When Jenkins appeared, its pipelines were called FreeStyle jobs. There was no way to describe them in code, and they were not kept in version control. We were creating and maintaining those jobs through Jenkins UI by filling input fields, marking checkboxes, and selecting values from drop-down lists. The results were impossible-to-read XML files stored in the Jenkins home directory. Nevertheless, that approach was so great (compared to what existed at the time) that Jenkins become widely adopted overnight. But, that was many years ago and what was great over a decade ago is not necessarily as good today. As a matter of fact, FreeStyle jobs are the antithesis of the types of jobs we should be writing today. Tools that create code through drag-and-drop methods are extinct. Not having code in version control is a cardinal sin. Not being able to use our favorite IDE or code editor is unacceptable. Hence, the Jenkins community created Jenkins pipelines.
Jenkins X main logic is based on applying GitOps principles. Every change must be recorded in Git, and only Git is allowed to initiate events that result in changes in our clusters. That logic is the cornerstone of Jenkins X, and it served us well so far. However, there are actions we might need to perform that do not result in changes to the source code or configurations. Hence the emergence of ChatOps.
The serverless flavor of Jenkins X or, as some call it, Jenkins X Next Generation, is an attempt to redefine how we do continuous delivery and GitOps inside Kubernetes clusters. It does that by combining quite a few tools into a single easy-to-use bundle. As a result, most people will not have a need to understand intricacies of how the pieces work independently, nor how they are all integrated. Instead, many will merely push a change to Git and let the system do the rest. But, there are always those who would like to know what's happening behind the hood. To satisfy those craving for insight, we'll explore the processes and the components involved in the serverless Jenkins X platform. Understanding the flow of an event initiated by a Git webhook will give us insight into how the solution works and help us later on when we go deeper into each of the new components.
Pull Requests (or whatever their equivalents are called in your favorite Git distribution) are a norm. Most of us adopted them as the primary way of reviewing and accepting changes that will ultimately be deployed to production. They work hand-in-hand with feature branches.
I stand by my claim that "you do not need to understand Kubernetes to use Jenkins X." To be more precise, those who do not want to know Kubernetes and its ecosystem in detail can benefit from Jenkins X ability to simplify the processes around software development lifecycle. That's the promise or, at least, one of the driving ideas behind the project. Nevertheless, for that goal to reach as wide of an audience as possible, we need a variety of build packs. The more we have, the more use cases can be covered with a single
jx import or
jx quickstart command. The problem is that there is an infinite number of types of applications and combinations we might have. Not all can be covered with community-based packs. No matter how much effort the community puts into creating build packs, they will always be a fraction of what we might need. That's where you come in.
To understand intricacies and inner workings of Jenkins X, we need to understand Kubernetes. But, you do not need to understand Kubernetes to use Jenkins X. That is one of the main contributions of the project. Jenkins X allows us to harness the power of Kubernetes without spending eternity learning the ever-growing list of the things it does. Jenkins X helps us by simplifying complex processes into concepts that can be adopted quickly and without spending months in trying to figure out "the right way to do stuff." It helps by removing and simplifying some of the problems caused by the overall complexity of Kubernetes and its ecosystem. If you are indeed a Kubernetes ninja, you will appreciate all the effort put into Jenkins X. If you're not, you will be able to jump right in and harness the power of Kubernetes without ripping your hair out of frustration caused by Kubernetes complexity.
When I finished the last book (The DevOps 2.5 Toolkit: Monitoring, Logging, and Auto-Scaling Kubernetes), I wanted to take a break from writing for a month or two. I thought that would clear my mind and help me decide which subject to tackle next. Those days were horrible. I could not make up my mind. So many cool and useful tech is emerging and being adopted. I was never as undecided as those weeks. Which should be my next step?
I could explore serverless. That's definitely useful, and it might be considered the next big thing. Or I could dive into Istio. It is probably the biggest and the most important project sitting on top of Kubernetes. Or I could tackle some smaller subjects. Kaniko is the missing link in continuous delivery. Building containers might be the only thing we still do on the host level, and Kaniko allows us to move that process inside containers. How about security scanning? It is one of the things that are mandatory in most organizations, and yet I did not include it in "The DevOps 2.4 Toolkit: Continuous Deployment To Kubernetes". Then there is skaffold, prow, KNative, and quite a few other tools that are becoming stable and very useful.
Let's paint a high-level picture of the continuous delivery pipeline. To be more precise, we'll draw a diagram instead of painting anything. But, before we dive into a continuous delivery diagram, we'll refresh our memory with the one we used before for describing continuous deployment.
The continuous deployment pipeline contains all the steps from pushing a commit to deploying and testing a release in production.
Continuous delivery removes one of the stages from the continuous deployment pipeline. We do NOT want to deploy a new release automatically. Instead, we want humans to decide whether a release should be upgraded in production. If it should, we need to decide when will that happen. Those (human) decisions are, in our case, happening as Git operations. We'll comment on them soon. For now, the important note is that the deploy stage is now removed from pipelines residing in application repositories.
Explaining continuous deployment (CDP) is easy. Implementing it is very hard, and the challenges are often hidden and unexpected. Depending on the maturity of your processes, architecture, and code, you might find out that the real problems do not lie in the code of a continuous deployment pipeline, but everywhere else. As a matter of fact, developing a pipeline is the easiest part.
This article is an excerpt from The DevOps 2.4 Toolkit: Continuous Deployment To Kubernetes. It assumes that you already have a Kubernetes cluster with nginx Ingress. The article was tested with minikube, minishift, Docker for Mac/Windows, AWS with kops, and GKE. Furthermore, I will assume that you already installed Helm. Finally, I expect you to clone vfarcic/k8s-specs and execute the commands from inside it.
First things first... We need to find out the IP of our cluster or external LB if available. The commands that follow will differ from one cluster type to another.