Configuration manual


Default installation is suitable for most simple and common cases, but Polemarch is highly configurable system. If you need something more advanced (scalability, dedicated DB, custom cache, logging or directories) you can always configure Polemarch deeply by tweaking /etc/polemarch/settings.ini.

This manual does not have purpose to describe all possible configuration options in details because settings.ini has commentary for every option which makes clear its purpose and possible values. But here is a brief overview of the most important settings to make clear for you big picture: what you can actually customize in Polemarch.

We advice you to read Polemarch clustering overview if you want to setup cluster of Polemarch nodes to maintain reliability or speedup things. It will give you understanding of services, which are included into Polemarch and how to distribute them between the nodes to reach your goal.

Project architecture

Polemarch was created to adapt to any work environment. Almost every service can be easily replaced by another without losing any functionality. The application architecture consists of the following elements:

  • Database supports all types and versions that django can. The code was written to be vendor agnostic to support as many backends as possible. Database contains information about projects settings, schedule and templates of tasks, execution history, authorisation data, etc. Database performance is a key performance limitation of the entire Polemarch.

  • Cache services is used for store session data, services locks, etc. Also, PM support all of Django can. Mostly, we recommend to use Redis in small and medium clusters.

  • MQ or rpc engine is required for notifying celery worker about new task execution request. Redis in most cases can process up to 1000 executions/min. For more complex and high-load implementations, it is recommended to use a distributed RabbitMQ cluster. If technically possible, AWS SQS and its compatible counterparts from other cloud providers are also supported.

  • Centrifugo (optional) is used for active user interaction. At this point, the service notifies the user of an update or change to the data structure that the user is viewing to complete a data update request. This reduces the load on the database, because without this service, the interface makes periodic requests on a timer.

  • Project storage at now is directory in filesystem where PM clone or unarchive project files for further executions. Storage must be readable for web-server and writeable for celery worker. It can be mounted dir from shared storage.

Understanding what services the Polemarch application consists of, you can build any architecture of services suitable for the circumstances and infrastructure.

Polemarch clustering overview

Polemarch actually consists of two services: web-server and worker. Polemarch uses worker for long-running tasks (such as ansible-playbook runs, repo synchronizations and so on). Those services are designed as systemd services you can control using regular distro-tools for service manipulation. You can run more than one server with those services. In default configuration those services uses local file system to keep data and exchange with each other, but for multiple nodes they must be configured to use shared client-server database, cache server and network filesystem (for multiple workers). All those settings are described in appropriate sections of this documentation. It is up to you to make sure that configuration identical on every node to prevent discordant behaviour of nodes. If you have multiple web-servers, don’t forget to setup HAProxy or something similar for balancing load between them.

Lets assume, that you want to create 2 servers with web-part of Polemarch to maintain reliability of your admin-panel and 4 servers with workers to prevent denial for service because of overloading. Then briefly (it is mostly example than general howto) you must do such steps:

  1. Install Polemarch from PyPI at every server with worker and web-server by installation instructions. We recommend to install virtual environment in /opt/polemarch and set as owner user polemarch (need to be created).

  2. Setup some network filesystem (NFS, Samba, GlusterFS, Ceph). NFS, for example. Mount it in the same directory of all worker-intended nodes. Write this directory in Main settings. Example:

    projects_dir = /mnt/mystorage/projects
    hooks_dir = /mnt/mystorage/hooks
  3. Setup some http-balancer. HAProxy, for example. Point it to web-intended nodes.


    You can setup ssl for Polemarch endpoints in this step.

  4. Create polemarch systemd service:

    1. Firstly, create a file /etc/systemd/system/polemarch.service:

      Description=Polemarch Service HTTP Server redis.service mysql.service
      ExecStart=/opt/polemarch/bin/polemarchctl webserver
      ExecReload=/opt/polemarch/bin/polemarchctl webserver reload=/opt/polemarch/pid/
      ExecStop=/opt/polemarch/bin/polemarchctl webserver stop=/opt/polemarch/pid/
      # Uncomment this if used privileged ports
      # Capabilities=CAP_NET_BIND_SERVICE+ep
      # AmbientCapabilities=CAP_NET_BIND_SERVICE


      Notice, that user and group ‘polemarch’ should exist in your system. If they don’t exist, create them.

    2. Reload systemctl daemon:

      systemctl daemon-reload
    3. Add polemarch.service to autoload:

      systemctl enable polemarch.service
    4. Start polemarch.service:

      systemctl start polemarch.service
    5. Repeat all steps in other nodes and connect them to one DB, cache, MQ and storage.


      You don’t need migrate database on each node. This need only once when you install/update first node in cluster.


      Don’t forget to stop all Polemarch services when update polemarch package.

That’s it.

Main settings

Section [main].

This section is for settings related to whole Polemarch (both worker and web). Here you can specify verbosity level of Polemarch during work, which can be useful for troubleshoot problems (logging level etc). Also there are settings for changing of timezone for whole app and directory where Polemarch will store ansible projects cloned from repositories.

If you want to use LDAP protocol, you should create next settings in section [main].

ldap-server = ldap://server-ip-or-host:port
ldap-default-domain =
ldap-auth_format = cn=<username>,ou=your-group-name,<domain>

ldap-default-domain is an optional argument, that is aimed to make user authorization easier (without input of domain name).

ldap-auth_format is an optional argument, that is aimed to customize LDAP authorization request. Default value: cn=<username>,<domain>

So in this case authorization logic will be the following:

  1. System checks combination of login:password in database;

  2. System checks combination of login:password in LDAP:

    • if domain was mentioned, it will be set during authorization (if user enter login without or without DOMAIN\user );

    • if authorization was successful and there is user with mentioned login in database, server creates session for him.

  • debug - Enable debug mode. Default: false.

  • allowed_hosts - Comma separated list of domains, which allowed to serve. Default: *.

  • ldap-server - LDAP server connection.

  • ldap-default-domain - Default domain for auth.

  • timezone - Timezone of web-application. Default: UTC.

  • log_level - Logging level. Default: WARNING.

  • projects_dir - Path where projects will be stored.

  • hooks_dir - Path where hook scripts stored.

  • executor_path - Path for polemarch-ansible wrapper binary.

  • enable_django_logs - Enable or disable Django logger to output. Useful for debugging. Default: false.

  • enable_user_self_remove - Enable or disable user self-removing. Default: false.

  • auth-cache-user - Enable or disable user instance caching. It increases session performance on each request but saves model instance in unsafe storage (default django cache). The instance is serialized to a string using the standard python module pickle and then encrypted with Vigenère cipher. Read more in the vstutils.utils.SecurePickling documentation. Default: false.

Database settings

Section [database].

Here you can change settings related to database system, which Polemarch will use. Polemarch supports all databases supported by django. List of supported out of the box: SQLite (default choice), MySQL, Oracle, or PostgreSQL. Configuration details you can look at Django database documentation. If you run Polemarch at multiple nodes (clusterization), you should use some of client-server database (SQLite not suitable) shared for all nodes.

If you use MySQL there is a list of required settings, that you should create for correct database work.

Firstly, if you use MariaDB and you have set timezone different from “UTC” you should run next command:

mysql_tzinfo_to_sql /usr/share/zoneinfo | mysql -u root -p mysql

Secondly, for correct MariaDB work you should set next options in settings.ini file:

connect_timeout = 10
init_command = SET sql_mode='STRICT_TRANS_TABLES', default_storage_engine=INNODB, NAMES 'utf8', CHARACTER SET 'utf8', SESSION collation_connection = 'utf8_unicode_ci'

Finally, you should add some options to MariaDB configuration:

init_command = SET collation_connection = @@collation_database



You can find more database options in Databases settings.

Cache settings

Section [cache].

This section is for settings related to cache backend used by Polemarch. Polemarch supports all cache backends that Django supports. Currently is: filesystem, in-memory, memcached out of the box and many more by additional plugins. You can find details about cache configuration at Django caches documentation. In clusterization scenario we advice to share cache between nodes to speedup their work using client-server cache realizations. We recommend to use Redis in production environments.

Locks settings

Section [locks].

Locks is system that Polemarch uses to prevent damage from parallel actions working on something simultaneously. It is based on Django cache, so there is another bunch of same settings as Cache. And why there is another section for them, you may ask. Because cache backend used for locking must provide some guarantees, which does not required to usual cache: it MUST be shared for all Polemarch threads and nodes. So, in-memory backend, for example, is not suitable. In case of clusterization we strongly recommend to use Redis or Memcached as backend for that purpose. Cache and locks backend can be same, but don’t forget about requirement we said above.

Session cache settings

Section [session].

Polemarch store sessions in Database settings, but for better performance, we use a cache-based session backend. It is based on Django cache, so there is another bunch of same settings as Cache. By default, settings getted from Cache.

Rpc settings

Section [rpc].

Polemarch uses Celery for long-running tasks (such as ansible-playbook runs, repo synchronizations and so on). Celery is based on message queue concept, so between web-service and workers running under Celery bust be some kind of message broker (RabbitMQ or something). Those settings relate to this broker and Celery itself. Those kinds of settings: broker backend, number of worker-processes per node and some settings used for troubleshoot server-broker-worker interaction problems.

  • connection - Celery broker connection. Read more: Broker Settings. Default: filesystem:///var/tmp.

  • concurrency - Celery count worker threads. Default: 4.

  • heartbeat - Interval between sending heartbeat packages, which says that connection still alive. Default: 10.

  • enable_worker - Enable or disable worker with webserver. Default: true.

  • clone_retry_count - Retries count on project sync operation.


You can find more RPC options in Rpc settings.

Worker settings

Section [worker].

Celery worker options for start. Useful settings:

  • loglevel - Celery worker logging level. Default: from main section log_level.

  • pidfile - Celery worker pidfile. Default: /run/

  • autoscale - Options for autoscaling. Two comma separated numbers: max,min.

  • beat - Enable or disable celery beat scheduler. Default: true.

Other settings can be getted from command celery worker --help.

Web settings

Section [web].

Here placed settings related to web-server. Those settings like: session_timeout, static_files_url or pagination limit.

  • session_timeout - Session life-cycle time. Default: 2w (two weeks).

  • rest_page_limit - Default limit of objects in API list. Default: 1000.

  • history_metrics_window - Timeframe in seconds of collecting execution history statuses. Default: 1min.


You can find more Web options in Web settings.

Centrifugo client settings

Section [centrifugo].

To install app with centrifugo client, [centrifugo] section must be set. Centrifugo is used by application to auto-update page data. When user change some data, other clients get notification on subscriptions_update channel with model label and primary key. Without the service all GUI-clients get page data every 5 seconds (by default). Centrifugo server v3 is supported.

  • address - Centrifugo api address. For example, http://localhost:8000/api.

  • public_address - Centrifugo server address. By default used address without /api prefix (http -> ws, https -> wss). Also, can be used relative path, like /centrifugo.

  • api_key - API key for clients.

  • token_hmac_secret_key - API key for jwt-token generation.

  • timeout - Connection timeout.

  • verify - Connection verification.


These settings also add parameters to the OpenApi schema and change how the auto-update system works in the GUI. token_hmac_secret_key is used for jwt-token generation (based on session expiration time). Token will be used for Centrifugo-JS client.


api_key and token_hmac_secret_key come from config.json for Centrifugo. Read more in Official Centrifugo documentation

Git settings

Sections [git.fetch] and [git.clone].

Options for git commands. See options in git fetch --help or git clone --help.

Archive settings

Section [archive].

Here you can specify settings used by archive (e.g. TAR) projects.

  • max_content_length - Maximum download file size. Format: 30<unit>, where unit is b, kb, mb, gb, tb.

History output plugins

Section [history]

This section of the configuration provides to configure the output history plugin settings.

  • output_plugins - a comma-separated list of plugin names that are used to record history lines. Plugins must have the writeable attribute. Default: database

  • read_plugin - the name of the plugin used to display the history lines in the api. Default is database.

Other parameters are set in the plugin options section: history.plugin.PLUGIN_NAME.options.


Be careful. The reader plugin must be able to read the data. Therefore, the storage from which the reading plugin takes data must be filled with one of the writer plugins.

Production web settings

Section [uwsgi].

Here placed settings related to web-server used by Polemarch in production (for deb and rpm packages by default). Most of them related to system paths (logging, PID-file and so on).


More settings in Configuring uWSGI (deprecated) and uvicorn docs.


In production, it is recommended to use Centrifugo in order to reduce the load on the backend from automatic page updates.

Configuration options

This section contains additional information for configure additional elements.

#. If you need to set https for your web settings, you can do it using HAProxy, Nginx or configure it in settings.ini.

# [uvicorn]
# ssl_keyfile = /etc/polemarch/polemarch.key
# ssl_certfile = /etc/polemarch/polemarch.crt
  1. We strictly do not recommend running the web server from root. Use HTTP proxy to run on privileged ports.


If you need more options you can find it in Configuration manual in the official vstutils documentation.

Inventory plugins config

To connect an inventory plugin to Polemarch, there should be a section

backend =


  • <plugin_name> - name that will be available in API to work with

  • backend - is a python import path to plugin class

Also you may add options which will be available in plugin:

some_option = some_option

To read more about plugins, please see Plugins.

Execution plugins config

To connect an execution plugin to Polemarch, there should be a section

backend =
compatible_inventory_plugins = <inventory_plugin1>,<inventory_plugin1>


  • <plugin_name> - name that will be available in API to work with

  • backend - is a python import path to plugin class

  • compatible_inventory_plugins - inventory plugins which are compatible with this execution plugin. If omitted,

    it’s supposed that execution plugin cannot work with any inventory.

Also you may add options which will be available in plugin:

some_option = some_option

To read more about plugins, please see Plugins.