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Overview

This repo demonstrates examples of JMX monitoring stacks that can monitor Confluent Platform. While 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.

Caution

The examples in this repo may not be complete and are for testing purposes only. They serve only to demonstrate how the integration works with Confluent Platform.

Run

This repo is intended to be run specifically with 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).

  1. Ensure that cp-demo is not already running on the local host.

  2. Decide which monitoring stack to demo: either jmxexporter-prometheus-grafana or jolokia-elastic-kibana, and set the STACK variable accordingly.

# Set one of these
STACK=jmxexporter-prometheus-grafana
STACK=jolokia-elastic-kibana
  1. Clone cp-demo and checkout 5.5.0-post (this has been validated only with cp-demo in the 5.5.0-post branch).
[[ -d "cp-demo" ]] || git clone https://github.com/confluentinc/cp-demo.git
(cd cp-demo && git fetch && git checkout 5.5.0-post && git pull)
  1. Clone jmx-monitoring-stacks and checkout a compatible release.
[[ -d "jmx-monitoring-stacks" ]] || git clone https://github.com/confluentinc/jmx-monitoring-stacks.git
(cd jmx-monitoring-stacks && git fetch && git checkout 5.5.0-post && git pull)
  1. Start the monitoring solution with the STACK selected. This command also starts cp-demo, you do not need to start cp-demo separately.
${STACK}/start.sh
  1. Stop the monitoring solution. This command also stops cp-demo, you do not need to stop cp-demo separately.
${STACK}/stop.sh

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  • Python 74.4%
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