We'd like to be able to split some of the work that synapse does into multiple python processes. In theory multiple synapse processes could share a single postgresql database and we'd scale up by running more synapse processes. However much of synapse assumes that only one process is interacting with the database, both for assigning unique identifiers when inserting into tables, notifying components about new updates, and for invalidating its caches.
So running multiple copies of the current code isn't an option. One way to run multiple processes would be to have a single writer process and multiple reader processes connected to the same database. In order to do this we'd need a way for the reader process to invalidate its in-memory caches when an update happens on the writer. One way to do this is for the writer to present an append-only log of updates which the readers can consume to invalidate their caches and to push updates to listening clients or pushers.
Synapse already stores much of its data as an append-only log so that it
can correctly respond to
/sync requests so the amount of code changes
needed to expose the append-only log to the readers should be fairly
There are read-only version of the synapse storage layer in
synapse/replication/slave/storage that use the response of the
replication API to invalidate their caches.
Information about how the tcp replication module is structured, including how
the classes interact, can be found in