One of the main drivers behind Kubernetes’ success is the ability to manage containerised workloads and services by specifying a declarative configuration and letting the system make it happen. This effectively automates and abstracts away all those tedious and error-prone step-by-step deployment tasks usually known as ‘operations’.

First, some good news: the DevOps field’s expertise and performance is growing rapidly. Its best practices, like a clear change-approval process, not only improve speed and stability, but also help decrease engineer burnout.

Debugging Docker containers can be a very challenging process. Here, I’ll share a few basic techniques for debugging containers—mostly Docker ones, but the techniques are also valid for many other types of Linux container engines. (The methods I’ll detail here are intended for Linux-based systems.)

Linux capabilities, and how they interact with users and containers, can confuse even experienced engineers. At first it seems like this is fairly straightforward stuff, but it gets complex quickly and the information on exactly what is going on is scattered across many pages, Git repos and blogs, so it can be hard to piece together.

If you’re an engineer working with containers, and especially with Kubernetes, you’re going to hear about Istio. For the uninitiated, Istio is the service mesh for Kubernetes. A service mesh is a networking layer that allows you to dynamically manage service traffic, and do so in a safe and well-defined way.