Warning: This document is for the development version of Gnocchi. The latest version is 3.1.3.

Running Gnocchi

To run Gnocchi, simply run the HTTP server and metric daemon:


Running API As A WSGI Application

The Gnocchi API tier runs using WSGI. This means it can be run using Apache httpd and mod_wsgi, or other HTTP daemon such as uwsgi. You should configure the number of process and threads according to the number of CPU you have, usually around 1.5 × number of CPU. If one server is not enough, you can spawn any number of new API server to scale Gnocchi out, even on different machines.

The following uwsgi configuration file can be used:

http = localhost:8041
# Set the correct path depending on your installation
wsgi-file = /usr/lib/python2.7/dist-packages/gnocchi/rest/app.wsgi
master = true
die-on-term = true
threads = 32
# Adjust based on the number of CPU
processes = 32
enabled-threads = true
thunder-lock = true
plugins = python
buffer-size = 65535
lazy-apps = true

Once written to /etc/gnocchi/uwsgi.ini, it can be launched this way:

uwsgi /etc/gnocchi/uwsgi.ini

How to define archive policies

In Gnocchi, the archive policy definitions are expressed in number of points. If your archive policy defines a policy of 10 points with a granularity of 1 second, the time series archive will keep up to 10 seconds, each representing an aggregation over 1 second. This means the time series will at maximum retain 10 seconds of data (sometimes a bit more) between the more recent point and the oldest point. That does not mean it will be 10 consecutive seconds: there might be a gap if data is fed irregularly.

There is no expiry of data relative to the current timestamp.

Therefore, both the archive policy and the granularity entirely depends on your use case. Depending on the usage of your data, you can define several archiving policies. A typical low grained use case could be:

3600 points with a granularity of 1 second = 1 hour
1440 points with a granularity of 1 minute = 24 hours
720 points with a granularity of 1 hour = 30 days
365 points with a granularity of 1 day = 1 year

This would represent 6125 points × 9 = 54 KiB per aggregation method. If you use the 8 standard aggregation method, your metric will take up to 8 × 54 KiB = 432 KiB of disk space.

Be aware that the more definitions you set in an archive policy, the more CPU it will consume. Therefore, creating an archive policy with 2 definitons (e.g. 1 second granularity for 1 day and 1 minute granularity for 1 month) may consume twice CPU than just one definition (e.g. just 1 second granularity for 1 day).

Default archive policies

By default, 3 archive policies are created when calling gnocchi-upgrade: low, medium and high. The name both describes the storage space and CPU usage needs. They use default_aggregation_methods which is by default set to mean, min, max, sum, std, count.

A fourth archive policy named bool is also provided by default and is designed to store only boolean values (i.e. 0 and 1). It only stores one data point for each second (using the last aggregation method), with a one year retention period. The maximum optimistic storage size is estimated based on the assumption that no other value than 0 and 1 are sent as measures. If other values are sent, the maximum pessimistic storage size is taken into account.

  • low
    • 5 minutes granularity over 30 days
    • aggregation methods used: default_aggregation_methods
    • maximum estimated size per metric: 406 KiB
  • medium
    • 1 minute granularity over 7 days
    • 1 hour granularity over 365 days
    • aggregation methods used: default_aggregation_methods
    • maximum estimated size per metric: 887 KiB
  • high
    • 1 second granularity over 1 hour
    • 1 minute granularity over 1 week
    • 1 hour granularity over 1 year
    • aggregation methods used: default_aggregation_methods
    • maximum estimated size per metric: 1 057 KiB
  • bool * 1 second granularity over 1 year * aggregation methods used: last * maximum optimistic size per metric: 1 539 KiB * maximum pessimistic size per metric: 277 172 KiB

How many metricd workers do we need to run

By default, gnocchi-metricd daemon spans all your CPU power in order to maximize CPU utilisation when computing metric aggregation. You can use the gnocchi status command to query the HTTP API and get the cluster status for metric processing. It’ll show you the number of metric to process, known as the processing backlog for gnocchi-metricd. As long as this backlog is not continuously increasing, that means that gnocchi-metricd is able to cope with the amount of metric that are being sent. In case this number of measure to process is continuously increasing, you will need to (maybe temporarily) increase the number of gnocchi-metricd daemons. You can run any number of metricd daemon on any number of servers.

How to monitor Gnocchi

The /v1/status endpoint of the HTTP API returns various information, such as the number of measures to process (measures backlog), which you can easily monitor (see How many metricd workers do we need to run). Making sure that the HTTP server and gnocchi-metricd daemon are running and are not writing anything alarming in their logs is a sign of good health of the overall system.

Total measures for backlog status may not accurately reflect the number of points to be processed when measures are submitted via batch.

How to backup and restore Gnocchi

In order to be able to recover from an unfortunate event, you need to backup both the index and the storage. That means creating a database dump (PostgreSQL or MySQL) and doing snapshots or copy of your data storage (Ceph, S3, Swift or your file system). The procedure to restore is no more complicated than initial deployment: restore your index and storage backups, reinstall Gnocchi if necessary, and restart it.