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.
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
file to include a selected number of meters while disregarding the
rest. Similarly, in Ocata, you will need to edit
define which meters to generate.
By default, Telemetry service polls the service APIs every 10
minutes. You can change the polling interval on a per meter basis by
polling.yaml configuration file.
Prior to Ocata, the polling configuration was handled by
If the polling interval is too short, it will likely increase the stress on the service APIs.
Expand the configuration to have greater control over different meter intervals. For more information, see the Pipeline configuration.
You can delay or adjust polling requests by enabling the jitter support.
This adds a random delay on how the polling agents send requests to the
service APIs. To enable jitter, set
ceilometer.conf configuration file to an integer greater
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 see, Support for HA deployment.
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.
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.
We recommend that you install the API behind
mod_wsgi, as it provides
more settings to tweak, like
processes in case of
For more information on how to configure
mod_wsgi, see the
Telemetry Install Documentation.
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 Storing samples.
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.
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.
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.