Docker: How To Extract Image Filesystem Without Running Any Containers

A container image is a combination of layers where every layer represents some intermediary state of the final filesystem. Such a layered composition makes the building, storage, and distribution of images more efficient. But from a mere developer's standpoint, images are just root filesystems of our future containers. And we often want to explore their content accordingly - with familiar tools like ls, file, or tree. Let's try to see if we can achieve this goal using nothing but the means provided by Docker itself.

Container image to filesystem.

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What's Inside Of a Distroless Container Image: Taking a Deeper Look

GoogleContainerTools' distroless base images are often mentioned as one of the ways to produce small(er), fast(er), and secure(r) containers. But what are these distroless images, really? Why are they needed? What's the difference between a container built from a distroless base and a container built from scratch? Let's take a deeper look.

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In Pursuit of Better Container Images: Alpine, Distroless, Apko, Chisel, DockerSlim, oh my!

Many of us these days seem to be in pursuit of better container images. And this is for good reasons! Bloated images with many (potentially unneeded) moving parts slow down development and give more space for a CVE to sneak in. Luckily, there is a number of ways to produce slim and secure images, and everyone just needs to pick their poison a suitable one. But before doing so, it's good to become aware of a potential dissonance between what we say is important for us (securing our software supply chains) and what may actually drive our decisions (keeping out dev loops fast).

Containers - theory vs. practice.

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How Kubernetes Reinvented Virtual Machines (in a good sense)

There are lots of posts trying to show how simple it is to get started with Kubernetes. But many of these posts use complicated Kubernetes jargon for that, so even those with some prior server-side knowledge might be bewildered. Let me try something different here. Instead of explaining one unfamiliar matter (how to run a web service in Kubernetes?) with another (you just need a manifest, with three sidecars and a bunch of gobbledygook), I'll try to reveal how Kubernetes is actually a natural development of the good old deployment techniques.

If you already know how to run services using virtual machines, hopefully, you'll see that there's not much of a difference in the end. And if you're totally new to operating services at scale, following through the evolution of the technology might help you as well with the understanding of contemporary approaches.

As usual, this article is not meant to be comprehensive. Rather it's an attempt to summarize my personal experience and how my understanding of the domain has been forming over the years.

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How To Start Programming In Go: Advice For Fellow DevOps Engineers

"How to start programming in Go and for Kubernetes?" - the question I often get from fellow DevOps people. This is a tricky one. And I don't have a universal answer to it. However, I do have some thoughts to share.

But first, let me tell you my own story.

In my case, it was rather an evolutionary step - I'd been developing software for almost 10 years by the time I started coding for Kubernetes. I'd also been (sporadically) using Go for some of my server-side projects since probably 2015. And around 2019, I started my transition to, first, SRE and, then, Platform Engineering. So, when I decided to get my hands dirty with Kubernetes controllers, it was just a matter of joining the right team and picking up the Kubernetes domain. Luckily, I had a good candidate on my radar, and that required just an internal transition from one team to another.

However, based on my observations, for many contemporary DevOps engineers, the direction of the desired transformation is often inverse. From Ops to Dev (preferably, for Ops).

Since your background and experience may vary, instead of giving a concrete piece of advice here, I'll try to explain how I'd approach the problem given different levels of proficiency with the technologies.

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