As AI and machine learning workloads continue to grow in complexity and size, the need for efficient and scalable infrastructure becomes more important than ever. In this tutorial, I will show you how to deploy AI applications on AWS Elastic Kubernetes Service (EKS) with Karpenter from scratch, leveraging GPU resources for high-performance computing.

Kubernetes is very straightforward for deploying and managing stateless applications. Consequently, proper backups of the Kubernetes environment have often been postponed or neglected. Today, however, more and more applications running on Kubernetes are stateful, making backup and recovery solutions for these systems critical. Neglecting backup is risky: as applications become more complex and need to preserve their states, the challenges of recovering a setup increase.

Kubernetes annotations are key-value pairs attached to Kubernetes objects, providing a flexible way to extend the functionality of your Kubernetes resources without altering their internal specifications. These annotations serve as a tool to store additional metadata to tailor behavior, orchestrate tools, and interact seamlessly with third-party utilities that complement your Kubernetes environment.

ZenOps and StackState announce a partnership for the distribution in France of StackState solutions for Kubernetes problem detection and resolution, observability of containerized environments and application performance management. ZenOps will be able to offer these solutions to enterprises and the public sector, drawing on its technical expertise in cloud-native approaches and providing first-level support.

Deploying software to your internal systems or sending releases to external customers is a process that ideally follows strong security requirements in an end-to-end manner. In a perfect world, every software release should come with at least the following guarantees In the world of CI/CD we are mostly interested in binary artifacts and how they were created all the way from the initial release up until they reach production.

In the last years, Kubernetes has grown tremendously and is considered by most companies to be the best platform to run applications today. In simple words, Kubernetes is an open-source container orchestration platform that allows you to run and manage containerized applications at scale. In this article, I will explain how you can run Kubernetes on AWS in 3 different ways. But before getting down the road, let me explain why it does make sense to run Kubernetes on AWS.

When deploying an application using Kubernetes, you get used to all your resources being manageable by describing them to the Kubernetes API. Whether it’s deployments, secrets, configurations, or entire machines, everything exists as code somewhere. Introducing a cloud service into such an environment often means introducing additional ways to configure it, which can become cumbersome, given the rising number of cloud services modern applications depend on.

Monitoring tools are critical for DevOps, enabling them to quickly find and rectify performance issues. With the increasing popularity of Docker, it has become crucial that organizations can effectively monitor these containers. But, as monitoring Docker containers is particularly complex, developing a strategy and an appropriate monitoring system is not simple. However, this process can be streamlined by utilizing a Docker monitoring tool.

KubeCon Europe 2024 in Paris was the biggest event of the Cloud Native Computing Foundation (CNCF) to date. With over 12,000 participants, it was a monumental event, setting the stage for the latest trends and developments in cloud-native computing. As your loyal CNCF Ambassador, I’m here to share some of the important updates you don’t want to miss. I also invited fellow CNCF Ambassador Thomas Schuetz to join me with his own insights.

As Kubernetes adoption continues to surge across various industries, the need for robust monitoring solutions is more critical than ever. Effective Kubernetes monitoring not only ensures the health and performance of your containerized applications but also provides valuable insights for troubleshooting and optimizing your infrastructure. However, Kubernetes's distributed and dynamic nature presents unique challenges regarding monitoring and observability.