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Diffstat (limited to 'src')
| -rw-r--r-- | src/Technique/Développement/Garage/Internals.md | 156 | ||||
| -rw-r--r-- | src/Technique/Développement/Garage/Quickstart.md | 140 | ||||
| -rw-r--r-- | src/Technique/Développement/Garage/Related Work.md | 38 | ||||
| -rw-r--r-- | src/Technique/Développement/Garage/index.md | 8 |
4 files changed, 4 insertions, 338 deletions
diff --git a/src/Technique/Développement/Garage/Internals.md b/src/Technique/Développement/Garage/Internals.md deleted file mode 100644 index dd98246..0000000 --- a/src/Technique/Développement/Garage/Internals.md +++ /dev/null @@ -1,156 +0,0 @@ -#### Modules - -- `membership/`: configuration, membership management (gossip of node's presence and status), ring generation --> what about Serf (used by Consul/Nomad) : https://www.serf.io/? Seems a huge library with many features so maybe overkill/hard to integrate -- `metadata/`: metadata management -- `blocks/`: block management, writing, GC and rebalancing -- `internal/`: server to server communication (HTTP server and client that reuses connections, TLS if we want, etc) -- `api/`: S3 API -- `web/`: web management interface - -#### Metadata tables - -**Objects:** - -- *Hash key:* Bucket name (string) -- *Sort key:* Object key (string) -- *Sort key:* Version timestamp (int) -- *Sort key:* Version UUID (string) -- Complete: bool -- Inline: bool, true for objects < threshold (say 1024) -- Object size (int) -- Mime type (string) -- Data for inlined objects (blob) -- Hash of first block otherwise (string) - -*Having only a hash key on the bucket name will lead to storing all file entries of this table for a specific bucket on a single node. At the same time, it is the only way I see to rapidly being able to list all bucket entries...* - -**Blocks:** - -- *Hash key:* Version UUID (string) -- *Sort key:* Offset of block in total file (int) -- Hash of data block (string) - -A version is defined by the existence of at least one entry in the blocks table for a certain version UUID. -We must keep the following invariant: if a version exists in the blocks table, it has to be referenced in the objects table. -We explicitly manage concurrent versions of an object: the version timestamp and version UUID columns are index columns, thus we may have several concurrent versions of an object. -Important: before deleting an older version from the objects table, we must make sure that we did a successfull delete of the blocks of that version from the blocks table. - -Thus, the workflow for reading an object is as follows: - -1. Check permissions (LDAP) -2. Read entry in object table. If data is inline, we have its data, stop here. - -> if several versions, take newest one and launch deletion of old ones in background -3. Read first block from cluster. If size <= 1 block, stop here. -4. Simultaneously with previous step, if size > 1 block: query the Blocks table for the IDs of the next blocks -5. Read subsequent blocks from cluster - -Workflow for PUT: - -1. Check write permission (LDAP) -2. Select a new version UUID -3. Write a preliminary entry for the new version in the objects table with complete = false -4. Send blocks to cluster and write entries in the blocks table -5. Update the version with complete = true and all of the accurate information (size, etc) -6. Return success to the user -7. Launch a background job to check and delete older versions - -Workflow for DELETE: - -1. Check write permission (LDAP) -2. Get current version (or versions) in object table -3. Do the deletion of those versions NOT IN A BACKGROUND JOB THIS TIME -4. Return succes to the user if we were able to delete blocks from the blocks table and entries from the object table - -To delete a version: - -1. List the blocks from Cassandra -2. For each block, delete it from cluster. Don't care if some deletions fail, we can do GC. -3. Delete all of the blocks from the blocks table -4. Finally, delete the version from the objects table - -Known issue: if someone is reading from a version that we want to delete and the object is big, the read might be interrupted. I think it is ok to leave it like this, we just cut the connection if data disappears during a read. - -("Soit P un problème, on s'en fout est une solution à ce problème") - -#### Block storage on disk - -**Blocks themselves:** - -- file path = /blobs/(first 3 hex digits of hash)/(rest of hash) - -**Reverse index for GC & other block-level metadata:** - -- file path = /meta/(first 3 hex digits of hash)/(rest of hash) -- map block hash -> set of version UUIDs where it is referenced - -Usefull metadata: - -- list of versions that reference this block in the Casandra table, so that we can do GC by checking in Cassandra that the lines still exist -- list of other nodes that we know have acknowledged a write of this block, usefull in the rebalancing algorithm - -Write strategy: have a single thread that does all write IO so that it is serialized (or have several threads that manage independent parts of the hash space). When writing a blob, write it to a temporary file, close, then rename so that a concurrent read gets a consistent result (either not found or found with whole content). - -Read strategy: the only read operation is get(hash) that returns either the data or not found (can do a corruption check as well and return corrupted state if it is the case). Can be done concurrently with writes. - -**Internal API:** - -- get(block hash) -> ok+data/not found/corrupted -- put(block hash & data, version uuid + offset) -> ok/error -- put with no data(block hash, version uuid + offset) -> ok/not found plz send data/error -- delete(block hash, version uuid + offset) -> ok/error - -GC: when last ref is deleted, delete block. -Long GC procedure: check in Cassandra that version UUIDs still exist and references this block. - -Rebalancing: takes as argument the list of newly added nodes. - -- List all blocks that we have. For each block: -- If it hits a newly introduced node, send it to them. - Use put with no data first to check if it has to be sent to them already or not. - Use a random listing order to avoid race conditions (they do no harm but we might have two nodes sending the same thing at the same time thus wasting time). -- If it doesn't hit us anymore, delete it and its reference list. - -Only one balancing can be running at a same time. It can be restarted at the beginning with new parameters. - -#### Membership management - -Two sets of nodes: - -- set of nodes from which a ping was recently received, with status: number of stored blocks, request counters, error counters, GC%, rebalancing% - (eviction from this set after say 30 seconds without ping) -- set of nodes that are part of the system, explicitly modified by the operator using the web UI (persisted to disk), - is a CRDT using a version number for the value of the whole set - -Thus, three states for nodes: - -- healthy: in both sets -- missing: not pingable but part of desired cluster -- unused/draining: currently present but not part of the desired cluster, empty = if contains nothing, draining = if still contains some blocks - -Membership messages between nodes: - -- ping with current state + hash of current membership info -> reply with same info -- send&get back membership info (the ids of nodes that are in the two sets): used when no local membership change in a long time and membership info hash discrepancy detected with first message (passive membership fixing with full CRDT gossip) -- inform of newly pingable node(s) -> no result, when receive new info repeat to all (reliable broadcast) -- inform of operator membership change -> no result, when receive new info repeat to all (reliable broadcast) - -Ring: generated from the desired set of nodes, however when doing read/writes on the ring, skip nodes that are known to be not pingable. -The tokens are generated in a deterministic fashion from node IDs (hash of node id + token number from 1 to K). -Number K of tokens per node: decided by the operator & stored in the operator's list of nodes CRDT. Default value proposal: with node status information also broadcast disk total size and free space, and propose a default number of tokens equal to 80%Free space / 10Gb. (this is all user interface) - - -#### Constants - -- Block size: around 1MB ? --> Exoscale use 16MB chunks -- Number of tokens in the hash ring: one every 10Gb of allocated storage -- Threshold for storing data directly in Cassandra objects table: 1kb bytes (maybe up to 4kb?) -- Ping timeout (time after which a node is registered as unresponsive/missing): 30 seconds -- Ping interval: 10 seconds -- ?? - -#### Links - -- CDC: <https://www.usenix.org/system/files/conference/atc16/atc16-paper-xia.pdf> -- Erasure coding: <http://web.eecs.utk.edu/~jplank/plank/papers/CS-08-627.html> -- [Openstack Storage Concepts](https://docs.openstack.org/arch-design/design-storage/design-storage-concepts.html) -- [RADOS](https://ceph.com/wp-content/uploads/2016/08/weil-rados-pdsw07.pdf) diff --git a/src/Technique/Développement/Garage/Quickstart.md b/src/Technique/Développement/Garage/Quickstart.md deleted file mode 100644 index 6d0993a..0000000 --- a/src/Technique/Développement/Garage/Quickstart.md +++ /dev/null @@ -1,140 +0,0 @@ -# Quickstart on an existing deployment - -First, chances are that your garage deployment is secured by TLS. -All your commands must be prefixed with their certificates. -I will define an alias once and for all to ease future commands. -Please adapt the path of the binary and certificates to your installation! - -``` -alias grg="/garage/garage --ca-cert /secrets/garage-ca.crt --client-cert /secrets/garage.crt --client-key /secrets/garage.key" -``` - -Now we can check that everything is going well by checking our cluster status: - -``` -grg status -``` - -Don't forget that `help` command and `--help` subcommands can help you anywhere, the CLI tool is self-documented! Two examples: - -``` -grg help -grg bucket allow --help -``` - -Fine, now let's create a bucket (we imagine that you want to deploy nextcloud): - -``` -grg bucket create nextcloud-bucket -``` - -Check that everything went well: - -``` -grg bucket list -grg bucket info nextcloud-bucket -``` - -Now we will generate an API key to access this bucket. -Note that API keys are independent of buckets: one key can access multiple buckets, multiple keys can access one bucket. - -Now, let's start by creating a key only for our PHP application: - -``` -grg key new --name nextcloud-app-key -``` - -You will have the following output (this one is fake, `key_id` and `secret_key` were generated with the openssl CLI tool): - -``` -Key { key_id: "GK3515373e4c851ebaad366558", secret_key: "7d37d093435a41f2aab8f13c19ba067d9776c90215f56614adad6ece597dbb34", name: "nextcloud-app-key", name_timestamp: 1603280506694, deleted: false, authorized_buckets: [] } -``` - -Check that everything works as intended (be careful, info works only with your key identifier and not with its friendly name!): - -``` -grg key list -grg key info GK3515373e4c851ebaad366558 -``` - -Now that we have a bucket and a key, we need to give permissions to the key on the bucket! - -``` -grg bucket allow --read --write nextcloud-bucket --key GK3515373e4c851ebaad366558 -``` - -You can check at any times allowed keys on your bucket with: - -``` -grg bucket info nextcloud-bucket -``` - -Now, let's move to the S3 API! -We will use the `s3cmd` CLI tool. -You can install it via your favorite package manager. -Otherwise, check [their website](https://s3tools.org/s3cmd) - -We will configure `s3cmd` with its interactive configuration tool, be careful not all endpoints are implemented! -Especially, the test run at the end does not work (yet). - -``` -$ s3cmd --configure - -Enter new values or accept defaults in brackets with Enter. -Refer to user manual for detailed description of all options. - -Access key and Secret key are your identifiers for Amazon S3. Leave them empty for using the env variables. -Access Key: GK3515373e4c851ebaad366558 -Secret Key: 7d37d093435a41f2aab8f13c19ba067d9776c90215f56614adad6ece597dbb34 -Default Region [US]: garage - -Use "s3.amazonaws.com" for S3 Endpoint and not modify it to the target Amazon S3. -S3 Endpoint [s3.amazonaws.com]: garage.deuxfleurs.fr - -Use "%(bucket)s.s3.amazonaws.com" to the target Amazon S3. "%(bucket)s" and "%(location)s" vars can be used -if the target S3 system supports dns based buckets. -DNS-style bucket+hostname:port template for accessing a bucket [%(bucket)s.s3.amazonaws.com]: garage.deuxfleurs.fr - -Encryption password is used to protect your files from reading -by unauthorized persons while in transfer to S3 -Encryption password: -Path to GPG program [/usr/bin/gpg]: - -When using secure HTTPS protocol all communication with Amazon S3 -servers is protected from 3rd party eavesdropping. This method is -slower than plain HTTP, and can only be proxied with Python 2.7 or newer -Use HTTPS protocol [Yes]: - -On some networks all internet access must go through a HTTP proxy. -Try setting it here if you can't connect to S3 directly -HTTP Proxy server name: - -New settings: - Access Key: GK3515373e4c851ebaad366558 - Secret Key: 7d37d093435a41f2aab8f13c19ba067d9776c90215f56614adad6ece597dbb34 - Default Region: garage - S3 Endpoint: garage.deuxfleurs.fr - DNS-style bucket+hostname:port template for accessing a bucket: garage.deuxfleurs.fr - Encryption password: - Path to GPG program: /usr/bin/gpg - Use HTTPS protocol: True - HTTP Proxy server name: - HTTP Proxy server port: 0 - -Test access with supplied credentials? [Y/n] n - -Save settings? [y/N] y -Configuration saved to '/home/quentin/.s3cfg' -``` - -Now, if everything works, the following commands should work: - -``` -echo hello world > hello.txt -s3cmd put hello.txt s3://nextcloud-bucket -s3cmd ls s3://nextcloud-bucket -s3cmd rm s3://nextcloud-bucket/hello.txt -``` - -That's all for now! - diff --git a/src/Technique/Développement/Garage/Related Work.md b/src/Technique/Développement/Garage/Related Work.md deleted file mode 100644 index c1a4eed..0000000 --- a/src/Technique/Développement/Garage/Related Work.md +++ /dev/null @@ -1,38 +0,0 @@ -## Context - -Data storage is critical: it can lead to data loss if done badly and/or on hardware failure. -Filesystems + RAID can help on a single machine but a machine failure can put the whole storage offline. -Moreover, it put a hard limit on scalability. Often this limit can be pushed back far away by buying expensive machines. -But here we consider non specialized off the shelf machines that can be as low powered and subject to failures as a raspberry pi. - -Distributed storage may help to solve both availability and scalability problems on these machines. -Many solutions were proposed, they can be categorized as block storage, file storage and object storage depending on the abstraction they provide. - -## Related work - -Block storage is the most low level one, it's like exposing your raw hard drive over the network. -It requires very low latencies and stable network, that are often dedicated. -However it provides disk devices that can be manipulated by the operating system with the less constraints: it can be partitioned with any filesystem, meaning that it supports even the most exotic features. -We can cite [iSCSI](https://en.wikipedia.org/wiki/ISCSI) or [Fibre Channel](https://en.wikipedia.org/wiki/Fibre_Channel). -Openstack Cinder proxy previous solution to provide an uniform API. - -File storage provides a higher abstraction, they are one filesystem among others, which means they don't necessarily have all the exotic features of every filesystem. -Often, they relax some POSIX constraints while many applications will still be compatible without any modification. -As an example, we are able to run MariaDB (very slowly) over GlusterFS... -We can also mention CephFS (read [RADOS](https://ceph.com/wp-content/uploads/2016/08/weil-rados-pdsw07.pdf) whitepaper), Lustre, LizardFS, MooseFS, etc. -OpenStack Manila proxy previous solutions to provide an uniform API. - -Finally object storages provide the highest level abstraction. -They are the testimony that the POSIX filesystem API is not adapted to distributed filesystems. -Especially, the strong concistency has been dropped in favor of eventual consistency which is way more convenient and powerful in presence of high latencies and unreliability. -We often read about S3 that pioneered the concept that it's a filesystem for the WAN. -Applications must be adapted to work for the desired object storage service. -Today, the S3 HTTP REST API acts as a standard in the industry. -However, Amazon S3 source code is not open but alternatives were proposed. -We identified Minio, Pithos, Swift and Ceph. -Minio/Ceph enforces a total order, so properties similar to a (relaxed) filesystem. -Swift and Pithos are probably the most similar to AWS S3 with their consistent hashing ring. -However Pithos is not maintained anymore. More precisely the company that published Pithos version 1 has developped a second version 2 but has not open sourced it. -Some tests conducted by the [ACIDES project](https://acides.org/) have shown that Openstack Swift consumes way more resources (CPU+RAM) that we can afford. Furthermore, people developing Swift have not designed their software for geo-distribution. - -There were many attempts in research too. I am only thinking to [LBFS](https://pdos.csail.mit.edu/papers/lbfs:sosp01/lbfs.pdf) that was used as a basis for Seafile. But none of them have been effectively implemented yet. diff --git a/src/Technique/Développement/Garage/index.md b/src/Technique/Développement/Garage/index.md index d710788..67a016d 100644 --- a/src/Technique/Développement/Garage/index.md +++ b/src/Technique/Développement/Garage/index.md @@ -16,10 +16,10 @@ Non-goals include: Currently, Garage is deployed on our cluster (this very website is hosted on garage!) but must be considered as a technical preview. -If you want to learn more about Garage, you can check our documentation: - - [Quickstart](/Technique/Développement/Garage/Quickstart.html), learn how to quickly interact with garage. - - [Related Work](/Technique/Développement/Garage/Related%20Work.html), understand why we decided to build a new software instead of using existing ones. - - [Internals](/Technique/Développement/Garage/Internals.html), contains a quick description of the data models that are used in Garage. +If you want to learn more about Garage, you can check our [documentation](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/branch/master/doc): + - [Quickstart](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/branch/master/doc/Internals.md), learn how to quickly interact with garage. + - [Related Work](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/branch/master/doc/Related%20Work.md), understand why we decided to build a new software instead of using existing ones. + - [Internals](https://git.deuxfleurs.fr/Deuxfleurs/garage/src/branch/master/doc/Internals.md), contains a quick description of the data models that are used in Garage. External links: - [Repository](https://git.deuxfleurs.fr/Deuxfleurs/garage/), Garage is a free software, developed on our own Gitea instance |