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Scaling synapse via workers

Synapse has experimental support for splitting out functionality into multiple separate python processes, helping greatly with scalability. These processes are called 'workers', and are (eventually) intended to scale horizontally independently.

All processes continue to share the same database instance, and as such, workers only work with postgres based synapse deployments (sharing a single sqlite across multiple processes is a recipe for disaster, plus you should be using postgres anyway if you care about scalability).

The workers communicate with the master synapse process via a synapse-specific HTTP protocol called 'replication' - analogous to MySQL or Postgres style database replication; feeding a stream of relevant data to the workers so they can be kept in sync with the main synapse process and database state.

To enable workers, you need to add a replication listener to the master synapse, e.g.:

  - port: 9092
    bind_address: ''
    type: http
    tls: false
    x_forwarded: false
      - names: [replication]
        compress: false

Under no circumstances should this replication API listener be exposed to the public internet; it currently implements no authentication whatsoever and is unencrypted HTTP.

You then create a set of configs for the various worker processes. These should be worker configuration files should be stored in a dedicated subdirectory, to allow synctl to manipulate them.

The current available worker applications are:
  • - handles sending push notifications to sygnal and email
  • - handles /sync endpoints. can scales horizontally through multiple instances.
  • - handles output traffic to Application Services
  • - handles receiving federation traffic (including public_rooms API)
  • - handles the media repository.
  • - handles client API endpoints like /publicRooms

Each worker configuration file inherits the configuration of the main homeserver configuration file. You can then override configuration specific to that worker, e.g. the HTTP listener that it provides (if any); logging configuration; etc. You should minimise the number of overrides though to maintain a usable config.

You must specify the type of worker application (worker_app) and the replication endpoint that it's talking to on the main synapse process (worker_replication_url).

For instance:


# The replication listener on the synapse to talk to.

 - type: http
   port: 8083
     - names:
       - client

worker_daemonize: True
worker_pid_file: /home/matrix/synapse/
worker_log_config: /home/matrix/synapse/config/synchrotron_log_config.yaml a full configuration for a synchrotron worker instance, which will expose a plain HTTP /sync endpoint on port 8083 separately from the /sync endpoint provided by the main synapse.

Obviously you should configure your loadbalancer to route the /sync endpoint to the synchrotron instance(s) in this instance.

Finally, to actually run your worker-based synapse, you must pass synctl the -a commandline option to tell it to operate on all the worker configurations found in the given directory, e.g.:

synctl -a $CONFIG/workers start

Currently one should always restart all workers when restarting or upgrading synapse, unless you explicitly know it's safe not to. For instance, restarting synapse without restarting all the synchrotrons may result in broken typing notifications.

To manipulate a specific worker, you pass the -w option to synctl:

synctl -w $CONFIG/workers/synchrotron.yaml restart

All of the above is highly experimental and subject to change as Synapse evolves, but documenting it here to help folks needing highly scalable Synapses similar to the one running!