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Tag: logstash

Dockerizing Jenkins build logs with ELK stack (Filebeat, Elasticsearch, Logstash and Kibana)

This is 4th part of Dockerizing Jenkins series, you can find more about previous parts here:

Dockerizing Jenkins, Part 1: Declarative Build Pipeline With SonarQube Analysis
Dockerizing Jenkins, part 2: Deployment with maven and JFrog Artifactory
Dockerizing Jenkins, part 3: Securing password with docker-compose, docker-secret and jenkins credentials plugin

Today we are going to look at managing the Jenkins build logs in a dockerized environment.

Normally, in order to view the build logs in Jenkins, all you have to do is to go to particular job and check the logs. Depending on a log rotation configuration, the logs could be saved for N number of builds, days, etc, meaning the old jobs logs will be lost.

Our aim in this article will be persisting the logs in a centralised fashion, just like any other application logs, so it could be searched, viewed and monitored from single location.

We also will be running Jenkins in Docker, meaning if container is dropped and no other means are in place, like mounting the volume for logs from a host and taking the backup the logs will be lost.

As you may have already heard, one of the best solutions when it comes to logging is called ELK stack.

The Idea with ELK stack is you collect logs with Filebeat(or any other *beat), parse, filter logs with longstash and then send them to elasticsearch for persistence, and then view them in kibana.

On top of that, because logstash is heavyweight jruby app on JVM , you either skip it at all or use a way smaller application called Filebeat, which is a logstash log forwarder, all it does, collects the logs and sends to longstash for further processing.

In fact, if you don’t have any filtering and parsing requirements you can skip the logstash at all and use Filebeat’s elastic output for sending the logs directly to elasticsearch.

In our example we will try to use all of them, plus, we won’t be running Filebeat in a separate container, but instead, will install it right inside of our Jenkins image, because Filebeat is small enough. I also wanted to demonstrate how we can install anything on our Jenkins image, so it is more interesting.

So the summary of what we are going to look at today is:

  1. Prepare our dockerized dev environment with Jenkins, Sonarqube and JFrog artifactory running the declarative pipeline
  2. Download and install Filebeat on our Jenkins image
  3. Configure Filebeat so it knows how and where collect the Jenkins logs and how to send them further to logstash
  4. Configure and run logstash in a docker container
  5. Configure and run elasticsearch in a docker container
  6. Configure and run kibana in a docker container

1. Prepare our dockerized dev environment with Jenkins, Sonarqube and JFrog artifactory running the declarative pipeline

In this example we will use Jenkins image we created earlier in the part 3 of these series. First thing first, let’s checkout the project:

git clone && \
   cd dockerizing-jenkins && \
   git checkout dockerizing_jenkins_part_3_docker_compose_docker_secret_credentials_plugin && \

Let’s see what does:

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