Engineering teams are rapidly embracing ephemeral environments. These short-lived, on-demand environments offer a game-changer for developers, accelerating workflows and boosting efficiency. However, with a variety of ephemeral environment tools available, choosing the right one can feel like navigating a maze. Today, I’m sharing a detailed assessment checklist for Ephemeral Environment tools.

Kubernetes has emerged as the clear cornerstone for orchestrating containerized applications. However, alongside its numerous benefits, Kubernetes introduces its own set of complexities, particularly in monitoring and managing costs. The dynamic nature of Kubernetes — where resources can be scaled up or down in response to demand — makes traditional cost monitoring methods inadequate.

Explore the best strategies for implementing automated testing in CI/CD pipelines to streamline your development process and ensure high-quality software delivery.

In the previous article of the series we explained how to model GitOps environments and promote an application between them. That article was laser-focused on a single application and its Kubernetes resources. In this article we will zoom out to look at several related subjects: It is worth mentioning that as always, our advice is a general recommendation that follows best practices.

Calico 3.28 now has enabled VXLAN checksum offload by default for environments with the kernel version of 5.8 or above. In the past, offloading was disabled due to kernel bugs. Please keep in mind, if you are upgrading to 3.28 this change will take effect after node restarts.

In the fast-paced world of software development, efficiency is key. One of the most critical aspects of ensuring smooth and reliable software delivery is streamlining your deployment pipeline. A well-optimized deployment pipeline not only saves time and resources but also enhances the overall quality of your product. Let’s embark on a DevOps journey to explore how you can streamline your deployment pipeline effectively.

In Kubernetes a static pod is a concept where you can deploy a pod that is not managed by the API server. Static pods are directly managed by the Kubelet component. The Kubelet service is deployed with the configuration path where we can add the pod manifest for the Kubelet to deploy. Even though a static pod is not managed by the API server, you can use Kubectl to list the static pod. This is because, when Kubelet deploys a static pod, it creates a mirror pod in the API server.

Log analysis is a very powerful feature for an application when it comes to debugging and finding out which flow is working properly in the application and which is not. In a world of containerization and cloud computing, it is essential to understand logs generated by a Docker environment to maintain healthy performing applications. In this article, we will discuss log analysis in Docker and how logging in Docker containers is different than in other applications.

Logs are useful for troubleshooting and identifying issues in applications, as they provide a record of events and activities. However, managing log data can be challenging due to the large volume of log events generated by modern applications, as well as the need to balance the level of detail in the logs and the impact on the application's performance.