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author Mads Kiilerich <mads@kiilerich.com>
date Mon, 04 May 2020 19:12:40 +0200
parents fb0417c65c64
children b688a2a1b189
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1 .. _performance:
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3 ================================
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4 Optimizing Kallithea performance
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5 ================================
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6
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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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18
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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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25
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26 .. note::
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27
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28 Beaker has no upper bound on cache size and will never drop any caches. For
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29 memory cache, the only option is to regularly restart the worker process.
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30 For file cache, it must be cleaned manually, as described in the `Beaker
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31 documentation <https://beaker.readthedocs.io/en/latest/sessions.html#removing-expired-old-sessions>`_::
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32
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33 find data/cache -type f -mtime +30 -print -exec rm {} \;
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36 Database
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37 --------
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39 SQLite is a good option when having a small load on the system. But due to
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40 locking issues with SQLite, it is not recommended to use it for larger
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41 deployments.
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43 Switching to MySQL or PostgreSQL will result in an immediate performance
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44 increase. A tool like SQLAlchemyGrate_ can be used for migrating to another
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45 database platform.
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48 Horizontal scaling
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49 ------------------
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51 Scaling horizontally means running several Kallithea instances and let them
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52 share the load. That can give huge performance benefits when dealing with large
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53 amounts of traffic (many users, CI servers, etc.). Kallithea can be scaled
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54 horizontally on one (recommended) or multiple machines.
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56 It is generally possible to run WSGI applications multithreaded, so that
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57 several HTTP requests are served from the same Python process at once. That can
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58 in principle give better utilization of internal caches and less process
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59 overhead.
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60
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61 One danger of running multithreaded is that program execution becomes much more
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62 complex; programs must be written to consider all combinations of events and
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63 problems might depend on timing and be impossible to reproduce.
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65 Kallithea can't promise to be thread-safe, just like the embedded Mercurial
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66 backend doesn't make any strong promises when used as Kallithea uses it.
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67 Instead, we recommend scaling by using multiple server processes.
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69 Web servers with multiple worker processes (such as ``mod_wsgi`` with the
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70 ``WSGIDaemonProcess`` ``processes`` parameter) will work out of the box.
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71
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72 In order to scale horizontally on multiple machines, you need to do the
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73 following:
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74
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75 - Each instance's ``data`` storage needs to be configured to be stored on a
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76 shared disk storage, preferably together with repositories. This ``data``
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77 dir contains template caches, sessions, whoosh index and is used for
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78 task locking (so it is safe across multiple instances). Set the
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79 ``cache_dir``, ``index_dir``, ``beaker.cache.data_dir``, ``beaker.cache.lock_dir``
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80 variables in each .ini file to a shared location across Kallithea instances
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81 - If using several Celery instances,
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82 the message broker should be common to all of them (e.g., one
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83 shared RabbitMQ server)
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84 - Load balance using round robin or IP hash, recommended is writing LB rules
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85 that will separate regular user traffic from automated processes like CI
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86 servers or build bots.
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89 Serve static files directly from the web server
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90 -----------------------------------------------
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91
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92 With the default ``static_files`` ini setting, the Kallithea WSGI application
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93 will take care of serving the static files from ``kallithea/public/`` at the
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94 root of the application URL.
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95
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96 The actual serving of the static files is very fast and unlikely to be a
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97 problem in a Kallithea setup - the responses generated by Kallithea from
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98 database and repository content will take significantly more time and
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99 resources.
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100
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101 To serve static files from the web server, use something like this Apache config
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102 snippet::
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103
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104 Alias /images/ /srv/kallithea/kallithea/kallithea/public/images/
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105 Alias /css/ /srv/kallithea/kallithea/kallithea/public/css/
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106 Alias /js/ /srv/kallithea/kallithea/kallithea/public/js/
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107 Alias /codemirror/ /srv/kallithea/kallithea/kallithea/public/codemirror/
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108 Alias /fontello/ /srv/kallithea/kallithea/kallithea/public/fontello/
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109
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110 Then disable serving of static files in the ``.ini`` ``app:main`` section::
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111
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112 static_files = false
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113
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114 If using Kallithea installed as a package, you should be able to find the files
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115 under ``site-packages/kallithea``, either in your Python installation or in your
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116 virtualenv. When upgrading, make sure to update the web server configuration
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117 too if necessary.
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118
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119 It might also be possible to improve performance by configuring the web server
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120 to compress responses (served from static files or generated by Kallithea) when
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121 serving them. That might also imply buffering of responses - that is more
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122 likely to be a problem; large responses (clones or pulls) will have to be fully
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123 processed and spooled to disk or memory before the client will see any
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124 response. See the documentation for your web server.
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125
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127 .. _SQLAlchemyGrate: https://github.com/shazow/sqlalchemygrate