eq:optimal} first, and then, among the possible optimal solution, to try to minimize the number of partition transfers. More formally, we minimize the distance between two assignments defined by
 \begin{equation}
 	d(\alpha, \alpha') := \#\{ (n,p) \in \mathbf{N}\times\mathbf{P} ~|~ n\in \alpha_p \triangle \alpha'_p \}
 \end{equation}
 where the symmetric difference $\alpha_p \triangle \alpha'_p$ denotes the nodes appearing in one of the assignations but not in both.
 \section{Computation of an optimal assignment}
 The algorithm that we propose takes as inputs the cluster layout parameters $\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$, that we defined in the introduction, together with the former assignation $\alpha'$ (if any). The computation of the new optimal assignation $\alpha^*$ is done in three successive steps that will be detailed in the following sections. The first step computes the largest partition size $s^*$ that an assignation can achieve. The second step computes an optimal candidate assignment $\alpha$ that achieves $s^*$ and a heuristic is used in the computation to make it hopefully close to $\alpha'$. The third steps modifies $\alpha$ iteratively to reduces $d(\alpha, \alpha')$ and yields an assignation $\alpha^*$ achieving $s^*$, and minimizing $d(\cdot, \alpha')$ among such assignations.
 We will explain in the next section how to represent an assignment $\alpha$ by a flow $f$ on a weighted graph $G$ to enable the use of flow and graph algorithms. The main function of the algorithm can be written as follows.
 \subsubsection*{Algorithm}
 \begin{algorithmic}[1]
 	\Function{Compute Layout}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$, $\alpha'$}
 	\State $s^* \leftarrow$ \Call{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$}
 	\State $G \leftarrow G(s^*)$
 	\State $f \leftarrow$ 	\Call{Compute Candidate Assignment}{$G$, $\alpha'$}
 	\State $f^* \leftarrow$ 	\Call{Minimize transfer load}{$G$, $f$, $\alpha'$}
 	\State Build $\alpha^*$ from $f^*$
 	\State \Return $\alpha^*$
 	\EndFunction
 \end{algorithmic}
 \subsubsection*{Complexity}
 As we will see in the next sections, the worst case complexity of this algorithm is $O(P^2 N^2)$. The minimization of transfer load is the most expensive step, and it can run with a timeout since it is only an optimization step. Without this step (or with a smart timeout), the worst cas complexity can be $O((PN)^{3/2}\log C)$ where $C$ is the total storage capacity of the cluster. 
 \subsection{Determination of the partition size $s^*$}
 We will represent an assignment $\alpha$ as a flow in a specific graph $G$. We will not compute the optimal partition size $s^*$ a priori, but we will determine it by dichotomy, as the largest size $s$ such that the maximal flow achievable on $G=G(s)$ has value $\rho_\mathbf{N}P$. We will assume that the capacities are given in a small enough unit (say, Megabytes), and we will determine $s^*$ at the precision of the given unit.
 Given some candidate size value $s$, we describe the oriented weighted graph $G=(V,E)$ with vertex set $V$ arc set $E$ (see Figure \ref{fig:flowgraph}).
 The set of vertices $V$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices 
 $\mathbf{p^+, p^-}$ for every partition $p$, vertices $\mathbf{x}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{n}$ for every node $n$. 
 The set of arcs $E$ contains:
 \begin{itemize}
 	\item ($\mathbf{s}$,$\mathbf{p}^+$, $\rho_\mathbf{Z}$) for every partition $p$;
 	\item ($\mathbf{s}$,$\mathbf{p}^-$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$;
 	\item ($\mathbf{p}^+$,$\mathbf{x}_{p,z}$, 1) for every partition $p$ and zone $z$;
 	\item ($\mathbf{p}^-$,$\mathbf{x}_{p,z}$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$ and zone $z$;
 	\item ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) for every partition $p$, zone $z$ and node $n\in z$;
 	\item ($\mathbf{n}$, $\mathbf{t}$, $\lfloor c_n/s \rfloor$) for every node $n$.
 \end{itemize}
 \begin{figure}
 	\centering
 	\includegraphics[width=\linewidth]{figures/flow_graph_param}
 	\caption{An example of graph $G(s)$. Arcs are oriented from left to right, and unlabeled arcs have capacity 1. In this example, nodes $n_1,n_2,n_3$ belong to zone $z_1$, and nodes $n_4,n_5$ belong to zone $z_2$.}
 	\label{fig:flowgraph}
 \end{figure}
 In the following complexity calculations, we will use the number of vertices and edges of $G$. Remark from now that $\# V = O(PZ)$ and $\# E = O(PN)$.
 \begin{proposition}
 	An assignment $\alpha$ is realizable with partition size $s$ and the redundancy constraints $(\rho_\mathbf{N},\rho_\mathbf{Z})$ if and only if there exists a maximal flow function $f$ in $G$ with total flow $\rho_\mathbf{N}P$, such that the arcs ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) used are exactly those for which $p$ is associated to $n$ in $\alpha$.
 \end{proposition}
 \begin{proof}
 	Given such flow $f$, we can reconstruct a candidate $\alpha$. In $f$, the flow passing through $\mathbf{p^+}$ and $\mathbf{p^-}$ is $\rho_\mathbf{N}$, and since the outgoing capacity of every $\mathbf{x}_{p,z}$ is 1, every partition is associated to $\rho_\mathbf{N}$ distinct nodes. The fraction $\rho_\mathbf{Z}$ of the flow passing through every $\mathbf{p^+}$ must be spread over as many distinct zones as every arc outgoing from $\mathbf{p^+}$ has capacity 1. So the reconstructed $\alpha$ verifies the redundancy constraints. For every node $n$, the flow between $\mathbf{n}$ and $\mathbf{t}$ corresponds to the number of partitions associated to $n$. By construction of $f$, this does not exceed $\lfloor c_n/s \rfloor$. We assumed that the partition size is $s$, hence this association does not exceed the storage capacity of the nodes.
 	In the other direction, given an assignment $\alpha$, one can similarly check that the facts that $\alpha$ respects the redundancy constraints, and the storage capacities of the nodes, are necessary condition to construct a maximal flow function $f$.
 \end{proof}
 \textbf{Implementation remark:} In the flow algorithm, while exploring the graph, we explore the neighbours of every vertex in a random order to heuristically spread the associations between nodes and partitions.
 \subsubsection*{Algorithm}
 With this result mind, we can describe the first step of our algorithm. All divisions are supposed to be integer divisions.
 \begin{algorithmic}[1]
 	\Function{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$}
 	\State Build the graph $G=G(s=1)$
 	\State $ f \leftarrow$ \Call{Maximal flow}{$G$}
 	\If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$}
 	\State \Return Error: capacities too small or constraints too strong.
 	\EndIf
 	\State $s^- \leftarrow 1$
 	\State $s^+ \leftarrow 1+\frac{1}{\rho_\mathbf{N}}\sum_{n \in \mathbf{N}} c_n$
 	\While{$s^-+1 < s^+$}
 	\State Build the graph $G=G(s=(s^-+s^+)/2)$
 	\State $ f \leftarrow$ \Call{Maximal flow}{$G$}
 	\If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$}
 	\State $s^+ \leftarrow (s^- + s^+)/2$
 	\Else
 	\State $s^- \leftarrow (s^- + s^+)/2$
 	\EndIf
 	\EndWhile
 	\State \Return $s^-$
 	\EndFunction
 \end{algorithmic}
 \subsubsection*{Complexity}
 To compute the maximal flow, we use Dinic's algorithm. Its complexity on general graphs is $O(\#V^2 \#E)$, but on graphs with edge capacity bounded by a constant, it turns out to be $O(\#E^{3/2})$. The graph $G$ does not fall in this case since the capacities of the arcs incoming to $\mathbf{t}$ are far from bounded. However, the proof of this complexity function works readily for graphs where we only ask the edges \emph{not} incoming to the sink $\mathbf{t}$ to have their capacities bounded by a constant. One can find the proof of this claim in \cite[Section 2]{even1975network}.
 The dichotomy adds a logarithmic factor $\log (C)$ where $C=\sum_{n \in \mathbf{N}} c_n$ is the total capacity of the cluster. The total complexity of this first function is hence 
 $O(\#E^{3/2}\log C ) = O\big((PN)^{3/2} \log C\big)$.
 \subsubsection*{Metrics}
 We can display the discrepancy between the computed $s^*$ and the best size we could have hoped for the given total capacity, that is $C/\rho_\mathbf{N}$.
 \subsection{Computation of a candidate assignment}
 Now that we have the optimal partition size $s^*$, to compute a candidate assignment it would be enough to compute a maximal flow function $f$ on $G(s^*)$. This is what we do if there is no former assignation $\alpha'$.
 If there is some $\alpha'$, we add a step that will heuristically help to obtain a candidate $\alpha$ closer to $\alpha'$. We fist compute a flow function $\tilde{f}$ that uses only the partition-to-node associations appearing in $\alpha'$. Most likely, $\tilde{f}$ will not be a maximal flow of $G(s^*)$. In Dinic's algorithm, we can start from a non maximal flow function and then discover improving paths. This is what we do by starting from $\tilde{f}$. The hope\footnote{This is only a hope, because one can find examples where the construction of $f$ from $\tilde{f}$ produces an assignment $\alpha$ that is not as close as possible to $\alpha'$.} is that the final flow function $f$ will tend to keep the associations appearing in $\tilde{f}$.
 More formally, we construct the graph $G_{|\alpha'}$ from $G$ by removing all the arcs $(\mathbf{x}_{p,z},\mathbf{n}, 1)$ where $p$ is not associated to $n$ in $\alpha'$. We compute a maximal flow function $\tilde{f}$ in $G_{|\alpha'}$. The flow $\tilde{f}$ is also a valid (most likely non maximal) flow function on $G$. We compute a maximal flow function $f$ on $G$ by starting Dinic's algorithm on $\tilde{f}$.
 \subsubsection*{Algorithm}
 \begin{algorithmic}[1]
 	\Function{Compute Candidate Assignment}{$G$, $\alpha'$}
 	\State Build the graph $G_{|\alpha'}$
 	\State $ \tilde{f} \leftarrow$ \Call{Maximal flow}{$G_{|\alpha'}$}
 	\State $ f \leftarrow$ \Call{Maximal flow from flow}{$G$, $\tilde{f}$}
 	\State \Return $f$
 	\EndFunction
 \end{algorithmic}
 ~ 
 \textbf{Remark:} The function ``Maximal flow'' can be just seen as the function ``Maximal flow from flow'' called with the zero flow function as starting flow.
 \subsubsection*{Complexity}
 With the considerations of the last section, we have the complexity of the Dinic's algorithm $O(\#E^{3/2}) = O((PN)^{3/2})$.
 \subsubsection*{Metrics}
 We can display the flow value of $\tilde{f}$, which is an upper bound of the distance between $\alpha$ and $\alpha'$. It might be more a Debug level display than Info.
 \subsection{Minimization of the transfer load}
 Now that we have a candidate flow function $f$, we want to modify it to make its corresponding assignation $\alpha$ as close as possible to $\alpha'$. Denote by $f'$ the maximal flow corresponding to $\alpha'$, and let $d(f, \alpha')=d(f, f'):=d(\alpha,\alpha')$\footnote{It is the number of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$ saturated in one flow and not in the other.}. 
 We want to build a sequence $f=f_0, f_1, f_2 \dots$ of maximal flows such that $d(f_i, \alpha')$ decreases as $i$ increases. The distance being a non-negative integer, this sequence of flow functions must be finite. We now explain how to find some improving $f_{i+1}$ from $f_i$.
 For any maximal flow $f$ in $G$, we define the oriented weighted graph $G_f=(V, E_f)$ as follows. The vertices of $G_f$ are the same as the vertices of $G$. $E_f$ contains the arc $(v_1,v_2, w)$ between vertices $v_1,v_2\in V$ with weight $w$ if and only if the arc $(v_1,v_2)$ is not saturated in $f$ (i.e. $c(v_1,v_2)-f(v_1,v_2) \ge 1$, we also consider reversed arcs). The weight $w$ is: 
 \begin{itemize}
 	\item  $-1$  if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in only one of the two flows $f,f'$;
 	\item $+1$  if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in either both or none of the two flows $f,f'$;
 	\item $0$ otherwise.
 \end{itemize}
 If $\gamma$ is a simple cycle of arcs in $G_f$, we define its weight $w(\gamma)$ as the sum of the weights of its arcs. We can add $+1$ to the value of $f$ on the arcs of $\gamma$, and by construction of $G_f$ and the fact that $\gamma$ is a cycle, the function that we get is still a valid flow function on $G$, it is maximal as it has the same flow value as $f$. We denote this new function $f+\gamma$.
 \begin{proposition}
 	Given a maximal flow $f$ and a simple cycle $\gamma$ in $G_f$, we have $d(f+\gamma, f') - d(f,f') = w(\gamma)$.
 \end{proposition}
 \begin{proof}
 	Let $X$ be the set of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$. Then we can express $d(f,f')$ as
 	\begin{align*}
 		d(f,f') & = \#\{e\in X ~|~ f(e)\neq f'(e)\}
 		= \sum_{e\in X} 1_{f(e)\neq f'(e)} \\
 		& = \frac{1}{2}\big( \#X + \sum_{e\in X} 1_{f(e)\neq f'(e)} - 1_{f(e)= f'(e)} \big).
 	\end{align*}
 	We can express the cycle weight as
 	\begin{align*}
 		w(\gamma) &  = \sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)}.
 	\end{align*}
 	Remark that since we passed on unit of flow in $\gamma$ to construct $f+\gamma$, we have for any $e\in X$, $f(e)=f'(e)$ if and only if $(f+\gamma)(e) \neq f'(e)$.
 	Hence
 	\begin{align*}
 		w(\gamma) &  = \frac{1}{2}(w(\gamma) + w(\gamma)) \\
 		&= \frac{1}{2} \Big( 
 		\sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} +  1_{f(e)= f'(e)} \\
 		& \qquad +
 		\sum_{e\in X, e\in \gamma} 1_{(f+\gamma)(e)\neq f'(e)} +  1_{(f+\gamma)(e)= f'(e)}
 		\Big).
 	\end{align*}
 	Plugging this in the previous equation, we find that 
 	$$d(f,f')+w(\gamma) = d(f+\gamma, f').$$
 \end{proof}
 This result suggests that given some flow $f_i$, we just need to find a negative cycle $\gamma$ in $G_{f_i}$ to construct $f_{i+1}$ as $f_i+\gamma$. The following proposition ensures that this greedy strategy reaches an optimal flow. 
 \begin{proposition}
 	For any maximal flow $f$, $G_f$ contains a negative cycle if and only if there exists a maximal flow $f^*$ in $G$ such that $d(f^*, f') < d(f, f')$.
 \end{proposition}
 \begin{proof}
 	Suppose that there is such flow $f^*$. Define the oriented multigraph $M_{f,f^*}=(V,E_M)$ with the same vertex set $V$ as in $G$, and for every $v_1,v_2 \in V$, $E_M$ contains $(f^*(v_1,v_2) - f(v_1,v_2))_+$  copies of the arc $(v_1,v_2)$. For every vertex $v$, its total degree (meaning its outer degree minus its inner degree) is equal to 
 	\begin{align*}
 		\deg v & = \sum_{u\in V} (f^*(v,u) - f(v,u))_+ - \sum_{u\in V} (f^*(u,v) - f(u,v))_+  \\
 		& = \sum_{u\in V} f^*(v,u) - f(v,u) = \sum_{u\in V} f^*(v,u) - \sum_{u\in V}  f(v,u).
 	\end{align*}
 	The last two sums are zero for any inner vertex since $f,f^*$ are flows, and they are equal on the source and sink since the two flows are both maximal and have hence the same value. Thus, $\deg v = 0$ for every vertex $v$.
 	This implies that the multigraph $M_{f,f^*}$ is the union of disjoint simple cycles. $f$ can be transformed into $f^*$ by pushing a mass 1 along all these cycles in any order. Since $d(f^*, f')<d(f,f')$, there must exists one of these simple cycles $\gamma$ with $d(f+\gamma, f') < d(f, f')$. Finally, since we can push a mass in $f$ along $\gamma$, it must appear in $G_f$. Hence $\gamma$ is a cycle of $G_f$ with negative weight.
 \end{proof}
 In the next section we describe the corresponding algorithm. Instead of discovering only one cycle, we are allowed to discover a set $\Gamma$ of disjoint negative cycles. 
 \subsubsection*{Algorithm}
 \begin{algorithmic}[1]
 	\Function{Minimize transfer load}{$G$, $f$, $\alpha'$}
 	\State Build the graph $G_f$
 	\State $\Gamma \leftarrow$ \Call{Detect Negative Cycles}{$G_f$}
 	\While{$\Gamma \neq \emptyset$}
 	\ForAll{$\gamma \in \Gamma$}
 	\State $f \leftarrow f+\gamma$
 	\EndFor
 	\State Update $G_f$
 	\State $\Gamma \leftarrow$ \Call{Detect Negative Cycles}{$G_f$}
 	\EndWhile
 	\State \Return $f$
 	\EndFunction
 \end{algorithmic}
 \subsubsection*{Complexity}
 The distance $d(f,f')$ is bounded by the maximal number of differences in the associated assignment. If these assignment are totally disjoint, this distance is $2\rho_N P$. At every iteration of the While loop, the distance decreases, so there is at most $O(\rho_N P) = O(P)$ iterations.
 The detection of negative cycle is done with the Bellman-Ford algorithm, whose complexity should normally be $O(\#E\#V)$. In our case, it amounts to $O(P^2ZN)$. Multiplied by the complexity of the outer loop, it amounts to $O(P^3ZN)$ which is a lot when the number of partitions and nodes starts to be large. To avoid that, we adapt the Bellman-Ford algorithm.
 The Bellman-Ford algorithm runs $\#V$ iterations of an outer loop, and an inner loop over $E$. The idea is to compute the shortest paths from a source vertex $v$ to all other vertices. After $k$ iterations of the outer loop, the algorithm has computed all shortest path of length at most $k$. All simple paths have length at most $\#V-1$, so if there is an update in the last iteration of the loop, it means that there is a negative cycle in the graph. The observation that will enable us to improve the complexity is the following:
 \begin{proposition}
 	In the graph $G_f$ (and $G$), all simple paths have a length at most $4N$.
 \end{proposition}
 \begin{proof}
 	Since $f$ is a maximal flow, there is no outgoing edge from $\mathbf{s}$ in $G_f$. One can thus check than any simple path of length 4 must contain at least two node of type $\mathbf{n}$. Hence on a path, at most 4 arcs separate two successive nodes of type $\mathbf{n}$. 
 \end{proof}
 Thus, in the absence of negative cycles, shortest paths in $G_f$ have length at most $4N$. So we can do only $4N+1$ iterations of the outer loop in the Bellman-Ford algorithm. This makes the complexity of the detection of one set of cycle to be $O(N\#E) = O(N^2 P)$.
 With this improvement, the complexity of the whole algorithm is, in the worst case, $O(N^2P^2)$. However, since we detect several cycles at once and we start with a flow that might be close to the previous one, the number of iterations of the outer loop might be smaller in practice.
 \subsubsection*{Metrics}
 We can display the node and zone utilization ratio, by dividing the flow passing through them divided by their outgoing capacity. In particular, we can pinpoint saturated nodes and zones (i.e. used at their full potential).
 We can display the distance to the previous assignment, and the number of partition transfers.
 \bibliography{optimal_layout} 
 \bibliographystyle{ieeetr}
 \end{document}
--- a/doc/optimal_layout_report/optimal_layout.bib
+++ b/doc/optimal_layout_report/optimal_layout.bib
@ -1,11 +0,0 @@
@article{even1975network,
 	title={Network flow and testing graph connectivity},
 	author={Even, Shimon and Tarjan, R Endre},
 	journal={SIAM journal on computing},
 	volume={4},
 	number={4},
 	pages={507--518},
 	year={1975},
 	publisher={SIAM}
 }
--- a/doc/optimal_layout_report/optimal_layout.pdf
+++ b/doc/optimal_layout_report/optimal_layout.pdf
--- a/doc/optimal_layout_report/optimal_layout.tex
+++ b/doc/optimal_layout_report/optimal_layout.tex
@ -1,709 +0,0 @@
 \documentclass[]{article}
 \usepackage{amsmath,amssymb}
 \usepackage{amsthm}
 \usepackage{graphicx,xcolor}
 \usepackage{algorithm,algpseudocode,float} 
 \renewcommand\thesubsubsection{\Alph{subsubsection})}
 \newtheorem{proposition}{Proposition}
 %opening
 \title{Optimal partition assignment in Garage}
 \author{Mendes}
 \begin{document}
 \maketitle
 \section{Introduction}
 \subsection{Context}
 Garage is an open-source distributed storage service blablabla$\dots$
 Every object to be stored in the system falls in a partition given by the last $k$ bits of its hash. There are $P=2^k$ partitions. Every partition will be stored on distinct nodes of the system. The goal of the assignment of partitions to nodes is to ensure (nodes and zone) redundancy and to be as efficient as possible.
 \subsection{Formal description of the problem}
 We are given a set of nodes $\mathbf{N}$ and a set of zones $\mathbf{Z}$. Every node $n$ has a non-negative storage capacity $c_n\ge 0$ and belongs to a zone $z\in \mathbf{Z}$. We are also given a number of partition $P>0$ (typically $P=256$).
 We would like to compute an assignment of nodes to partitions. We will impose some redundancy constraints to this assignment, and under these constraints, we want our system to have the largest storage capacity possible. To link storage capacity to partition assignment, we make the following assumption:
 \begin{equation}
 	\tag{H1}
 	\text{\emph{All partitions have the same size $s$.}}
 \end{equation}
 This assumption is justified by the dispersion of the hashing function, when the number of partitions is small relative to the number of stored large objects.
 Every node $n$ wille store some number $k_n$ of partitions. Hence the partitions stored by $n$ (and hence all partitions by our assumption) have there size bounded by $c_n/k_n$. This remark leads us to define the optimal size that we will want to maximize:
 \begin{equation}
 	\label{eq:optimal}
 	\tag{OPT}
 s^* = \min_{n \in N} \frac{c_n}{k_n}.
 \end{equation}
 When the capacities of the nodes are updated (this includes adding or removing a node), we want to update the assignment as well. However, transferring the data between nodes has a cost and we would like to limit the number of changes in the assignment. We make the following assumption:
 \begin{equation}
 	\tag{H2}
 	\text{\emph{Updates of capacity happens rarely relatively to object storing.}}
 \end{equation}
 This assumption justifies that when we compute the new assignment, it is worth to optimize the partition size \eqref{eq:optimal} first, and then, among the possible optimal solution, to try to minimize the number of partition transfers.
 For now, in the following, we ask the following redundancy constraint:
 \textbf{Parametric node and zone redundancy:} Given two integer parameters $1\le \rho_\mathbf{Z} \le \rho_\mathbf{N}$, we ask every partition to be stored on $\rho_\mathbf{N}$ distinct nodes, and these nodes must belong to at least $\rho_\mathbf{Z}$ distinct zones.
 \textbf{Mode 3-strict:}  every partition needs to be assignated to three nodes belonging to three different zones.
 \textbf{Mode 3:} every partition needs to be assignated to three nodes. We try to spread the three nodes over different zones as much as possible.
 \textbf{Warning:} This is a working document written incrementaly. The last version of the algorithm is the \textbf{parametric assignment} described in the next section.
 \section{Computation of a parametric assignment}
 \textbf{Attention : }We change notations in this section.
 Notations : let $P$ be the number of partitions, $N$ the number of nodes, $Z$ the number of zones. Let $\mathbf{P,N,Z}$ be the label sets of, respectively, partitions, nodes and zones.
 Let $s^*$ be the largest partition size achievable with the redundancy constraints. Let $(c_n)_{n\in \mathbf{N}}$ be the storage capacity of every node. 
 In this section, we propose a third specification of the problem. The user inputs two redundancy parameters $1\le \rho_\mathbf{Z} \le \rho_\mathbf{N}$. We compute an assignment $\alpha = (\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}})_{p\in \mathbf{P}}$ such that every partition $p$ is associated to $\rho_\mathbf{N}$ distinct nodes $\alpha_p^1, \ldots, \alpha_p^{\rho_\mathbf{N}}$ and these nodes belong to at least $\rho_\mathbf{Z}$ distinct zones.
 If the layout contained a previous assignment $\alpha'$, we try to minimize the amount of data to transfer during the layout update by making $\alpha$ as close as possible to $\alpha'$.
 In the following subsections, we describe the successive steps of the algorithm we propose to compute $\alpha$.
 \subsubsection*{Algorithm}
 \begin{algorithmic}[1]
 	\Function{Compute Layout}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$, $\alpha'$}
 	\State $s^* \leftarrow$ \Call{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$}
 	\State $G \leftarrow G(s^*)$
 	\State $f \leftarrow$ 	\Call{Compute Candidate Assignment}{$G$, $\alpha'$}
 	\State $f^* \leftarrow$ 	\Call{Minimize transfer load}{$G$, $f$, $\alpha'$}
 	\State Build $\alpha^*$ from $f^*$
 	\State \Return $\alpha^*$
 	\EndFunction
 \end{algorithmic}
 \subsubsection*{Complexity}
 As we will see in the next sections, the worst case complexity of this algorithm is $O(P^2 N^2)$. The minimization of transfer load is the most expensive step, and it can run with a timeout since it is only an optimization step. Without this step (or with a smart timeout), the worst cas complexity can be $O((PN)^{3/2}\log C)$ where $C$ is the total storage capacity of the cluster. 
 \subsection{Determination of the partition size $s^*$}
 Again, we will represent an assignment $\alpha$ as a flow in a specific graph $G$. We will not compute the optimal partition size $s^*$ a priori, but we will determine it by dichotomy, as the largest size $s$ such that the maximal flow achievable on $G=G(s)$ has value $\rho_\mathbf{N}P$. We will assume that the capacities are given in a small enough unit (say, Megabytes), and we will determine $s^*$ at the precision of the given unit.
 Given some candidate size value $s$, we describe the oriented weighted graph $G=(V,E)$ with vertex set $V$ arc set $E$.
 The set of vertices $V$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices 
 $\mathbf{p^+, p^-}$ for every partition $p$, vertices $\mathbf{x}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{n}$ for every node $n$. 
 The set of arcs $E$ contains:
 \begin{itemize}
 	\item ($\mathbf{s}$,$\mathbf{p}^+$, $\rho_\mathbf{Z}$) for every partition $p$;
 	\item ($\mathbf{s}$,$\mathbf{p}^-$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$;
 	\item ($\mathbf{p}^+$,$\mathbf{x}_{p,z}$, 1) for every partition $p$ and zone $z$;
 	\item ($\mathbf{p}^-$,$\mathbf{x}_{p,z}$, $\rho_\mathbf{N}-\rho_\mathbf{Z}$) for every partition $p$ and zone $z$;
 	\item ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) for every partition $p$, zone $z$ and node $n\in z$;
 	\item ($\mathbf{n}$, $\mathbf{t}$, $\lfloor c_n/s \rfloor$) for every node $n$.
 \end{itemize}
 In the following complexity calculations, we will use the number of vertices and edges of $G$. Remark from now that $\# V = O(PZ)$ and $\# E = O(PN)$.
 \begin{proposition}
 	An assignment $\alpha$ is realizable with partition size $s$ and the redundancy constraints $(\rho_\mathbf{N},\rho_\mathbf{Z})$ if and only if there exists a maximal flow function $f$ in $G$ with total flow $\rho_\mathbf{N}P$, such that the arcs ($\mathbf{x}_{p,z}$,$\mathbf{n}$, 1) used are exactly those for which $p$ is associated to $n$ in $\alpha$.
 \end{proposition}
 \begin{proof}
 	Given such flow $f$, we can reconstruct a candidate $\alpha$. In $f$, the flow passing through $\mathbf{p^+}$ and $\mathbf{p^-}$ is $\rho_\mathbf{N}$, and since the outgoing capacity of every $\mathbf{x}_{p,z}$ is 1, every partition is associated to $\rho_\mathbf{N}$ distinct nodes. The fraction $\rho_\mathbf{Z}$ of the flow passing through every $\mathbf{p^+}$ must be spread over as many distinct zones as every arc outgoing from $\mathbf{p^+}$ has capacity 1. So the reconstructed $\alpha$ verifies the redundancy constraints. For every node $n$, the flow between $\mathbf{n}$ and $\mathbf{t}$ corresponds to the number of partitions associated to $n$. By construction of $f$, this does not exceed $\lfloor c_n/s \rfloor$. We assumed that the partition size is $s$, hence this association does not exceed the storage capacity of the nodes.
 	In the other direction, given an assignment $\alpha$, one can similarly check that the facts that $\alpha$ respects the redundancy constraints, and the storage capacities of the nodes, are necessary condition to construct a maximal flow function $f$.
 \end{proof}
 \textbf{Implementation remark:} In the flow algorithm, while exploring the graph, we explore the neighbours of every vertex in a random order to heuristically spread the association between nodes and partitions.
 \subsubsection*{Algorithm}
 With this result mind, we can describe the first step of our algorithm. All divisions are supposed to be integer division.
 \begin{algorithmic}[1]
 	\Function{Compute Partition Size}{$\mathbf{N}$, $\mathbf{Z}$, $\mathbf{P}$, $(c_n)_{n\in \mathbf{N}}$, $\rho_\mathbf{N}$, $\rho_\mathbf{Z}$}
 	\State Build the graph $G=G(s=1)$
 	\State $ f \leftarrow$ \Call{Maximal flow}{$G$}
 	\If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$}
 	\State \Return Error: capacities too small or constraints too strong.
 	\EndIf
 	\State $s^- \leftarrow 1$
 	\State $s^+ \leftarrow 1+\frac{1}{\rho_\mathbf{N}}\sum_{n \in \mathbf{N}} c_n$
 	\While{$s^-+1 < s^+$}
 	\State Build the graph $G=G(s=(s^-+s^+)/2)$
 	\State $ f \leftarrow$ \Call{Maximal flow}{$G$}
 	\If{$f.\mathrm{total flow} < \rho_\mathbf{N}P$}
 	\State $s^+ \leftarrow (s^- + s^+)/2$
 	\Else
 	\State $s^- \leftarrow (s^- + s^+)/2$
 	\EndIf
 	\EndWhile
 	\State \Return $s^-$
 	\EndFunction
 \end{algorithmic}
 \subsubsection*{Complexity}
 To compute the maximal flow, we use Dinic's algorithm. Its complexity on general graphs is $O(\#V^2 \#E)$, but on graphs with edge capacity bounded by a constant, it turns out to be $O(\#E^{3/2})$. The graph $G$ does not fall in this case since the capacities of the arcs incoming to $\mathbf{t}$ are far from bounded. However, the proof of this complexity works readily for graph where we only ask the edges \emph{not} incoming to the sink $\mathbf{t}$ to have their capacities bounded by a constant. One can find the proof of this claim in \cite[Section 2]{even1975network}.
 The dichotomy adds a logarithmic factor $\log (C)$ where $C=\sum_{n \in \mathbf{N}} c_n$ is the total capacity of the cluster. The total complexity of this first function is hence 
 $O(\#E^{3/2}\log C ) = O\big((PN)^{3/2} \log C\big)$.
 \subsubsection*{Metrics}
 We can display the discrepancy between the computed $s^*$ and the best size we could hope for a given total capacity, that is $C/\rho_\mathbf{N}$.
 \subsection{Computation of a candidate assignment}
 Now that we have the optimal partition size $s^*$, to compute a candidate assignment, it would be enough to compute a maximal flow function $f$ on $G(s^*)$. This is what we do if there was no previous assignment $\alpha'$.
 If there was some $\alpha'$, we add a step that will heuristically help to obtain a candidate $\alpha$ closer to $\alpha'$. to do so, we fist compute a flow function $\tilde{f}$ that uses only the partition-to-node association appearing in $\alpha'$. Most likely, $\tilde{f}$ will not be a maximal flow of $G(s^*)$. In Dinic's algorithm, we can start from a non maximal flow function and then discover improving paths. This is what we do in starting from $\tilde{f}$. The hope\footnote{This is only a hope, because one can find examples where the construction of $f$ from $\tilde{f}$ produces an assignment $\alpha$ that is not as close as possible to $\alpha'$.} is that the final flow function $f$ will tend to keep the associations appearing in $\tilde{f}$.
 More formally, we construct the graph $G_{|\alpha'}$ from $G$ by removing all the arcs $(\mathbf{x}_{p,z},\mathbf{n}, 1)$ where $p$ is not associated to $n$ in $\alpha'$. We compute a maximal flow function $\tilde{f}$ in $G_{|\alpha'}$. $\tilde{f}$ is also a valid (most likely non maximal) flow function in $G$. We compute a maximal flow function $f$ on $G$ by starting Dinic's algorithm on $\tilde{f}$.
 \subsubsection*{Algorithm}
 \begin{algorithmic}[1]
 	\Function{Compute Candidate Assignment}{$G$, $\alpha'$}
 	\State Build the graph $G_{|\alpha'}$
 	\State $ \tilde{f} \leftarrow$ \Call{Maximal flow}{$G_{|\alpha'}$}
 	\State $ f \leftarrow$ \Call{Maximal flow from flow}{$G$, $\tilde{f}$}
 	\State \Return $f$
 	\EndFunction
 \end{algorithmic}
 \textbf{Remark:} The function ``Maximal flow'' can be just seen as the function ``Maximal flow from flow'' called with the zero flow function as starting flow.
 \subsubsection*{Complexity}
 From the consideration of the last section, we have the complexity of the Dinic's algorithm $O(\#E^{3/2}) = O((PN)^{3/2})$.
 \subsubsection*{Metrics}
 We can display the flow value of $\tilde{f}$, which is an upper bound of the distance between $\alpha$ and $\alpha'$. It might be more a Debug level display than Info.
 \subsection{Minimization of the transfer load}
 Now that we have a candidate flow function $f$, we want to modify it to make its associated assignment as close as possible to $\alpha'$. Denote by $f'$ the maximal flow associated to $\alpha'$, and let $d(f, f')$ be distance between the associated assignments\footnote{It is the number of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$ saturated in one flow and not in the other.}. 
 We want to build a sequence $f=f_0, f_1, f_2 \dots$ of maximal flows such that $d(f_i, \alpha')$ decreases as $i$ increases. The distance being a non-negative integer, this sequence of flow functions must be finite. We now explain how to find some improving $f_{i+1}$ from $f_i$.
 For any maximal flow $f$ in $G$, we define the oriented weighted graph $G_f=(V, E_f)$ as follows. The vertices of $G_f$ are the same as the vertices of $G$. $E_f$ contains the arc $(v_1,v_2, w)$ between vertices $v_1,v_2\in V$ with weight $w$ if and only if the arc $(v_1,v_2)$ is not saturated in $f$ (i.e. $c(v_1,v_2)-f(v_1,v_2) \ge 1$, we also consider reversed arcs). The weight $w$ is: 
 \begin{itemize}
 	\item  $-1$  if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in only one of the two flows $f,f'$;
 	\item $+1$  if $(v_1,v_2)$ is of type $(\mathbf{x}_{p,z},\mathbf{n})$ or $(\mathbf{x}_{p,z},\mathbf{n})$ and is saturated in either both or none of the two flows $f,f'$;
 	\item $0$ otherwise.
 \end{itemize}
 If $\gamma$ is a simple cycle of arcs in $G_f$, we define its weight $w(\gamma)$ as the sum of the weights of its arcs. We can add $+1$ to the value of $f$ on the arcs of $\gamma$, and by construction of $G_f$ and the fact that $\gamma$ is a cycle, the function that we get is still a valid flow function on $G$, it is maximal as it has the same flow value as $f$. We denote this new function $f+\gamma$.
 \begin{proposition}
 	Given a maximal flow $f$ and a simple cycle $\gamma$ in $G_f$, we have $d(f+\gamma, f') - d(f,f') = w(\gamma)$.
 \end{proposition}
 \begin{proof}
 	Let $X$ be the set of arcs of type $(\mathbf{x}_{p,z},\mathbf{n})$. Then we can express $d(f,f')$ as
 	\begin{align*}
 		d(f,f') & = \#\{e\in X ~|~ f(e)\neq f'(e)\}
 		= \sum_{e\in X} 1_{f(e)\neq f'(e)} \\
 		& = \frac{1}{2}\big( \#X + \sum_{e\in X} 1_{f(e)\neq f'(e)} - 1_{f(e)= f'(e)} \big).
 	\end{align*}
 	We can express the cycle weight as
 	\begin{align*}
 		w(\gamma) &  = \sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} + 1_{f(e)= f'(e)}.
 	\end{align*}
 	Remark that since we passed on unit of flow in $\gamma$ to construct $f+\gamma$, we have for any $e\in X$, $f(e)=f'(e)$ if and only if $(f+\gamma)(e) \neq f'(e)$.
 	Hence
 	\begin{align*}
 		w(\gamma) &  = \frac{1}{2}(w(\gamma) + w(\gamma)) \\
 		&= \frac{1}{2} \Big( 
 		\sum_{e\in X, e\in \gamma} - 1_{f(e)\neq f'(e)} +  1_{f(e)= f'(e)} \\
 		& \qquad +
 		\sum_{e\in X, e\in \gamma} 1_{(f+\gamma)(e)\neq f'(e)} +  1_{(f+\gamma)(e)= f'(e)}
 		\Big).
 	\end{align*}
 	Plugging this in the previous equation, we find that 
 	$$d(f,f')+w(\gamma) = d(f+\gamma, f').$$
 \end{proof}
 This result suggests that given some flow $f_i$, we just need to find a negative cycle $\gamma$ in $G_{f_i}$ to construct $f_{i+1}$ as $f_i+\gamma$. The following proposition ensures that this greedy strategy reaches an optimal flow. 
 \begin{proposition}
 	For any maximal flow $f$, $G_f$ contains a negative cycle if and only if there exists a maximal flow $f^*$ in $G$ such that $d(f^*, f') < d(f, f')$.
 \end{proposition}
 \begin{proof}
 	Suppose that there is such flow $f^*$. Define the oriented multigraph $M_{f,f^*}=(V,E_M)$ with the same vertex set $V$ as in $G$, and for every $v_1,v_2 \in V$, $E_M$ contains $(f^*(v_1,v_2) - f(v_1,v_2))_+$  copies of the arc $(v_1,v_2)$. For every vertex $v$, its total degree (meaning its outer degree minus its inner degree) is equal to 
 	\begin{align*}
 		\deg v & = \sum_{u\in V} (f^*(v,u) - f(v,u))_+ - \sum_{u\in V} (f^*(u,v) - f(u,v))_+  \\
 		& = \sum_{u\in V} f^*(v,u) - f(v,u) = \sum_{u\in V} f^*(v,u) - \sum_{u\in V}  f(v,u).
 	\end{align*}
 	The last two sums are zero for any inner vertex since $f,f^*$ are flows, and they are equal on the source and sink since the two flows are both maximal and have hence the same value. Thus, $\deg v = 0$ for every vertex $v$.
 	This implies that the multigraph $M_{f,f^*}$ is the union of disjoint simple cycles. $f$ can be transformed into $f^*$ by pushing a mass 1 along all these cycles in any order. Since $d(f^*, f')<d(f,f')$, there must exists one of these simple cycles $\gamma$ with $d(f+\gamma, f') < d(f, f')$. Finally, since we can push a mass in $f$ along $\gamma$, it must appear in $G_f$. Hence $\gamma$ is a cycle of $G_f$ with negative weight.
 \end{proof}
 In the next section we describe the corresponding algorithm. Instead of discovering only one cycle, we are allowed to discover a set $\Gamma$ of disjoint negative cycles. 
 \subsubsection*{Algorithm}
 \begin{algorithmic}[1]
 	\Function{Minimize transfer load}{$G$, $f$, $\alpha'$}
 	\State Build the graph $G_f$
 	\State $\Gamma \leftarrow$ \Call{Detect Negative Cycles}{$G_f$}
 	\While{$\Gamma \neq \emptyset$}
 	\ForAll{$\gamma \in \Gamma$}
 	\State $f \leftarrow f+\gamma$
 	\EndFor
 	\State Update $G_f$
 	\State $\Gamma \leftarrow$ \Call{Detect Negative Cycles}{$G_f$}
 	\EndWhile
 	\State \Return $f$
 	\EndFunction
 \end{algorithmic}
 \subsubsection*{Complexity}
 The distance $d(f,f')$ is bounded by the maximal number of differences in the associated assignment. If these assignment are totally disjoint, this distance is $2\rho_N P$. At every iteration of the While loop, the distance decreases, so there is at most $O(\rho_N P) = O(P)$ iterations.
 The detection of negative cycle is done with the Bellman-Ford algorithm, whose complexity should normally be $O(\#E\#V)$. In our case, it amounts to $O(P^2ZN)$. Multiplied by the complexity of the outer loop, it amounts to $O(P^3ZN)$ which is a lot when the number of partitions and nodes starts to be large. To avoid that, we adapt the Bellman-Ford algorithm.
 The Bellman-Ford algorithm runs $\#V$ iterations of an outer loop, and an inner loop over $E$. The idea is to compute the shortest paths from a source vertex $v$ to all other vertices. After $k$ iterations of the outer loop, the algorithm has computed all shortest path of length at most $k$. All simple paths have length at most $\#V-1$, so if there is an update in the last iteration of the loop, it means that there is a negative cycle in the graph. The observation that will enable us to improve the complexity is the following:
 \begin{proposition}
 	In the graph $G_f$ (and $G$), all simple paths have a length at most $4N$.
 \end{proposition}
 \begin{proof}
 	Since $f$ is a maximal flow, there is no outgoing edge from $\mathbf{s}$ in $G_f$. One can thus check than any simple path of length 4 must contain at least two node of type $\mathbf{n}$. Hence on a path, at most 4 arcs separate two successive nodes of type $\mathbf{n}$. 
 \end{proof}
 Thus, in the absence of negative cycles, shortest paths in $G_f$ have length at most $4N$. So we can do only $4N+1$ iterations of the outer loop in Bellman-Ford algorithm. This makes the complexity of the detection of one set of cycle to be $O(N\#E) = O(N^2 P)$.
 With this improvement, the complexity of the whole algorithm is, in the worst case, $O(N^2P^2)$. However, since we detect several cycles at once and we start with a flow that might be close to the previous one, the number of iterations of the outer loop might be smaller in practice.
 \subsubsection*{Metrics}
 We can display the node and zone utilization ratio, by dividing the flow passing through them divided by their outgoing capacity. In particular, we can pinpoint saturated nodes and zones (i.e. used at their full potential).
 We can display the distance to the previous assignment, and the number of partition transfers.
 \section{Properties of an optimal 3-strict assignment}
 \subsection{Optimal assignment}
 \label{sec:opt_assign}
 For every zone $z\in Z$, define the zone capacity $c_z = \sum_{v, z_v=z} c_v$ and define $C = \sum_v c_v = \sum_z c_z$.
 One can check that the best we could be doing to maximize $s^*$ would be to use the nodes proportionally to their capacity. This would yield $s^*=C/(3N)$. This is not possible because of (i) redundancy constraints and (ii) integer rounding but it gives and upper bound. 
 \subsubsection*{Optimal utilization}
 We call an \emph{utilization} a collection of non-negative integers $(n_v)_{v\in V}$ such that $\sum_v n_v = 3N$ and for every zone $z$, $\sum_{v\in z} n_v \le N$. We call such utilization \emph{optimal} if it maximizes $s^*$.
 We start by computing a node sub-utilization $(\hat{n}_v)_{v\in V}$ such that for every zone $z$, $\sum_{v\in z} \hat{n}_v \le N$ and we show that there is an optimal utilization respecting the constraints and such that $\hat{n}_v \le n_v$ for every node.
 Assume that there is a zone $z_0$ such that $c_{z_0}/C \ge 1/3$. Then for any $v\in z_0$, we define 
 $$\hat{n}_v = \left\lfloor\frac{c_v}{c_{z_0}}N\right\rfloor.$$ 
 This choice ensures for any such $v$ that
 $$
 \frac{c_v}{\hat{n}_v} \ge \frac{c_{z_0}}{N} \ge \frac{C}{3N}
 $$
 which is the universal upper bound on $s^*$. Hence any optimal utilization $(n_v)$ can be modified to another optimal utilization such that $n_v\ge \hat{n}_v$
 Because $z_0$ cannot store more than $N$ partition occurences, in any assignment, at least $2N$ partitions must be assignated to the zones $Z\setminus\{z_0\}$. Let $C_0 = C-c_{z_0}$. Suppose that there exists a zone $z_1\neq z_0$ such that $c_{z_1}/C_0 \ge 1/2$. Then, with the same argument as for $z_0$, we can define 
 $$\hat{n}_v = \left\lfloor\frac{c_v}{c_{z_1}}N\right\rfloor$$
 for every $v\in z_1$.
 Now we can assign the remaining partitions. Let $(\hat{N}, \hat{C})$ to be
 \begin{itemize}
 	\item $(3N,C)$ if we did not find any $z_0$;
 	\item $(2N,C-c_{z_0})$ if there was a $z_0$ but no $z_1$;
 	\item $(N,C-c_{z_0}-c_{z_1})$ if there was a $z_0$ and a $z_1$.
 \end{itemize}
 Then at least $\hat{N}$ partitions must be spread among the remaining zones. Hence $s^*$ is upper bounded by $\hat{C}/\hat{N}$ and without loss of generality, we can define, for every node that is not in $z_0$ nor $z_1$, 
 $$\hat{n}_v = \left\lfloor\frac{c_v}{\hat{C}}\hat{N}\right\rfloor.$$ 
 We constructed a sub-utilization $\hat{n}_v$. Now notice that $3N-\sum_v \hat{n}_v \le \# V$ where $\# V$ denotes the number of nodes. We can iteratively pick a node $v^*$ such that 
 \begin{itemize}
 	\item $\sum_{v\in z_{v^*}} \hat{n}_v < N$ where $z_{v^*}$ is the zone of $v^*$;
 	\item $v^*$ maximizes the quantity $c_v/(\hat{n}_v+1)$ among the vertices satisfying the first condition (i.e. not in a saturated zone).
 \end{itemize}
 We iterate these instructions until $\sum_v \hat{n}_v= 3N$, and at this stage we define $(n_v) = (\hat{n}_v)$. It is easy to prove by induction that at every step, there is an optimal utilization that is pointwise larger than $\hat{n}_v$, and in particular, that $(n_v)$ is optimal.
 \subsubsection*{Existence of an optimal assignment}
 As for now, the \emph{optimal utilization} that we obtained is just a vector of numbers and it is not clear that it can be realized as the utilization of some concrete assignment. Here is a way to get a concrete assignment.
 Define $3N$ tokens $t_1,\ldots, t_{3N}\in V$ as follows:
 \begin{itemize}
 	\item Enumerate the zones $z$ of $Z$ in any order;
 	\item enumerate the nodes $v$ of $z$ in any order;
 	\item repeat $n_v$ times the token $v$.
 \end{itemize} 
 Then for $1\le i \le N$, define the triplet $T_i$ to be 
 $(t_i, t_{i+N}, t_{i+2N})$. Since the same nodes of a zone appear contiguously, the three nodes of a triplet must belong to three distinct zones.
 However simple, this solution to go from an utilization to an assignment has the drawback of not spreading the triplets: a node will tend to be associated to the same two other nodes for many partitions. Hence, during data transfer, it will tend to use only two link, instead of spreading the bandwith use over many other links to other nodes. To achieve this goal, we will reframe the search of an assignment as a flow problem. and in the flow algorithm, we will introduce randomness in the order of exploration. This will be sufficient to obtain a good dispersion of the triplets.
 \begin{figure}
 	\centering
 	\includegraphics[width=0.9\linewidth]{figures/naive}
 	\caption{On the left, the creation of a concrete assignment with the naive approach of repeating tokens. On the right, the zones containing the nodes.}
 \end{figure}
 \subsubsection*{Assignment as a maximum flow problem}
 We describe the flow problem via its graph $(X,E)$ where $X$ is a set of vertices, and $E$ are directed weighted edges between the vertices. For every zone $z$, define $n_z=\sum_{v\in z} n_v$.
 The set of vertices $X$ contains the source $\mathbf{s}$ and the sink $\mathbf{t}$; a vertex $\mathbf{x}_z$ for every zone $z\in Z$, and a vertex $\mathbf{y}_i$ for every partition index $1\le i\le N$. 
 The set of edges $E$ contains
 \begin{itemize}
 	\item the edge $(\mathbf{s}, \mathbf{x}_z, n_z)$ for every zone $z\in Z$;
 	\item the edge $(\mathbf{x}_z, \mathbf{y}_i, 1)$ for every zone $z\in Z$ and partition $1\le i\le N$;
 	\item the edge $(\mathbf{y}_i, \mathbf{t}, 3)$ for every partition $1\le i\le N$.
 \end{itemize}
 \begin{figure}[b]
 	\centering
 	\includegraphics[width=0.6\linewidth]{figures/flow}
 	\caption{Flow problem to compute and optimal assignment.}
 \end{figure}
 We first show the equivalence between this problem and and the construction of an assignment. Given some optimal assignment $(n_v)$, define the flow $f:E\to \mathbb{N}$ that saturates every edge from $\mathbf{s}$ or to $\mathbf{t}$, takes value $1$ on the edge between $\mathbf{x}_z$ and $\mathbf{y}_i$ if partition $i$ is stored in some node of the zone $z$, and $0$ otherwise. One can easily check that $f$ thus defined is indeed a flow and is maximum.
 Reciprocally, by the existence of maximum flows constructed from optimal assignments, any maximum flow must saturate the edges linked to the source or the sink. It can only take value 0 or 1 on the other edge, and every partition vertex is associated to exactly three distinct zone vertices. Every zone is associated to exactly $n_z$ partitions.
 A maximum flow can be constructed using, for instance, Dinic's algorithm. This algorithm works by discovering augmenting path to iteratively increase the flow. During the exploration of the graph to find augmenting path, we can shuffle the order of enumeration of the neighbours to spread the associations between zones and partitions.
 Once we have such association, we can randomly distribute the $n_z$ edges picked for every zone $z$ to its nodes $v\in z$ such that every such $v$ gets $n_z$ edges. This defines an optimal assignment of partitions to nodes.
 \subsection{Minimal transfer}
 Assume that there was a previous assignment $(T'_i)_{1\le i\le N}$ corresponding to utilizations $(n'_v)_{v\in V}$. We would like the new computed assignment $(T_i)_{1\le i\le N}$ from some $(n_v)_{v\in V}$ to minimize the number of partitions that need to be transferred. We can imagine two different objectives corresponding to different hypotheses: 
 \begin{equation}
 	\tag{H3A}
 	\label{hyp:A}
 	\text{\emph{Transfers between different zones cost much more than inside a zone.}}
 \end{equation}
 \begin{equation}
 	\tag{H3B}
 	\label{hyp:B}
 	\text{\emph{Changing zone is not the largest cost when transferring a partition.}}
 \end{equation}
 In case $A$, our goal will be to minimize the number of changes of zone in the assignment of partitions to zone. More formally, we will maximize the quantity
 $$
 Q_Z := 
 \sum_{1\le i\le N} 
 \#\{z\in Z ~|~ z\cap T_i \neq \emptyset, z\cap T'_i \neq \emptyset \}
 .$$
 In case $B$, our goal will be to minimize the number of changes of nodes in the assignment of partitions to nodes. We will maximize the quantity
 $$
 Q_V :=
 \sum_{1\le i\le N} \#(T_i \cap T'_i).
 $$
 It is tempting to hope that there is a way to maximize both quantity, that having the least discrepancy in terms of nodes will lead to the least discrepancy in terms of zones. But this is actually wrong! We propose the following counter-example to convince the reader:
 We consider eight nodes $a, a', b, c, d, d', e, e'$ belonging to five different zones $\{a,a'\}, \{b\}, \{c\}, \{d,d'\}, \{e, e'\}$. We take three partitions ($N=3$), that are originally assigned with some utilization $(n'_v)_{v\in V}$ as follows:
 $$
 T'_1=(a,b,c) \qquad
 T'_2=(a',b,d) \qquad 
 T'_3=(b,c,e).
 $$
 This assignment, with updated utilizations $(n_v)_{v\in V}$ minimizes the number of zone changes:
 $$
 T_1=(d,b,c) \qquad
 T_2=(a,b,d) \qquad 
 T_3=(b,c,e').
 $$
 This one, with the same utilization, minimizes the number of node changes:
 $$
 T_1=(a,b,c) \qquad
 T_2=(e',b,d) \qquad 
 T_3=(b,c,d').
 $$
 One can check that in this case, it is impossible to minimize both the number of zone and node changes.
 Because of the redundancy constraint, we cannot use a greedy algorithm to just replace nodes in the triplets to try to get the new utilization rate: this could lead to blocking situation where there is still a hole to fill in a triplet but no available node satisfies the zone separation constraint. To circumvent this issue, we propose an algorithm based on finding cycles in a graph encoding of the assignment. As in section \ref{sec:opt_assign}, we can explore the neigbours in a random order in the graph algorithms, to spread the triplets distribution.
 \subsubsection{Minimizing the zone discrepancy}
 First, notice that, given an assignment of partitions to \emph{zones}, it is easy to deduce an assignment to \emph{nodes} that minimizes the number of transfers for this zone assignment: For every zone $z$ and every node $v\in z$, pick in any way a set $P_v$ of partitions that where assigned to $v$ in $T'$, to $z_v$ in $T$, with the cardinality of $P_v$ smaller than $n_v$. Once all these sets are chosen, complement the assignment to reach the right utilization for every node. If $\#P_v > n_v$, it means that all the partitions that could stay in $v$ (i.e. that were already in $v$ and are still assigned to its zone) do stay in $v$. If $\#P_v = n_v$, then $n_v$ partitions stay in $v$, which is the number of partitions that need to be in $v$ in the end. In both cases, we could not hope for better given the partition to zone assignment.
 Our goal now is to find a assignment of partitions to zones that minimizes the number of zone transfers. To do so we are going to represent an assignment as a graph.
 Let $G_T=(X,E_T)$ be the directed weighted graph with vertices $(\mathbf{x}_i)_{1\le i\le N}$ and $(\mathbf{y}_z)_{z\in Z}$. For any $1\le i\le N$ and $z\in Z$, $E_T$ contains  the arc:
 \begin{itemize}
 	\item $(\mathbf{x}_i, \mathbf{y}_z, +1)$, if $z$ appears in $T_i'$ and $T_i$;
 	\item $(\mathbf{x}_i, \mathbf{y}_z, -1)$, if $z$ appears in $T_i$ but not in $T'_i$;
 	\item $(\mathbf{y}_z, \mathbf{x}_i, -1)$, if $z$ appears in $T'_i$ but not in $T_i$;
 	\item $(\mathbf{y}_z, \mathbf{x}_i, +1)$, if $z$ does not appear in $T'_i$ nor in $T_i$.
 \end{itemize}
 In other words, the orientation of the arc encodes whether partition $i$ is stored in zone $z$ in the assignment $T$ and the weight $\pm 1$ encodes whether this corresponds to what happens in the assignment $T'$.
 \begin{figure}[t]
 	\centering
 	\begin{minipage}{.40\linewidth}
 		\centering
 		\includegraphics[width=.8\linewidth]{figures/mini_zone}
 	\end{minipage}
 	\begin{minipage}{.55\linewidth}
 		\centering
 		\includegraphics[width=.8\linewidth]{figures/mini_node}
 	\end{minipage}
 	\caption{On the left: the graph $G_T$ encoding an assignment to minimize the zone discrepancy. On the right: the graph $G_T$ encoding an assignment to minimize the node discrepancy.}
 \end{figure}
 Notice that at every partition, there are three outgoing arcs, and at every zone, there are $n_z$ incoming arcs. Moreover, if $w(e)$ is the weight of an arc $e$, define the weight of $G_T$ by
 \begin{align*}
 w(G_T) := \sum_{e\in E} w(e) &= \#Z \times N - 4 \sum_{1\le i\le N} \#\{z\in Z ~|~ z\cap T_i = \emptyset, z\cap T'_i \neq \emptyset\}	\\
 &=\#Z \times N - 4 \sum_{1\le i\le N} 3- \#\{z\in Z ~|~ z\cap T_i \neq \emptyset, z\cap T'_i \neq \emptyset\} \\
 &= (\#Z-12)N + 4 Q_Z.
 \end{align*}
 Hence maximizing $Q_Z$ is equivalent to maximizing $w(G_T)$.
 Assume that their exist some assignment $T^*$ with the same utilization $(n_v)_{v\in V}$. Define $G_{T^*}$ similarly and consider the set $E_\mathrm{Diff} = E_T \setminus E_{T^*}$ of arcs that appear only in $G_T$. Since all vertices have the same number of incoming arcs in $G_T$ and $G_{T^*}$, the vertices of the graph $(X, E_\mathrm{Diff})$ must all have the same number number of incoming and outgoing arrows. So $E_\mathrm{Diff}$ can be expressed as a union of disjoint cycles. Moreover, the edges of $E_\mathrm{Diff}$ must appear in $E_{T^*}$ with reversed orientation and opposite weight. Hence, we have
 $$
 w(G_T) - w(G_{T^*}) = 2 \sum_{e\in E_\mathrm{Diff}} w(e). 
 $$
 Hence, if $T$ is not optimal, there exists some $T^*$ with $w(G_T) < w(G_{T^*})$, and by the considerations above, there must exist a cycle in $E_\mathrm{Diff}$, and hence in $G_T$, with negative weight. If we reverse the edges and weights along this cycle, we obtain some graph. Since we did not change the incoming degree of any vertex, this is the graph encoding of some valid assignment $T^+$ such that $w(G_{T^+}) > w(G_T)$. We can iterate this operation until there is no other assignment $T^*$ with larger weight, that is until we obtain an optimal assignment.
 \subsubsection{Minimizing the node discrepancy}
 We will follow an approach similar to the one where we minimize the zone discrepancy. Here we will directly obtain a node assignment from a graph encoding.
 Let $G_T=(X,E_T)$ be the directed weighted graph with vertices $(\mathbf{x}_i)_{1\le i\le N}$, $(\mathbf{y}_{z,i})_{z\in Z, 1\le i\le N}$ and $(\mathbf{u}_v)_{v\in V}$. For any $1\le i\le N$ and $z\in Z$, $E_T$ contains  the arc:
 \begin{itemize}
 	\item $(\mathbf{x}_i, \mathbf{y}_{z,i}, 0)$, if $z$ appears in $T_i$;
 	\item $(\mathbf{y}_{z,i}, \mathbf{x}_i, 0)$, if $z$ does not appear in $T_i$.
 \end{itemize}
 For any $1\le i\le N$ and $v\in V$, $E_T$ contains  the arc:
 \begin{itemize}
 	\item $(\mathbf{y}_{z_v,i}, \mathbf{u}_v, +1)$, if $v$ appears in $T_i'$ and $T_i$;
 	\item $(\mathbf{y}_{z_v,i}, \mathbf{u}_v, -1)$, if $v$ appears in $T_i$ but not in $T'_i$;
 	\item $(\mathbf{u}_v, \mathbf{y}_{z_v,i}, -1)$, if $v$ appears in $T'_i$ but not in $T_i$;
 	\item $(\mathbf{u}_v, \mathbf{y}_{z_v,i}, +1)$, if $v$ does not appear in $T'_i$ nor in $T_i$.
 \end{itemize}
 Every vertex $\mathbb{x}_i$ has outgoing degree 3, every vertex $\mathbf{y}_{z,v}$ has outgoing degree 1, and every vertex $\mathbf{u}_v$ has incoming degree $n_v$. 
 Remark that any graph respecting these degree constraints is the encoding of a valid assignment with utilizations $(n_v)_{v\in V}$, in particular no partition is stored in two nodes of the same zone.
 We define $w(G_T)$ similarly:
 \begin{align*}
 	w(G_T) := \sum_{e\in E_T} w(e) &= \#V \times N - 4\sum_{1\le i\le N} 3-\#(T_i\cap T'_i) \\
 	&= (\#V-12)N + 4Q_V.
 \end{align*}
 Exactly like in the previous section, the existence of an assignment with larger weight implies the existence of a negatively weighted cycle in $G_T$. Reversing this cycle gives us the encoding of a valid assignment with a larger weight. Iterating this operation yields an optimal assignment.
 \subsubsection{Linear combination of both criteria}
 In the graph $G_T$ defined in the previous section, instead of having weights $0$ and $\pm 1$, we could be having weights $\pm\alpha$ between $\mathbf{x}$ and  $\mathbf{y}$ vertices, and weights $\pm\beta$ between $\mathbf{y}$ and  $\mathbf{u}$ vertices, for some $\alpha,\beta>0$ (we have positive weight if the assignment corresponds to $T'$ and negative otherwise). Then
 \begin{align*}
 	w(G_T) &= \sum_{e\in E_T} w(e) = 
 	\alpha \big( (\#Z-12)N + 4 Q_Z\big) + 
 	\beta \big( (\#V-12)N + 4 Q_V\big) \\
 	&= \mathrm{const}+ 4(\alpha Q_Z + \beta Q_V).
 \end{align*}
 So maximizing the weight of such graph encoding would be equivalent to maximizing a linear combination of $Q_Z$ and $Q_V$.
 \subsection{Algorithm}
 We give a high level description of the algorithm to compute an optimal 3-strict assignment. The operations appearing at lines 1,2,4 are respectively described by Algorithms \ref{alg:util},\ref{alg:opt} and \ref{alg:mini}.
 \begin{algorithm}[H]
 	\caption{Optimal 3-strict assignment}
 	\label{alg:total}
 	\begin{algorithmic}[1]
 	\Function{Optimal 3-strict assignment}{$N$, $(c_v)_{v\in V}$, $T'$}
 		\State $(n_v)_{v\in V} \leftarrow$ \Call{Compute optimal utilization}{$N$, $(c_v)_{v\in V}$}
 		\State $(T_i)_{1\le i\le N} \leftarrow$ \Call{Compute candidate assignment}{$N$, $(n_v)_{v\in V}$}
 		\If {there was a previous assignment $T'$}
 			\State $T \leftarrow$ \Call{Minimization of transfers}{$(T_i)_{1\le i\le N}$, $(T'_i)_{1\le i\le N}$}
 		\EndIf
 		\State \Return $T$.
 	\EndFunction
 	\end{algorithmic}
 \end{algorithm}
 We give some considerations of worst case complexity for these algorithms. In the following, we assume $N>\#V>\#Z$. The complexity of Algorithm \ref{alg:total} is $O(N^3\# Z)$ if we assume \eqref{hyp:A} and $O(N^3 \#Z \#V)$ if we assume \eqref{hyp:B}.
 Algorithm \ref{alg:util} can be implemented with complexity $O(\#V^2)$. The complexity of the function call at line \ref{lin:subutil} is $O(\#V)$. The difference between the sum of the subutilizations and $3N$ is at most the sum of the rounding errors when computing the $\hat{n}_v$. Hence it is bounded by $\#V$ and the loop at line \ref{lin:loopsub} is iterated at most $\#V$ times. Finding the minimizing $v$ at line \ref{lin:findmin} takes $O(\#V)$ operations (naively, we could also use a heap).
 Algorithm \ref{alg:opt} can be implemented with complexity $O(N^3\times \#Z)$. The flow graph has $O(N+\#Z)$ vertices and $O(N\times \#Z)$ edges. Dinic's algorithm has complexity $O(\#\mathrm{Vertices}^2\#\mathrm{Edges})$ hence in our case it is $O(N^3\times \#Z)$.
 Algorithm \ref{alg:mini} can be implented with complexity $O(N^3\# Z)$ under \eqref{hyp:A} and $O(N^3 \#Z \#V)$ under \eqref{hyp:B}.
 The graph $G_T$ has $O(N)$ vertices and $O(N\times \#Z)$ edges under assumption \eqref{hyp:A} and respectively $O(N\times \#Z)$ vertices and $O(N\times \#V)$ edges under assumption \eqref{hyp:B}. The loop at line \ref{lin:repeat} is iterated at most $N$ times since the distance between $T$ and $T'$ decreases at every iteration. Bellman-Ford algorithm has complexity $O(\#\mathrm{Vertices}\#\mathrm{Edges})$, which in our case amounts to $O(N^2\# Z)$ under \eqref{hyp:A} and $O(N^2 \#Z \#V)$ under \eqref{hyp:B}.
 \begin{algorithm}
 	\caption{Computation of the optimal utilization}
 	\label{alg:util}
 	\begin{algorithmic}[1]
 \Function{Compute optimal utilization}{$N$, $(c_v)_{v\in V}$}
 	\State $(\hat{n}_v)_{v\in V} \leftarrow $ \Call{Compute subutilization}{$N$, $(c_v)_{v\in V}$} \label{lin:subutil}
 	\While{$\sum_{v\in V} \hat{n}_v < 3N$} \label{lin:loopsub}
 	\State Pick $v\in V$ minimizing $\frac{c_v}{\hat{n}_v+1}$ and such that
 		$\sum_{v'\in z_v} \hat{n}_{v'} < N$ \label{lin:findmin}
 		\State $\hat{n}_v \leftarrow \hat{n}_v+1$
 	\EndWhile
 	\State \Return $(\hat{n}_v)_{v\in V}$
 \EndFunction
 \State
 \Function{Compute subutilization}{$N$, $(c_v)_{v\in V}$}
 		\State $R \leftarrow 3$
 \For{$v\in V$}
 \State $\hat{n}_v \leftarrow \mathrm{unset}$
 \EndFor
 \For{$z\in Z$}
 \State $c_z \leftarrow \sum_{v\in z} c_v$
 \EndFor
 \State $C \leftarrow \sum_{z\in Z} c_z$
 \While{$\exists z \in Z$ such that $R\times c_{z} > C$}
 \For{$v\in z$}
 \State $\hat{n}_v \leftarrow \left\lfloor \frac{c_v}{c_z} N \right\rfloor$
 \EndFor
 \State $C \leftarrow C-c_z$
 \State $R\leftarrow R-1$
 \EndWhile
 \For{$v\in V$}
 \If{$\hat{n}_v = \mathrm{unset}$}
 \State $\hat{n}_v \leftarrow \left\lfloor \frac{Rc_v}{C} N \right\rfloor$
 \EndIf
 \EndFor
 \State \Return $(\hat{n}_v)_{v\in V}$
 \EndFunction
 	\end{algorithmic}
 \end{algorithm}
 \begin{algorithm}
 	\caption{Computation of a candidate assignment}
 	\label{alg:opt}
 	\begin{algorithmic}[1]
 		\Function{Compute candidate assignment}{$N$, $(n_v)_{v\in V}$}
 		\State Compute the flow graph $G$
 		\State Compute the maximal flow $f$ using Dinic's algorithm with randomized neighbours enumeration
 		\State Construct the assignment $(T_i)_{1\le i\le N}$ from $f$
 		\State \Return $(T_i)_{1\le i\le N}$
 		\EndFunction
 	\end{algorithmic}
 \end{algorithm}
 \begin{algorithm}
 	\caption{Minimization of the number of transfers}
 	\label{alg:mini}
 	\begin{algorithmic}[1]
 		\Function{Minimization of transfers}{$(T_i)_{1\le i\le N}$, $(T'_i)_{1\le i\le N}$}
 		\State Construct the graph encoding $G_T$
 		\Repeat \label{lin:repeat}
 		\State Find a negative cycle $\gamma$ using Bellman-Ford algorithm on $G_T$
 		\State Reverse the orientations and weights of edges in $\gamma$
 		\Until{no negative cycle is found}
 		\State Update $(T_i)_{1\le i\le N}$ from $G_T$
 		\State \Return $(T_i)_{1\le i\le N}$
 		\EndFunction
 	\end{algorithmic}
 \end{algorithm}
 \newpage
 \section{Computation of a 3-non-strict assignment}
 \subsection{Choices of optimality}
 In this mode, we primarily want to store every partition on three nodes, and only secondarily try to spread the nodes among different zone. So we make the choice of not taking the zone repartition in the criterion of optimality.
 We try to maximize $s^*$ defined in \eqref{eq:optimal}. So we can compute the optimal utilizations $(n_v)_{v\in V}$ with the only constraint that $n_v \le N$ for every node $v$. As in the previous section, we start with a sub-utilization proportional to $c_v$ (and capped at $N$), and we iteratively increase the $\hat{n}_v$ that is less than $N$ and maximizes the quantity $c_v/(\hat{n}_v+1)$, until the total sum is $3N$.
 \subsection{Computation of a candidate assignment}
 To compute a candidate assignment (that does not optimize zone spreading nor distance to a previous assignment yet), we can use the folowing flow problem.
 Define the oriented weighted graph $(X,E)$. The set of vertices $X$ contains the source $\mathbf{s}$, the sink $\mathbf{t}$, vertices 
 $\mathbf{x}_p, \mathbf{u}^+_p, \mathbf{u}^-_p$ for every partition $p$, vertices $\mathbf{y}_{p,z}$ for every partition $p$ and zone $z$, and vertices $\mathbf{z}_v$ for every node $v$. 
 The set of edges is composed of the following arcs:
 \begin{itemize}
 	\item ($\mathbf{s}$,$\mathbf{x}_p$, 3) for every partition $p$;
 	\item ($\mathbf{x}_p$,$\mathbf{u}^+_p$, 3) for every partition $p$;
 	\item ($\mathbf{x}_p$,$\mathbf{u}^-_p$, 2) for every partition $p$;
 	\item ($\mathbf{u}^+_p$,$\mathbf{y}_{p,z}$, 1) for every partition $p$ and zone $z$;
 	\item ($\mathbf{u}^-_p$,$\mathbf{y}_{p,z}$, 2) for every partition $p$ and zone $z$;
 	\item ($\mathbf{y}_{p,z}$,$\mathbf{z}_v$, 1) for every partition $p$, zone $z$ and node $v\in z$;
 	\item ($\mathbf{z}_v$, $\mathbf{t}$, $n_v$) for every node $v$;
 \end{itemize}
 One can check that any maximal flow in this graph corresponds to an assignment of partitions to nodes. In such a flow, all the arcs from $\mathbf{s}$ and to $\mathbf{t}$ are saturated. The arc from $\mathbf{y}_{p,z}$ to $\mathbf{z}_v$ is saturated if and only if $p$ is associated to~$v$. 
 Finally the flow from $\mathbf{x}_p$ to $\mathbf{y}_{p,z}$ can go either through $\mathbf{u}^+_p$ or $\mathbf{u}^-_p$.
 \subsection{Maximal spread and minimal transfers}
 Notice that if the arc $\mathbf{u}_p^+\mathbf{y}_{p,z}$ is not saturated but there is some flow in $\mathbf{u}_p^-\mathbf{y}_{p,z}$, then it is possible to transfer a unit of flow from the path  $\mathbf{x}_p\mathbf{u}_p^-\mathbf{y}_{p,z}$ to the path $\mathbf{x}_p\mathbf{u}_p^+\mathbf{y}_{p,z}$. So we can always find an equivalent maximal flow $f^*$ that uses the path through $\mathbf{u}_p^-$ only if the path through $\mathbf{u}_p^+$ is saturated.
 We will use this fact to consider the amount of flow going through the vertices $\mathbf{u}^+$ as a measure of how well the partitions are spread over nodes belonging to different zones. If the partition $p$ is associated to 3 different zones, then a flow of 3 will cross $\mathbf{u}_p^+$ in $f^*$ (i.e. a flow of 0 will cross $\mathbf{u}_p^+$). If $p$ is associated to two zones, a flow of $2$ will cross $\mathbf{u}_p^+$. If $p$ is associated to a single zone, a flow of $1$ will cross $\mathbf{u}_p^+$.
 Let $N_1, N_2, N_3$ be the number of partitions associated to respectively 1,2 and 3 distinct zones. We will optimize a linear combination of these variables using the discovery of positively weighted circuits in a graph.
 At the same step, we will also optimize the distance to a previous assignment $T'$. Let $\alpha> \beta> \gamma \ge 0$ be three parameters.
 Given the flow $f$, let $G_f=(X',E_f)$ be the multi-graph where $X' = X\setminus\{\mathbf{s},\mathbf{t}\}$. The set $E_f$ is composed of the arcs:
 \begin{itemize}
 \item As many arcs from $(\mathbf{x}_p, \mathbf{u}^+_p,\alpha), (\mathbf{x}_p, \mathbf{u}^+_p,\beta), (\mathbf{x}_p, \mathbf{u}^+_p,\gamma)$ (selected in this order) as there is flow crossing $\mathbf{u}^+_p$ in $f$;
 \item As many arcs from $(\mathbf{u}^+_p, \mathbf{x}_p,-\gamma), (\mathbf{u}^+_p, \mathbf{x}_p,-\beta), (\mathbf{u}^+_p, \mathbf{x}_p,-\alpha)$ (selected in this order) as there is flow crossing $\mathbf{u}^-_p$ in $f$;
 \item  As many copies of $(\mathbf{x}_p, \mathbf{u}^-_p,0)$ as there is flow through $\mathbf{u}^-_p$;
 \item  As many copies of $(\mathbf{u}^-_p,\mathbf{x}_p,0)$ so that the number of arcs between these two vertices is 2;
 \item $(\mathbf{u}^+_p,\mathbf{y}_{p,z}, 0)$ if the flow between these vertices is 1, and the opposite arc otherwise;
 \item as many copies of $(\mathbf{u}^-_p,\mathbf{y}_{p,z}, 0)$ as the flow between these vertices, and as many copies of the opposite arc as 2~$-$~the flow;
 \item $(\mathbf{y}_{p,z},\mathbf{z}_v, \pm1)$ if it is saturated in $f$, with $+1$ if $v\in T'_p$ and $-1$ otherwise;
 \item $(\mathbf{z}_v,\mathbf{y}_{p,z}, \pm1)$ if it is not saturated in $f$, with $+1$ if $v\notin T'_p$ and $-1$ otherwise.
 \end{itemize}
 To summarize, arcs are oriented left to right if they correspond to a presence of flow in $f$, and right to left if they correspond to an absence of flow. They are positively weighted if we want them to stay at their current state, and negatively if we want them to switch. Let us compute the weight of such graph.
 \begin{multline*}
 	w(G_f)  = \sum_{e\in E_f} w(e_f)  \\
 	= 
 	(\alpha - \beta -\gamma) N_1 + (\alpha +\beta - \gamma) N_2 + (\alpha+\beta+\gamma) N_3 
 	\\ + 
 	\#V\times N - 4 \sum_p 3-\#(T_p\cap T'_p) \\ 
 	=(\#V-12+\alpha-\beta-\gamma)\times N + 4Q_V + 2\beta N_2 + 2(\beta+\gamma) N_3 \\
 \end{multline*}
 As for the mode 3-strict, one can check that the difference of two such graphs corresponding to the same $(n_v)$ is always eulerian. Hence we can navigate in this class with the same greedy algorithm that discovers positive cycles and flips them.
 The function that we optimize is 
 $$
 2Q_V +  \beta N_2 + (\beta+\gamma) N_3.
 $$
 The choice of parameters $\beta$ and $\gamma$ should be lead by the following question: For $\beta$, where to put the tradeoff between zone dispersion and distance to the previous configuration? For $\gamma$, do we prefer to have more partitions spread between 2 zones, or have less between at least 2 zones but more between 3 zones.
 The quantity $Q_V$ varies between $0$ and $3N$, it should be of order $N$. The quantity $N_2+N_3$ should also be of order $N$ (it is exactly $N$ in the strict mode). So the two terms of the function are comparable. 
 \bibliography{optimal_layout} 
 \bibliographystyle{ieeetr}
 \end{document}
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--- a/doc/talks/2023-01-18-tocatta/abstract.md
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 ### (fr) Garage, un système de stockage de données géo-distribué léger et robuste
 Garage est un système de stockage de données léger, géo-distribué, qui
 implémente le protocole de stockage S3 de Amazon. Garage est destiné
 principalement à l'auto-hébergement sur du matériel courant d'occasion. À ce
 titre, il doit tolérer un grand nombre de pannes: coupures de courant, coupures
 de connexion Internet, pannes de machines, ... Il doit également être facile à
 déployer et à maintenir, afin de pouvoir être facilement utilisé par des
 amateurs ou des petites organisations.
 Cette présentation vous proposera un aperçu de Garage et du choix technique
 principal qui rend un système comme Garage possible: le refus d'utiliser des
 algorithmes de consensus, remplacés avantageusement par des méthodes à
 cohérence faible.  Notre modèle est fortement inspiré de la base de donnée
 Dynamo (DeCandia et al, 2007), et fait usage des types de données CRDT (Shapiro
 et al, 2011).  Nous exploreront comment ces méthodes s'appliquent à la
 construction de l'abstraction "stockage objet" dans un système distribué, et
 quelles autres abstractions peuvent ou ne peuvent pas être construites dans ce
 modèle.
 ### (en) Garage, a lightweight and robust geo-distributed data storage system
 Garage is a lightweight geo-distributed data store that implements the Amazon
 S3 object storage protocol.  Garage is meant primarily for self-hosting at home
 on second-hand commodity hardware, meaning it has to tolerate a wide variety of
 failure scenarios such as power cuts, Internet disconnections and machine
 crashes. It also has to be easy to deploy and maintain, so that hobbyists and
 small organizations can use it without trouble. 
 This talk will present Garage and the key technical choice that made Garage
 possible: refusing to use consensus algorithms and using instead weak
 consistency methods, with a model that is loosely based on that of the Dynamo
 database (DeCandia et al, 2007) and that makes heavy use of conflict-free
 replicated data types (Shapiro et al, 2011).  We will explore how these methods
 are suited to building the "object store" abstraction in a distributed system,
 and what other abstractions are possible or impossible to build in this model.
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--- a/Show more
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