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author | Richard van der Hoff <richard@matrix.org> | 2019-06-26 22:34:41 +0100 |
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committer | Richard van der Hoff <richard@matrix.org> | 2019-06-26 22:34:41 +0100 |
commit | a4daa899ec4cd195fc10936f68df5c78314b366c (patch) | |
tree | 35e88ff388b0f7652773a79930b732aa04f16bde /README.rst | |
parent | changelog (diff) | |
parent | Improve docs on choosing server_name (#5558) (diff) | |
download | synapse-a4daa899ec4cd195fc10936f68df5c78314b366c.tar.xz |
Merge branch 'develop' into rav/saml2_client
Diffstat (limited to 'README.rst')
-rw-r--r-- | README.rst | 32 |
1 files changed, 25 insertions, 7 deletions
diff --git a/README.rst b/README.rst index 5409f0c563..13e11a5773 100644 --- a/README.rst +++ b/README.rst @@ -340,8 +340,11 @@ log lines and looking for any 'Processed request' lines which take more than a few seconds to execute. Please let us know at #synapse:matrix.org if you see this failure mode so we can help debug it, however. -Help!! Synapse eats all my RAM! -------------------------------- +Help!! Synapse is slow and eats all my RAM/CPU! +----------------------------------------------- + +First, ensure you are running the latest version of Synapse, using Python 3 +with a PostgreSQL database. Synapse's architecture is quite RAM hungry currently - we deliberately cache a lot of recent room data and metadata in RAM in order to speed up @@ -352,14 +355,29 @@ variable. The default is 0.5, which can be decreased to reduce RAM usage in memory constrained enviroments, or increased if performance starts to degrade. +However, degraded performance due to a low cache factor, common on +machines with slow disks, often leads to explosions in memory use due +backlogged requests. In this case, reducing the cache factor will make +things worse. Instead, try increasing it drastically. 2.0 is a good +starting value. + Using `libjemalloc <http://jemalloc.net/>`_ can also yield a significant -improvement in overall amount, and especially in terms of giving back RAM -to the OS. To use it, the library must simply be put in the LD_PRELOAD -environment variable when launching Synapse. On Debian, this can be done -by installing the ``libjemalloc1`` package and adding this line to -``/etc/default/matrix-synapse``:: +improvement in overall memory use, and especially in terms of giving back +RAM to the OS. To use it, the library must simply be put in the +LD_PRELOAD environment variable when launching Synapse. On Debian, this +can be done by installing the ``libjemalloc1`` package and adding this +line to ``/etc/default/matrix-synapse``:: LD_PRELOAD=/usr/lib/x86_64-linux-gnu/libjemalloc.so.1 This can make a significant difference on Python 2.7 - it's unclear how much of an improvement it provides on Python 3.x. + +If you're encountering high CPU use by the Synapse process itself, you +may be affected by a bug with presence tracking that leads to a +massive excess of outgoing federation requests (see `discussion +<https://github.com/matrix-org/synapse/issues/3971>`_). If metrics +indicate that your server is also issuing far more outgoing federation +requests than can be accounted for by your users' activity, this is a +likely cause. The misbehavior can be worked around by setting +``use_presence: false`` in the Synapse config file. |