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97 lines
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ReStructuredText
97 lines
4 KiB
ReStructuredText
Scaling synapse via workers
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---------------------------
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Synapse has experimental support for splitting out functionality into
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multiple separate python processes, helping greatly with scalability. These
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processes are called 'workers', and are (eventually) intended to scale
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horizontally independently.
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All processes continue to share the same database instance, and as such, workers
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only work with postgres based synapse deployments (sharing a single sqlite
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across multiple processes is a recipe for disaster, plus you should be using
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postgres anyway if you care about scalability).
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The workers communicate with the master synapse process via a synapse-specific
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HTTP protocol called 'replication' - analogous to MySQL or Postgres style
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database replication; feeding a stream of relevant data to the workers so they
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can be kept in sync with the main synapse process and database state.
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To enable workers, you need to add a replication listener to the master synapse, e.g.::
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listeners:
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- port: 9092
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bind_address: '127.0.0.1'
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type: http
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tls: false
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x_forwarded: false
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resources:
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- names: [replication]
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compress: false
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Under **no circumstances** should this replication API listener be exposed to the
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public internet; it currently implements no authentication whatsoever and is
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unencrypted HTTP.
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You then create a set of configs for the various worker processes. These should be
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worker configuration files should be stored in a dedicated subdirectory, to allow
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synctl to manipulate them.
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The current available worker applications are:
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* synapse.app.pusher - handles sending push notifications to sygnal and email
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* synapse.app.synchrotron - handles /sync endpoints. can scales horizontally through multiple instances.
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* synapse.app.appservice - handles output traffic to Application Services
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* synapse.app.federation_reader - handles receiving federation traffic (including public_rooms API)
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* synapse.app.media_repository - handles the media repository.
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Each worker configuration file inherits the configuration of the main homeserver
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configuration file. You can then override configuration specific to that worker,
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e.g. the HTTP listener that it provides (if any); logging configuration; etc.
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You should minimise the number of overrides though to maintain a usable config.
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You must specify the type of worker application (worker_app) and the replication
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endpoint that it's talking to on the main synapse process (worker_replication_url).
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For instance::
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worker_app: synapse.app.synchrotron
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# The replication listener on the synapse to talk to.
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worker_replication_url: http://127.0.0.1:9092/_synapse/replication
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worker_listeners:
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- type: http
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port: 8083
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resources:
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- names:
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- client
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worker_daemonize: True
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worker_pid_file: /home/matrix/synapse/synchrotron.pid
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worker_log_config: /home/matrix/synapse/config/synchrotron_log_config.yaml
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...is a full configuration for a synchrotron worker instance, which will expose a
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plain HTTP /sync endpoint on port 8083 separately from the /sync endpoint provided
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by the main synapse.
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Obviously you should configure your loadbalancer to route the /sync endpoint to
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the synchrotron instance(s) in this instance.
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Finally, to actually run your worker-based synapse, you must pass synctl the -a
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commandline option to tell it to operate on all the worker configurations found
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in the given directory, e.g.::
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synctl -a $CONFIG/workers start
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Currently one should always restart all workers when restarting or upgrading
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synapse, unless you explicitly know it's safe not to. For instance, restarting
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synapse without restarting all the synchrotrons may result in broken typing
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notifications.
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To manipulate a specific worker, you pass the -w option to synctl::
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synctl -w $CONFIG/workers/synchrotron.yaml restart
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All of the above is highly experimental and subject to change as Synapse evolves,
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but documenting it here to help folks needing highly scalable Synapses similar
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to the one running matrix.org!
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