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. 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. 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. 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. 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.Īs you may have already heard, one of the best solutions when it comes to logging is called ELK stack. 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. 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. 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. Today we are going to look at managing the Jenkins build logs in a dockerized environment. This is 4th part of Dockerizing Jenkins series, you can find more about previous parts here:ĭockerizing Jenkins, Part 1: Declarative Build Pipeline With SonarQube Analysisĭockerizing Jenkins, part 2: Deployment with maven and JFrog Artifactoryĭockerizing Jenkins, part 3: Securing password with docker-compose, docker-secret and jenkins credentials plugin
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