This blog post explores how to use observability tools to set and maintain Service Level Objectives (SLOs) for Kubernetes applications. Understanding the difference between SLOs, SLIs, and SLAs is crucial. The best observability tools for Kubernetes include Prometheus, Grafana, and Jaeger. These tools help you collect metrics, visualize data, and trace requests to set SLOs and troubleshoot performance issues. The key steps to using observability tools effectively involve observing your service's behavior, setting thresholds and error budgets for SLOs, and updating SLOs as your system evolves. By following these steps, you can ensure your Kubernetes applications meet performance and availability targets.

Helm dry run, using the helm install --dry-run command, is a valuable technique for validating Helm charts before deployment on a Kubernetes cluster. It helps avoid errors and unexpected behavior by simulating the installation process without modifying the cluster. Helm dry run works alongside other Helm commands like helm template and helm lint to streamline development and ensure charts are well-structured, compatible, and ready for deployment.

This overview lists and describes Open Source tools for Kubernetes administrators interested in leveraging AI for their everyday needs. They include K8sGPT (a CNCF project), Kubernetes ChatGPT bot by Robusta, kube-copilot, and a few kubectl plugins (such as kubectl-ai and kubectl-gpt).Learn about th..