annotate docs/usage/performance.rst @ 7611:9efcf6b78f71

dependencies: remove duplicate dependencies in dev_requirements.txt Babel and WebOb were present both in setup.py and dev_requirements.txt. When explicitly setting minimum dependencies in setup.py and running: pip install --upgrade -e . -r dev_requirements.txt python-ldap python-pam this duplication replaced useful diagnostic message from pip with less useful ones. For example, the following message was displayed when the Babel dependency duplication is present: kallithea 0.4.0rc1 has requirement Babel<2.7,==0.9.6, but you'll have babel 2.6.0 which is incompatible. When removing the duplication in dev_requirements.txt, this becomes: sphinx 1.7.9 has requirement babel!=2.0,>=1.3, but you'll have babel 0.9.6 which is incompatible. which makes it clear that to solve this problem, we need to bump the minimum dependency for Babel in setup.py from 0.9.6 to 1.3.
author Thomas De Schampheleire <thomas.de_schampheleire@nokia.com>
date Mon, 25 Mar 2019 20:57:39 +0100
parents 692dddf298e2
children 19af3fef3b34
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1 .. _performance:
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2
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3 ================================
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4 Optimizing Kallithea performance
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5 ================================
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7 When serving a large amount of big repositories, Kallithea can start performing
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8 slower than expected. Because of the demanding nature of handling large amounts
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9 of data from version control systems, here are some tips on how to get the best
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10 performance.
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13 Fast storage
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14 ------------
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16 Kallithea is often I/O bound, and hence a fast disk (SSD/SAN) and plenty of RAM
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17 is usually more important than a fast CPU.
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20 Caching
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21 -------
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23 Tweak beaker cache settings in the ini file. The actual effect of that is
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24 questionable.
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27 Database
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28 --------
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30 SQLite is a good option when having a small load on the system. But due to
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31 locking issues with SQLite, it is not recommended to use it for larger
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32 deployments.
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34 Switching to MySQL or PostgreSQL will result in an immediate performance
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35 increase. A tool like SQLAlchemyGrate_ can be used for migrating to another
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36 database platform.
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39 Horizontal scaling
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40 ------------------
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42 Scaling horizontally means running several Kallithea instances and let them
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43 share the load. That can give huge performance benefits when dealing with large
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44 amounts of traffic (many users, CI servers, etc.). Kallithea can be scaled
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45 horizontally on one (recommended) or multiple machines.
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47 It is generally possible to run WSGI applications multithreaded, so that
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48 several HTTP requests are served from the same Python process at once. That can
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49 in principle give better utilization of internal caches and less process
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50 overhead.
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52 One danger of running multithreaded is that program execution becomes much more
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53 complex; programs must be written to consider all combinations of events and
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54 problems might depend on timing and be impossible to reproduce.
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56 Kallithea can't promise to be thread-safe, just like the embedded Mercurial
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57 backend doesn't make any strong promises when used as Kallithea uses it.
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58 Instead, we recommend scaling by using multiple server processes.
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60 Web servers with multiple worker processes (such as ``mod_wsgi`` with the
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61 ``WSGIDaemonProcess`` ``processes`` parameter) will work out of the box.
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63 In order to scale horizontally on multiple machines, you need to do the
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64 following:
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65
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66 - Each instance's ``data`` storage needs to be configured to be stored on a
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67 shared disk storage, preferably together with repositories. This ``data``
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68 dir contains template caches, sessions, whoosh index and is used for
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69 task locking (so it is safe across multiple instances). Set the
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70 ``cache_dir``, ``index_dir``, ``beaker.cache.data_dir``, ``beaker.cache.lock_dir``
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71 variables in each .ini file to a shared location across Kallithea instances
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72 - If using several Celery instances,
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73 the message broker should be common to all of them (e.g., one
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74 shared RabbitMQ server)
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75 - Load balance using round robin or IP hash, recommended is writing LB rules
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76 that will separate regular user traffic from automated processes like CI
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77 servers or build bots.
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79
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80 Serve static files directly from the web server
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81 -----------------------------------------------
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83 With the default ``static_files`` ini setting, the Kallithea WSGI application
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84 will take care of serving the static files from ``kallithea/public/`` at the
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85 root of the application URL.
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86
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87 The actual serving of the static files is very fast and unlikely to be a
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88 problem in a Kallithea setup - the responses generated by Kallithea from
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89 database and repository content will take significantly more time and
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90 resources.
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92 To serve static files from the web server, use something like this Apache config
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93 snippet::
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94
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95 Alias /images/ /srv/kallithea/kallithea/kallithea/public/images/
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96 Alias /css/ /srv/kallithea/kallithea/kallithea/public/css/
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97 Alias /js/ /srv/kallithea/kallithea/kallithea/public/js/
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98 Alias /codemirror/ /srv/kallithea/kallithea/kallithea/public/codemirror/
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99 Alias /fontello/ /srv/kallithea/kallithea/kallithea/public/fontello/
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100
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101 Then disable serving of static files in the ``.ini`` ``app:main`` section::
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102
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103 static_files = false
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104
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105 If using Kallithea installed as a package, you should be able to find the files
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106 under ``site-packages/kallithea``, either in your Python installation or in your
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107 virtualenv. When upgrading, make sure to update the web server configuration
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108 too if necessary.
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109
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110 It might also be possible to improve performance by configuring the web server
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111 to compress responses (served from static files or generated by Kallithea) when
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112 serving them. That might also imply buffering of responses - that is more
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113 likely to be a problem; large responses (clones or pulls) will have to be fully
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114 processed and spooled to disk or memory before the client will see any
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115 response. See the documentation for your web server.
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116
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117
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118 .. _SQLAlchemyGrate: https://github.com/shazow/sqlalchemygrate