// Module included in the following assemblies:
//
// metrics/assembly_metrics-kafka-exporter.adoc

[id='proc-kafka-exporter-enabling-{context}']

= Enabling the Kafka Exporter Grafana dashboard

Strimzi provides xref:ref-metrics-config-files-{context}[example dashboard configuration files for Grafana].
The Kafka Exporter dashboard is provided in the link:https://github.com/strimzi/strimzi-kafka-operator/tree/{GithubVersion}/examples/metrics[examples/metrics] directory as a JSON file:

* `strimzi-kafka-exporter.json`

If you deployed Kafka Exporter with your Kafka cluster, you can visualize the metrics data it exposes on the Grafana dashboard.

.Prerequisites

* Kafka is deployed with xref:proc-kafka-exporter-configuring-{context}[Kafka Exporter metrics configuration]
* xref:assembly-metrics-prometheus-{context}[Prometheus and Prometheus Alertmanager are deployed to the Kafka cluster]
* xref:proc-metrics-deploying-grafana-{context}[Grafana is deployed to the Kafka cluster]

This procedure assumes you already have access to the Grafana user interface and Prometheus has been added as a data source.
If you are accessing the user interface for the first time, see xref:assembly-metrics-grafana-{context}[Grafana].

.Procedure

. xref:proc-metrics-grafana-dashboard-{context}[Access the Grafana user interface].

. Select the _Strimzi Kafka Exporter_ dashboard.
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When metrics data has been collected for some time, the Kafka Exporter charts are populated.

Strimzi Kafka Exporter:: Shows metrics for:
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* Topic count
* Partition count
* Replicas count
* In-sync replicas count
* Under-replicated partitions count
* Partitions which are at their minimum in sync replica count
* Partitions which are under their minimum in sync replica count
* Partitions not on a preferred node
* Messages in per second from topics
* Messages consumed per second from topics
* Messages consumed per minute by consumer groups
* Lag by consumer group
* Number of partitions
* Latest offsets
* Oldest offsets

Use the Grafana charts to analyze lag and to check if actions to reduce lag are having an impact on an affected consumer group.
If, for example, Kafka brokers are adjusted to reduce lag, the dashboard will show the  _Lag by consumer group_ chart going down and the _Messages consumed per minute_ chart going up.
