Mercurial > kallithea
annotate docs/usage/performance.rst @ 8443:b688a2a1b189 stable
docs: clarify that MariaDB is supported, with slight preference for this more free option
author | Mads Kiilerich <mads@kiilerich.com> |
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date | Mon, 08 Jun 2020 16:05:21 +0200 |
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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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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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15 |
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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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22 |
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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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34 |
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36 Database |
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37 -------- |
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38 |
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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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42 |
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43 Switching to PostgreSQL or MariaDB/MySQL 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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46 |
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48 Horizontal scaling |
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49 ------------------ |
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50 |
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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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55 |
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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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64 |
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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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68 |
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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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87 |
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88 |
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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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126 |
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127 .. _SQLAlchemyGrate: https://github.com/shazow/sqlalchemygrate |