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performance.rst
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Added simple docs for optimizing RhodeCode performance
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Optimizing RhodeCode Performance
================================
docs improvements
r2775 When serving large amount of big repositories RhodeCode can start
performing slower than expected. Because of demanding nature of handling large
amount of data from version control systems here are some tips how to get
the best performance.
* RhodeCode will perform better on machines with faster disks (SSD/SAN). It's
more important to have faster disk than faster CPU.
* Slowness on initial page can be easily fixed by grouping repositories, and/or
performance section docs update
r3390 increasing cache size (see below), that includes using lightweight dashboard
option and vcs_full_cache setting in .ini file
docs improvements
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Added simple docs for optimizing RhodeCode performance
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Follow these few steps to improve performance of RhodeCode system.
doc fixes
r2680 1. Increase cache
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doc fixes
r2680 in the .ini file::
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doc fixes
r2680 beaker.cache.sql_cache_long.expire=3600 <-- set this to higher number
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This option affects the cache expiration time for main page. Having
few hundreds of repositories on main page can sometimes make the system
to behave slow when cache expires for all of them. Increasing `expire`
option to day (86400) or a week (604800) will improve general response
docs improvements
r2775 times for the main page. RhodeCode has an intelligent cache expiration
system and it will expire cache for repositories that had been changed.
Added simple docs for optimizing RhodeCode performance
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2. Switch from sqlite to postgres or mysql
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Added simple docs for optimizing RhodeCode performance
r2517 sqlite is a good option when having small load on the system. But due to
locking issues with sqlite, it's not recommended to use it for larger
setup. Switching to mysql or postgres will result in a immediate
performance increase.
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Added simple docs for optimizing RhodeCode performance
r2517 3. Scale RhodeCode horizontally
performance section docs update
r3390 Scaling horizontally can give huge performance increase when dealing with
large traffic (large amount of users, CI servers etc). RhodeCode can be
scaled horizontally on one (recommended) or multiple machines. In order
to scale horizontally you need to do the following:
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performance section docs update
r3390 - each instance needs it's own .ini file and unique `instance_id` set in them
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r3413 - each instance `data` storage needs to be configured to be stored on a
performance section docs update
r3390 shared disk storage, preferably together with repositories. This `data`
dir contains template caches, sessions, whoosh index and it's used for
tasks locking (so it's safe across multiple instances). Set the
`cache_dir`, `index_dir`, `beaker.cache.data_dir`, `beaker.cache.lock_dir`
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r3413 variables in each .ini file to shared location across RhodeCode instances
performance section docs update
r3390 - if celery is used each instance should run separate celery instance, but
the message broken should be common to all of them (ex one rabbitmq
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r3413 shared server)
performance section docs update
r3390 - load balance using round robin or ip hash, recommended is writing LB rules
that will separate regular user traffic from automated processes like CI
servers or build bots.