This documentation gives you some clues on how to write a new agent or plugin for Ceilometer if you wish to instrument a measurement which has not yet been covered by an existing plugin.
The compute agent runs on each compute node to poll for resource usage. Each metric collected is tagged with the resource ID (such as an instance) and the owner, including tenant and user IDs. The metrics are then reported to the collector via the message bus. More detailed information follows.
The compute agent is implemented in ceilometer/compute/manager.py. As you will see in the manager, the computeagent loads all plugins defined in the namespace ceilometer.poll.compute, then periodically calls their get_samples() method.
The central agent polls other types of resources from a management server. The central agent is defined in ceilometer/central/manager.py. It loads plugins from the ceilometer.poll.central namespace and polls them by calling their get_samples() method.
An agent can support multiple plugins to retrieve different information and send them to the collector. As stated above, an agent will automatically activate all plugins of a given class. For example, the compute agent will load all plugins of class ceilometer.poll.compute. This will load, among others, the ceilometer.compute.pollsters.CPUPollster, which is defined in the file ceilometer/compute/pollsters.py as well as the ceilometer.compute.notifications.InstanceNotifications plugin which is defined in the file ceilometer/compute/notifications.py
We are using these two existing plugins as examples as the first one provides an example of how to interact when you need to retrieve information from an external system (pollster) and the second one is an example of how to forward an existing event notification on the standard OpenStack queue to ceilometer.
Compute plugins are defined as subclasses of the ceilometer.compute.plugin.ComputePollster class as defined in the ceilometer/compute/plugin.py file. Pollsters must implement one method: get_samples(self, manager, context), which returns a sequence of Sample objects as defined in the ceilometer/sample.py file.
In the CPUPollster plugin, the get_samples method is implemented as a loop which, for each instances running on the local host, retrieves the cpu_time from the hypervisor and sends back two Sample objects. The first one, named “cpu”, is of type “cumulative”, meaning that between two polls, its value is not reset, or in other word that the cpu value is always provided as a duration that continuously increases since the creation of the instance. The second one, named “cpu_util”, is of type “gauge”, meaning that its value is the percentage of cpu utilization.
Note that the LOG method is only used as a debugging tool and does not participate in the actual metering activity.
Notifications are defined as subclass of the ceilometer.plugin.NotificationBase meta class as defined in the ceilometer/plugin.py file. Notifications must implement:
event_types which should be a sequence of strings defining the event types to be given to the plugin and
process_notification(self, message) which receives an event message from the list provided to event_types and returns a sequence of Sample objects as defined in the ceilometer/sample.py file.
In the InstanceNotifications plugin, it listens to three events:
using the get_event_type method and subsequently the method process_notification will be invoked each time such events are happening which generates the appropriate sample objects to be sent to the collector.
Any new plugin or agent contribution will only be accepted into the project if provided together with unit tests. Those are defined for the compute agent plugins in the directory tests/compute and for the agent itself in test/agent. Unit tests are run in a continuous integration process for each commit made to the project, thus ensuring as best as possible that a given patch has no side effect to the rest of the project.