From 29645aab1d51746c4ea1b520840641025a085f8f Mon Sep 17 00:00:00 2001
From: Eliot Berriot <contact@eliotberriot.com>
Date: Sat, 28 Apr 2018 16:17:29 +0200
Subject: [PATCH] Added documentation page on how to reduce memory usage.
---
api/compose/django/daphne.sh | 2 +-
changes/changelog.d/optimization.doc | 11 +++++++++
deploy/funkwhale-server.service | 2 +-
docs/installation/index.rst | 6 +++++
docs/installation/optimization.rst | 37 ++++++++++++++++++++++++++++
5 files changed, 56 insertions(+), 2 deletions(-)
create mode 100644 changes/changelog.d/optimization.doc
create mode 100644 docs/installation/optimization.rst
diff --git a/api/compose/django/daphne.sh b/api/compose/django/daphne.sh
index 4fa3041436..3ceb19e96e 100755
--- a/api/compose/django/daphne.sh
+++ b/api/compose/django/daphne.sh
@@ -1,3 +1,3 @@
#!/bin/bash -eux
python /app/manage.py collectstatic --noinput
-/usr/local/bin/daphne -b 0.0.0.0 -p 5000 config.asgi:application
+/usr/local/bin/daphne -b 0.0.0.0 -p 5000 config.asgi:application --proxy-headers
diff --git a/changes/changelog.d/optimization.doc b/changes/changelog.d/optimization.doc
new file mode 100644
index 0000000000..929e148210
--- /dev/null
+++ b/changes/changelog.d/optimization.doc
@@ -0,0 +1,11 @@
+Added documentation for optimizing Funkwhale and reduce its memory
+footprint.
+
+Changelog
+^^^^^^^^^
+
+For non-docker deployments, add ``--proxy-headers`` at the end of the ``daphne``
+command in :file:`/etc/systemd/system/funkwhale-server.service`.
+
+This will ensure the application receive the correct IP address from the client
+and not the proxy's one.
diff --git a/deploy/funkwhale-server.service b/deploy/funkwhale-server.service
index 53d3a104bf..88d70d338e 100644
--- a/deploy/funkwhale-server.service
+++ b/deploy/funkwhale-server.service
@@ -8,7 +8,7 @@ User=funkwhale
# adapt this depending on the path of your funkwhale installation
WorkingDirectory=/srv/funkwhale/api
EnvironmentFile=/srv/funkwhale/config/.env
-ExecStart=/srv/funkwhale/virtualenv/bin/daphne -b ${FUNKWHALE_API_IP} -p ${FUNKWHALE_API_PORT} config.asgi:application
+ExecStart=/srv/funkwhale/virtualenv/bin/daphne -b ${FUNKWHALE_API_IP} -p ${FUNKWHALE_API_PORT} config.asgi:application --proxy-headers
[Install]
WantedBy=multi-user.target
diff --git a/docs/installation/index.rst b/docs/installation/index.rst
index c2a70421bb..0a159c6388 100644
--- a/docs/installation/index.rst
+++ b/docs/installation/index.rst
@@ -28,10 +28,16 @@ On a dockerized instance with 2 CPUs and a few active users, the memory footprin
funkwhale_postgres_1 22.73 MiB
funkwhale_redis_1 1.496 MiB
+Some users have reported running Funkwhale on Raspberry Pis with a memory
+consuption of less than 200MiB.
+
Thus, Funkwhale should run fine on commodity hardware, small hosting boxes and
Raspberry Pi. We lack real-world exemples of such deployments, so don't hesitate
do give us your feedback (either positive or negative).
+Check out :doc:`optimization` for advices on how to tune your instance on small
+configurations.
+
Software requirements
---------------------
diff --git a/docs/installation/optimization.rst b/docs/installation/optimization.rst
new file mode 100644
index 0000000000..f873795e26
--- /dev/null
+++ b/docs/installation/optimization.rst
@@ -0,0 +1,37 @@
+Optimizing your Funkwhale instance
+==================================
+
+Depending on your requirements, you may want to reduce as much as possible
+Funkwhale's footprint.
+
+Reduce workers concurrency
+--------------------------
+
+Asynchronous tasks are handled by a celery worker, which will by default
+spawn a worker process per CPU available. This can lead to a higher
+memory usage.
+
+You can control this behaviour using the ``--concurrency`` flag.
+For instance, setting ``--concurrency=1`` will spawn only one worker.
+
+This flag should be appended after the ``celery -A funkwhale_api.taskapp worker``
+command in your :file:`docker-compose.yml` file if your using Docker, or in your
+:file:`/etc/systemd/system/funkwhale-worker.service` otherwise.
+
+.. note::
+
+ Reducing concurrency comes at a cost: asynchronous tasks will be processed
+ more slowly. However, on small instances, this should not be an issue.
+
+
+Switch from prefork to solo pool
+--------------------------------
+
+Using a different pool implementation for Celery tasks may also help.
+
+Using the ``solo`` pool type should reduce your memory consumption.
+You can control this behaviour using the ``--pool=solo`` flag.
+
+This flag should be appended after the ``celery -A funkwhale_api.taskapp worker``
+command in your :file:`docker-compose.yml` file if your using Docker, or in your
+:file:`/etc/systemd/system/funkwhale-worker.service` otherwise.
--
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