When operating a distributed system like Zeebe, it is important to put proper monitoring in place. To facilitate this, Zeebe exposes an extensive set of metrics.
Zeebe exposes metrics over an embedded HTTP server.
- Counters: a time series that records a growing count of some unit. Examples: number of bytes transmitted over the network, number of workflow instances started, ...
- Gauges: a time series that records the current size of some unit. Examples: number of currently open client connections, current number of partitions, ...
Zeebe exposes metrics directly in Prometheus text format. The details of the format can be read in the Prometheus documentation.
The HTTP server to export the metrics can be configured in the configuration file.
As explained, Zeebe exposes the metrics over a HTTP server. The default port is
Add the following entry to your
All Zeebe related metrics have a
Most metrics have the following common label:
partition: cluster-unique id of the partition
Metrics related to workflow processing:
zeebe_stream_processor_events_total: The number of events processed by the stream processor. The
actionlabel separates processed, skipped and written events.
zeebe_exporter_events_total: The number of events processed by the exporter processor. The
actionlabel separates exported and skipped events.
zeebe_element_instance_events_total: The number of occurred workflow element instance events. The
actionlabel separates the number of activated, completed and terminated elements. The
typelabel separates different BPMN element types.
zeebe_running_workflow_instances_total: The number of currently running workflow instances, i.e. not completed or terminated.
zeebe_job_events_total: The number of job events. The
actionlabel separates the number of created, activated, timed out, completed, failed and canceled jobs.
zeebe_pending_jobs_total: The number of currently pending jobs, i.e. not completed or terminated.
zeebe_incident_events_total: The number of incident events. The
actionlabel separates the number of created and resolved incident events.
zeebe_pending_incidents_total: The number of currently pending incident, i.e. not resolved.
Metrics related to performance:
Zeebe has a back-pressure mechanism by which it rejects requests, when it receives more requests than it can handle with out incurring high processing latency. The following metrics can be used to monitor back-pressure and processing latency of the commands.
zeebe_dropped_request_count_total: The number of user requests rejected by the broker due to backpressure.
zeebe_backpressure_requests_limit: The limit for the number of inflight requests used for backpressure.
zeebe_stream_processor_latency_bucket: The processing latency for commands and event.
Metrics related to health:
The health of partitions in a broker can be monitored by the metric
Zeebe comes with a pre-built dashboard, available in the repository: monitor/grafana/zeebe.json
Import it into your Grafana instance, then select the correct Prometheus data source (important if you have more than one), and you should be greeted with the following dashboard: