werf is designed to glue together Git, Docker, Helm, and Kubernetes. It is meant to be used in CI/CD pipelines. Let’s see whether it can be helpful to manage our k8s applications.
Continue readingChat is continuous integration (CI), continuous delivery (CD), continuous deployment (CDP), and continuous testing (CT)? How do they differ from each other? Which one should we use?
Continue readingArgo Workflows & Pipelines is an open source container-native workflow engine for orchestrating parallel jobs on Kubernetes. It is a cloud-native solution designed from ground-up for Kubernetes.
Since the increase in popularity of continuous delivery (CD), there was an increase in the number of tools marketed as CD solutions. That’s normal. It is only natural for software vendors to ride the waves. They need to sell, and there’s nothing better to sell than whatever is popular at a given moment. Continuous delivery is one of those "popular" waves.
A video version of the same post is available in The DevOps Toolkit Series YouTube channel.
On the surface, there is nothing wrong with buying tools that solve problems. You have a problem, a vendor has a solution, you buy it, they earn money, and you have a good return on investment. Everybody wins, except when the tool does not do what it’s supposed to do. That’s when we run into issues.
The video below is a clip from the "Canary Deployments To Kubernetes Using Istio and Friends" course in Udemy. It provides the introduction to the course we released in December 2019. Additional preview clips are available inside the course. Please use the coupons with discounts provided below.
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Welcome to practical guide to canary deployments. Unlike some other work that I did…tutorials, workshops, and so on and so forth, that were very focused on a single tool, this time I will focus more on a process.
We’re going to try to figure out how to do canary deployments inside of Kubernetes. Because Kubernetes is everywhere now, I will assume that you are using Kubernetes. But outside of that, we are going to try to figure out which tools to use, but all serving as the process itself, not for the sake of learning a specific tool. And during that process, we are going to decide which tools to use and why to use them and the end result will be a fully operational canary deployments process that you will be able to plug into any CI/CD tool or any tool that orchestrates the lifecycle of your application.
So we will definitely choose some tools that we will use in a process.
And those tools will be revolving around Istio. I will explain why Istio a bit later.
So we will use Kubernetes and Istio for canary deployments, but the end result will be agnostic to the tool that will orchestrate your processes. We will most likely also have to choose one or two additional tools. Which tools we’ll choose is yet to be discovered.
For now just think of this as being a practical guide to a specific process. And that process today is canary deployments in Kubernetes.
A while ago, we (Viktor Farcic and Darin Pope) thought it would be a good idea to add an out-of-the-box option to use canary deployments in Jenkins X. We should have finished it by now, and yet we did not even start working on it. Instead of just adding it to Jenkins X, we spent considerable time exploring the subject.
After nine months of work, I managed to finish the latest book in The DevOps Toolkit Series. We’re at the seventh book, and this time it’s all about Jenkins X.
The book is called The DevOps 2.6 Toolkit: Jenkins X and the following few paragraphs is how it starts.
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.
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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.
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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.
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