Overview

This repo demonstrates examples of JMX monitoring stacks that can monitor Confluent Cloud and Confluent Platform. While Confluent Cloud UI and Confluent Control Center provides an opinionated view of Apache Kafka monitoring, JMX monitoring stacks serve a larger purpose to our users, allowing them to setup monitoring across multiple parts of their organization, many outside of Kafka, and to have a single pane of glass.

This project provides metrics and dashboards for:

📊 Dashboards

Some examples:

List of available dashboards for Confluent Platform:

Dashboard	Prometheus and Grafana	New Relic	Metricbeat and Kibana	Telegraf and Influx	Datadog
Kafka Cluster	yes	yes	yes	yes	yes
Zookeeper	yes	yes	yes
KRaft	yes
Schema Registry	yes		yes
Kafka Connect	yes		yes
ksqlDB	yes		yes
Producer/Consumer	yes	yes	yes		yes
Lag Exporter	yes
Topics	yes		yes
Kafka Streams	yes
Kafka Streams RocksDB	yes
Quotas	yes
TX Coordinator	yes
Rest Proxy	yes
Cluster Linking	yes
Oracle CDC	yes
Confluent RBAC	yes
Replicator	yes
Tiered Storage	yes

List of available dashboards for Confluent Cloud:

Dashboard	Prometheus and Grafana	New Relic	Metricbeat and Kibana
Cluster	yes	yes	yes
Producer/Consumer			yes
ksql	yes
Billing/Cost tracking	yes

⚠️ Alerts

Alerts are available for the stacks:

jmxexporter-prometheus-grafana including alerts on broker, zookeeper and kafka connect.

How to use with Confluent cp-ansible

To add JMX exporter configurations to Confluent cp-ansible, please refer to this README

How to use with Kubernetes and Confluent for Kubernetes Operator (CFK)

To add JMX exporter configurations to your Kubernetes workspace, please refer to this README

How to use with Confluent cp-demo

This repo is intended to work smoothly with Confluent cp-demo.

Make sure you have enough system resources on the local host to run this. Verify in the advanced Docker preferences settings that the memory available to Docker is at least 8 GB (default is 2 GB).

NOTE: jq is required to be installed on your machine to run the demo.

Ensure that cp-demo is not already running on the local host.
Decide which monitoring stack to demo: and set the MONITORING_STACK variable accordingly.

NOTE: New Relic requires a License Key to be added in jmxexporter-newrelic/start.sh

NOTE: Datadog requires a DATADOG_API_KEY and DATADOG_SITE to be added in datadog/start.sh. Datadog offers 14 day trial for new users.

# Set only one of these
MONITORING_STACK=jmxexporter-prometheus-grafana
MONITORING_STACK=metricbeat-elastic-kibana
MONITORING_STACK=jmxexporter-newrelic
MONITORING_STACK=jolokia
MONITORING_STACK=jolokia-telegraf-influxdb
MONITORING_STACK=datadog

Clone cp-demo and checkout a branch.

# Example with CP-DEMO 7.6.1 version (all branches starting from 7.2.0 have been tested)
CP_DEMO_VERSION=7.6.1-post

[[ -d "cp-demo" ]] || git clone https://github.com/confluentinc/cp-demo.git
(cd cp-demo && git fetch && git checkout $CP_DEMO_VERSION && git pull)

Clone jmx-monitoring-stacks and checkout main branch.

[[ -d "jmx-monitoring-stacks" ]] || git clone https://github.com/confluentinc/jmx-monitoring-stacks.git
(cd jmx-monitoring-stacks && git fetch && git checkout main && git pull)

Start the monitoring solution with the STACK selected. This command also starts cp-demo, you do not need to start cp-demo separately.

${MONITORING_STACK}/start.sh

Stop the monitoring solution. This command also stops cp-demo, you do not need to stop cp-demo separately.

${MONITORING_STACK}/stop.sh

How to use with Apache Kafka client applications (producers, consumers, kafka streams applications)

For an example that showcases how to monitor Apache Kafka client applications, and steps through various failure scenarios to see how they are reflected in the provided metrics, see the Observability for Apache Kafka® Clients to Confluent Cloud tutorial.

How to use with a minimal configuration: DEV-toolkit

To run a lightweight dev environment:

cd dev-toolkit
Put your new dashboards into the grafana-wip folder
start.sh -> It will create a minimal environment with a KRaft cluster, prometheus, grafana and a spring based java client
For Grafana, go to http://localhost:3000, login with admin/password
stop.sh

Run with profiles

To add more use cases, we are leveraging the docker profiles.

To run replicator scenario, i.e. start.sh --profile replicator. It's possible to combine profiles as well, i.e. start.sh --profile schema-registry --profile ksqldb.

Currently supported profiles:

replicator
schema-registry
ksqldb
consumer (with kafka-lag-exported included)

FAQ

What if I need more components?

More docker-compose envs will be released in the future, in the meantime you can use Kafka Docker Composer

What if I need more prometheus jobs?

You can add them to the start.sh, i.e.

# ADD client monitoring to prometheus config
cat <<EOF >> assets/prometheus/prometheus-config/prometheus.yml

  - job_name: 'spring-client'
    static_configs:
      - targets: ['spring-client:9191']
        labels:
          env: "dev"
EOF

You can also change the prometheus configuration here.

License

confluentinc/jmx-monitoring-stacks

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