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tuning-scale-horizontally.rst
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r1 .. _scale-horizontal:
Scale Horizontally
------------------
docs: updated section on performance, scaling, ssl support
r2205 |RCE| is built in a way it support horizontal scaling across multiple machines.
There are two main pre-requisites for that:
- Shared storage that each machine can access.
- Shared DB connection across machines.
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r1 Horizontal scaling means adding more machines or workers into your pool of
resources. Horizontally scaling |RCE| gives a huge performance increase,
especially under large traffic scenarios with a high number of requests. This
is very beneficial when |RCE| is serving many users simultaneously,
or if continuous integration servers are automatically pulling and pushing code.
docs: updated section on performance, scaling, ssl support
r2205
If you scale across different machines, each |RCM| instance
needs to store its data on a shared disk, preferably together with your
|repos|. This data directory contains template caches, a full text search index,
and is used for task locking to ensure safety across multiple instances.
To do this, set the following properties in the :file:`rhodecode.ini` file to
set the shared location across all |RCM| instances.
.. code-block:: ini
cache_dir = /shared/path/caches # set to shared location
search.location = /shared/path/search_index # set to shared location
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docs: updated section on performance, scaling, ssl support
r2205 ####################################
### BEAKER CACHE ####
####################################
beaker.cache.data_dir = /shared/path/data # set to shared location
beaker.cache.lock_dir = /shared/path/lock # set to shared location
.. note::
If you use custom caches such as `beaker.cache.auth_plugins.` it's recommended
to set it to the memcached/redis or database backend so it can be shared
across machines.
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r1
It is recommended to create another dedicated |RCE| instance to handle
traffic from build farms or continuous integration servers.
.. note::
You should configure your load balancing accordingly. We recommend writing
load balancing rules that will separate regular user traffic from
automated process traffic like continuous servers or build bots.
.. note::
If Celery is used on each instance then you should run separate Celery
instances, but the message broker should be the same for all of them.