doc: add presentation at seed webinar 2024-01-12 #693

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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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\title{Garage}
\subtitle{a lightweight and robust geo-distributed data storage system}
\author{Alex Auvolat, Deuxfleurs}
\date{SEED webinar, 2024-01-12}
\begin{document}
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% {\large\bf Alex Auvolat, Deuxfleurs Association}
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% \url{https://garagehq.deuxfleurs.fr/}
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%\frametitle{Who I am}
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\textbf{Alex Auvolat}\\
Member of Deuxfleurs, lead developer of Garage
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~
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\vspace{.5em}
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\\\textbf{Garage}\\
A self-hosted alternative to S3 for object storage
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~
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\vspace{2em}
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\textbf{Deuxfleurs}\\
A non-profit self-hosting collective,\\
member of the CHATONS network
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\begin{frame}
\frametitle{Stable vs Resilient}
\hspace{1em}
\begin{minipage}{7cm}
\textbf{Building a "stable" system:}
\vspace{1em}
Enterprise-grade systems typically employ:
\vspace{1em}
\begin{itemize}
\item RAID
\item Redundant power grid + UPS
\item Redundant Internet connections
\item Low-latency links
\item ...
\end{itemize}
\vspace{1em}
$\to$ costly, only worth at DC scale\\
$\to$ still risk of DC-level incident...
\end{minipage}
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\textbf{Building a \underline{resilient} system:}
\vspace{1em}
An alternative, cheaper way:
\vspace{1em}
\begin{itemize}
\item Commodity hardware \\(e.g. old desktop PCs)
\vspace{.5em}
\item Commodity Internet \\(e.g. FTTB, FTTH) and power grid
\vspace{.5em}
\item \textbf{Geographical redundancy} \\(multi-site replication)
\end{itemize}
\vspace{1.5em}
\end{minipage}
\hspace{1em}
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\begin{frame}
\frametitle{Example: our infrastructure at Deuxfleurs}
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\includegraphics[width=.8\linewidth]{assets/neptune.jpg}
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\only<3>{
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\includegraphics[width=.8\linewidth]{assets/inframap_jdll2023.pdf}
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}
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\begin{frame}
\frametitle{Object storage: simpler than file systems}
\begin{minipage}{6cm}
Only two operations:
\vspace{1em}
\begin{itemize}
\item Put an object at a key
\vspace{1em}
\item Retrieve an object from its key
\end{itemize}
\vspace{1em}
{\footnotesize (and a few others)}
\vspace{1em}
Sufficient for many applications!
\end{minipage}
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\begin{center}
\vspace{2em}
\includegraphics[height=6em]{../2020-12-02_wide-team/img/Amazon-S3.jpg}
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\includegraphics[height=5em]{assets/minio.png}
\vspace{2em}
\includegraphics[height=6em]{../../logo/garage_hires_crop.png}
\end{center}
\vspace{1em}
\end{minipage}
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\begin{frame}
\frametitle{The data model of object storage}
Object storage is basically a key-value store:
\vspace{1em}
\begin{center}
\begin{tabular}{|l|p{8cm}|}
\hline
\textbf{Key: file path + name} & \textbf{Value: file data + metadata} \\
\hline
\hline
\texttt{index.html} &
\texttt{Content-Type: text/html; charset=utf-8} \newline
\texttt{Content-Length: 24929} \newline
\texttt{<binary blob>} \\
\hline
\texttt{img/logo.svg} &
\texttt{Content-Type: text/svg+xml} \newline
\texttt{Content-Length: 13429} \newline
\texttt{<binary blob>} \\
\hline
\texttt{download/index.html} &
\texttt{Content-Type: text/html; charset=utf-8} \newline
\texttt{Content-Length: 26563} \newline
\texttt{<binary blob>} \\
\hline
\end{tabular}
\end{center}
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\begin{frame}
\frametitle{Implementation: consensus vs weak consistency}
\hspace{1em}
\begin{minipage}{7cm}
\textbf{Consensus-based systems:}
\vspace{1em}
\begin{itemize}
\item \textbf{Leader-based:} a leader is elected to coordinate
all reads and writes
\vspace{1em}
\item Allows for \textbf{sequential reasoning}:
program as if running on a single machine
\vspace{1em}
\item Serializability is one of the \\
\textbf{strongest consistency guarantees}
\vspace{1em}
\item \textbf{Costly}, the leader is a bottleneck;
leader elections on failure take time
\end{itemize}
\end{minipage}
\hfill
\begin{minipage}{7cm} \visible<2->{
\textbf{Weakly consistent systems:}
\vspace{1em}
\begin{itemize}
\item \textbf{Nodes are equivalent}, any node
can originate a read or write operation
\vspace{1em}
\item \textbf{Operations must be independent},
conflicts are resolved after the fact
\vspace{1em}
\item Strongest achievable consistency:\\
\textbf{read-after-write consistency}\\(using quorums)
\vspace{1em}
\item \textbf{Fast}, no single bottleneck;\\
works transparently with offline nodes
\end{itemize}
} \end{minipage}
\hspace{1em}
\end{frame}
\begin{frame}
\frametitle{Why avoid consensus?}
Consensus can be implemented reasonably well in practice, so why avoid it?
\vspace{2em}
\begin{itemize}
\item \textbf{Software complexity:} RAFT and PAXOS are complex beasts;\\
harder to prove, harder to reason about
\vspace{1.5em}
\item \textbf{Performance issues:}
\vspace{1em}
\begin{itemize}
\item Taking a decision may take an \textbf{arbitrary number of steps} (in adverse scenarios)
\vspace{1em}
\item The leader is a \textbf{bottleneck} for all requests;\\
even in leaderless approaches, \textbf{all nodes must process all operations in order}
\vspace{1em}
\item Particularly \textbf{sensitive to higher latency} between nodes
\end{itemize}
\end{itemize}
\end{frame}
\begin{frame}
\frametitle{Objective: the right level of consistency for Garage}
\underline{Constraints:} slow network (geographical distance), node unavailability/crashes\\
\underline{Objective:} maximize availability, maintain an \emph{appropriate level of consistency}\\
\vspace{1em}
\begin{enumerate}
\item<2-> \textbf{Weak consistency for most things}\\
\vspace{1em}
\underline{Example:} \texttt{PutObject}\\
\vspace{.5em}
If two clients write the same
object at the same time, one of the two is implicitly overwritten.
No need to coordinate, use a \emph{last-writer-wins register}.
\vspace{1em}
\item<3-> \textbf{Stronger consistency only when necessary}\\
\vspace{1em}
\underline{Example:} \texttt{CreateBucket}\\
\vspace{.5em}
A bucket is a reserved name in a shared namespace,
two clients should be prevented from both creating the same bucket
(\emph{mutual exclusion}).
\end{enumerate}
\end{frame}
\begin{frame}
\frametitle{The possibility of \emph{leaderless consensus}}
Currently, Garage \emph{only has weak consistency}. Is fast, but \texttt{CreateBucket} is broken!
\visible<2->{
\vspace{1em}
Leaderless consensus (Antoniadis et al., 2023) alleviates issues with RAFT and PAXOS:
\vspace{1em}
\begin{itemize}
\item \textbf{No leader.} All nodes participate equally at each time step,
and different nodes can be unavailable at different times without issues.
\\ \vspace{.5em} $\to$ better tolerance to the high latency (remove bottleneck issue)
\\ $\to$ tolerates crash transparently
\vspace{1em}
\item \textbf{Simpler formalization.} The algorithm is very simple to express and to analyze in mathematical terms.
\end{itemize}
}
\visible<3->{
\vspace{1em}
One of the possible subjects for this PhD:
\\$\to$ \emph{integration of leaderless consensus in Garage} + testing + perf eval, etc.
}
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\begin{center}
\includegraphics[width=.25\linewidth]{../../logo/garage_hires.png}\\
\vspace{-1em}
\url{https://garagehq.deuxfleurs.fr/}\\
\url{mailto:garagehq@deuxfleurs.fr}\\
\texttt{\#garage:deuxfleurs.fr} on Matrix
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\includegraphics[width=.13\linewidth]{assets/AGPLv3_Logo.png}
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\end{document}
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