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Increase Synapse caches and enable cache-autotuning by default (#3017)

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* Modify Synapse Cache Factor to use Auto Tune

Synapse has the ability to as it calls in its config auto tune caches.

This ability lets us set very high cache factors and then instead limit our resource use.

Defaults for this commit are 1/10th of what Element apparently runs for EMS stuff and matrix.org on Cache Factor and upstream documentation defaults for auto tune.

* Add vars to Synapse main.yml to control cache related config

This commit adds various cache related vars to main.yml for Synapse.

Some are auto tune and some are just adding explicit ways to control upstream vars.

* Updated Auto Tune figures

Autotuned figures have been bumped in consultation with other community members as to a reasonable level. Please note these defaults are more on the one of each workers side than they are on the monolith Side.

* Fix YML Error

The playbook is not happy with the previous state of this patch so this commit hopefully fixes it

* Add to_json to various Synapse tuning related configs

* Fix incorrect indication in homeserver.yaml.j2

* Minor cleanups

* Synapse Cache Autotuning Documentation

* Upgrade Synapse Cache Autotune to auto configure memory use

* Update Synapse Tuning docs to reflect automatic memory use configuration

* Fix Linting errors in synapses main.yml

* Rename variables for consistency (matrix_synapse_caches_autotuning_* -> matrix_synapse_cache_autotuning_*)

* Remove FIX ME comment about Synapse's `cache_autotuning`

`docs/maintenance-synapse.md` and `roles/custom/matrix-synapse/defaults/main.yml`
already contains documentation about these variables and the default values we set.

* Improve "Tuning caches and cache autotuning" documentation for Synapse

* Announce larger Synapse caches and cache auto-tuning

---------

Co-authored-by: Slavi Pantaleev <slavi@devture.com>
This commit is contained in:
Catalan Lover
2024-02-14 11:02:06 +01:00
committed by GitHub
parent f999947dfe
commit 9eab0292d4
5 changed files with 103 additions and 37 deletions
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docs/maintenance-synapse.md
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@ -74,8 +74,32 @@ Synapse's presence feature which tracks which users are online and which are off
If you have enough compute resources (CPU & RAM), you can make Synapse better use of them by [enabling load-balancing with workers](configuring-playbook-synapse.md#load-balancing-with-workers).
Tuning Synapse's cache factor can help reduce RAM usage. [See the upstream documentation](https://github.com/element-hq/synapse#help-synapse-is-slow-and-eats-all-my-ram-cpu) for more information on what value to set the cache factor to. Use the variable `matrix_synapse_caches_global_factor` to set the cache factor.
[Tuning your PostgreSQL database](maintenance-postgres.md#tuning-postgresql) could also improve Synapse performance. The playbook tunes the integrated Postgres database automatically, but based on your needs you may wish to adjust tuning variables manually. If you're using an [external Postgres database](configuring-playbook-external-postgres.md), you will aslo need to tune Postgres manually.
### Tuning caches and cache autotuning
Tuning Synapse's cache factor is useful for performance increases but also as part of controlling Synapse's memory use. Use the variable `matrix_synapse_caches_global_factor` to set the cache factor as part of this process.
**The playbook defaults the global cache factor to a large value** (e.g. `10`). A smaller value (e.g. `0.5`) will decrease the amount used for caches, but will [not necessarily decrease RAM usage as a whole](https://github.com/matrix-org/synapse/issues/3939).
Tuning the cache factor is useful only to a limited degree (as its crude to do in isolation) and therefore users who are tuning their cache factor should likely look into tuning autotune variables as well (see below).
Cache autotuning is **enabled by default** and controlled via the following variables:
- `matrix_synapse_cache_autotuning_max_cache_memory_usage` - defaults to 1/8 of total RAM with a cap of 2GB; values are specified in bytes
- `matrix_synapse_cache_autotuning_target_cache_memory_usage` - defaults to 1/16 of total RAM with a cap of 1GB; values are specified in bytes
- `matrix_synapse_cache_autotuning_min_cache_ttl` - defaults to `30s`
You can **learn more about cache-autotuning and the global cache factor settings** in the [Synapse's documentation on caches and associated values](https://matrix-org.github.io/synapse/latest/usage/configuration/config_documentation.html#caches-and-associated-values).
To **disable cache auto-tuning**, unset all values:
```yml
matrix_synapse_cache_autotuning_max_cache_memory_usage: ''
matrix_synapse_cache_autotuning_target_cache_memory_usage: ''
matrix_synapse_cache_autotuning_min_cache_ttl: ''
```
Users who wish to lower Synapse's RAM footprint should look into lowering the global cache factor and tweaking the autotune variables (or disabling auto-tuning). If your cache factor is too low for a given auto tune setting your caches will not reach autotune thresholds and autotune won't be able to do its job. Therefore, when auto-tuning is enabled (which it is by default), it's recommended to have your cache factor be large.
See also [How do I optimize this setup for a low-power server?](faq.md#how-do-i-optimize-this-setup-for-a-low-power-server).