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.
The difference between continuous integration, delivery, and deployment is not in processes, but in the level of confidence we have in them.
The continuous deployment process is relatively easy to explain, even though implementation might get tricky. We’ll split our requirements into two groups. We’ll start with a discussion about the overall goals that should be applied to the whole process. To be more precise, we’ll talk about what I consider non-negotiable requirements.