At the Jenkins user conference in London this year I stumbled into what turned out to be the most interesting session to my mind, From Virtual Machines to Containers: Achieving Continuous Integration, Build Reproducibility, Isolation and Scalability (a mouthful), from folks at a software shop by the name of Camunda.
The key aspect of this talk was the extension of the “code-as-configuration” model to nearly the entire Jenkins installation. Starting from a chaotic set of hundreds of hand-maintained jobs, corresponding to many product versions tested across various environmental combinations (I suppose beyond the abilities of the Matrix Project plugin to handle naturally), they wanted to move to a more controlled and reproducible definition.
Many people have long recognized the need to keep job configuration in regular project source control rather than requiring it to be stored in $JENKINS_HOME (and, worse, edited from the UI). This has led to all sorts of solutions, including the Literate plugin a few years back, and now various initialization modes of Workflow that I am working on, not to mention the Templates plugin in CloudBees Jenkins Enterprise.
In the case of Camunda they went with the Job DSL plugin, which has the advantage of being able to generate a variable number of job definitions from one script and some inputs (it can also interoperate meaningfully with other plugins in this space). This plugin also provides some opportunity for unit-testing its output, and interactively examining differences in output from build to build (harking back to a theme I encountered at JUC East).
They took the further step of making the entire Jenkins installation be stood up from scratch in a Docker container from a versioned declaration, including pinned plugin versions. This is certainly not the first time I have heard of an organization doing that, but it remains unusual. (What about Credentials, you might ask? I am guessing they have few real secrets, since for reproducibility and scalability they are also using containerized test environments, which can use dummy passwords.)
As a nice touch, they added Elasticsearch/Kibana statistics for their system, including Docker image usage and reports on unstable (“flaky”?) tests. CloudBees Jenkins Operations Center customers would get this sort of functionality out of the box, though I expect we need to expand the data sources streamed to CJOC to cover more domains of interest to developers. (The management, as opposed to reporting/analysis, features of CJOC are probably unwanted if you are defining your Jenkins environment as code.)
One awkward point I saw in their otherwise impressive setup was the handling of Docker images used for isolated build environments. They are using the Docker plugin’s cloud provider to offer elastic agents according to a defined image, but since different jobs need different images, and cloud definitions are global, they had to resort to using (Groovy) scripting to inject the desired cloud configurations. More natural is to have a single cloud that can supply a generic Docker-capable agent (the agent agent itself can also be inside a Docker container), where the job directly requests a particular image for its build steps. The CloudBees Docker Custom Build Environment plugin can manage this, as can the CloudBees Docker Workflow plugin my team worked on recently. Full interoperation with Swarm and Docker Machine takes a bit more work; my colleague Nicolas de Loof has been thinking about this.
The other missing piece was fully automated testing of the system, particularly Jenkins plugin updates. For now it seems they prototype such updates manually in a temporary copy of the infrastructure, using a special environment variable as a “dry-run” switch to prevent effects from leaking into the outside world. (Probably Jenkins should define an API for such a switch to be interpreted by popular plugins, so that the SMTP code in the Mailer plugin would print a message to some log rather than really sending mail, etc.) It would be great to see someone writing tests atop the Jenkins “acceptance test harness” to validate site-specific functions, with a custom launcher for their Jenkins service.
All told, a thought-provoking presentation, and I hope to see a follow-up next year with their next steps!
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