Telemetry best practices

Telemetry best practices

The following are some suggested best practices to follow when deploying and configuring the Telemetry service. The best practices are divided into data collection and storage.

Data collection

  1. The Telemetry service collects a continuously growing set of data. Not all the data will be relevant for an administrator to monitor.

    • Based on your needs, you can edit the polling.yaml and pipeline.yaml configuration files to include select meters to generate or process

    • By default, Telemetry service polls the service APIs every 10 minutes. You can change the polling interval on a per meter basis by editing the polling.yaml configuration file.


      If the polling interval is too short, it will likely increase the stress on the service APIs.

  2. If polling many resources or at a high frequency, you can add additional central and compute agents as necessary. The agents are designed to scale horizontally. For more information refer to the high availability guide.

  3. workload_partitioning of notification agents is only required if the pipeline configuration leverages transformers. It may also be enabled if batching is required to minimize load on the defined publisher targets. If transformers are not enabled, multiple agents may still be deployed without workload_partitioning and processing will be done greedily.

Data storage


As of Newton, data storage is not recommended in ceilometer. Alarm, metric, and event data should be stored in aodh, gnocchi, and panko respectively. The following details only relate to ceilometer’s legacy API.

  1. We recommend that you avoid open-ended queries. In order to get better performance you can use reasonable time ranges and/or other query constraints for retrieving measurements.

    For example, this open-ended query might return an unpredictable amount of data:

    $ ceilometer sample-list --meter cpu -q 'resource_id=INSTANCE_ID_1'

    Whereas, this well-formed query returns a more reasonable amount of data, hence better performance:

    $ ceilometer sample-list --meter cpu -q 'resource_id=INSTANCE_ID_1;timestamp > 2015-05-01T00:00:00;timestamp < 2015-06-01T00:00:00'


    The number of items returned will be restricted to the value defined by default_api_return_limit in the ceilometer.conf configuration file. Alternatively, the value can be set per query by passing limit option in request.

  2. We recommend that you install the API behind mod_wsgi, as it provides more settings to tweak, like threads and processes in case of WSGIDaemon.


    For more information on how to configure mod_wsgi, see the Telemetry Install Documentation.

  3. The collection service provided by the Telemetry project is not intended to be an archival service. Set a Time to Live (TTL) value to expire data and minimize the database size. If you would like to keep your data for longer time period, you may consider storing it in a data warehouse outside of Telemetry.


    For more information on how to set the TTL, see database.

  4. We recommend that you do not run MongoDB on the same node as the controller. Keep it on a separate node optimized for fast storage for better performance. Also it is advisable for the MongoDB node to have a lot of memory.


    For more information on how much memory you need, see MongoDB FAQ.

  5. Use replica sets in MongoDB. Replica sets provide high availability through automatic failover. If your primary node fails, MongoDB will elect a secondary node to replace the primary node, and your cluster will remain functional.

    For more information on replica sets, see the MongoDB replica sets docs.

  6. Use sharding in MongoDB. Sharding helps in storing data records across multiple machines and is the MongoDB’s approach to meet the demands of data growth.

    For more information on sharding, see the MongoDB sharding docs.

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