Kubernetes autoscaling is a powerful tool, but many setups fail silently due to misleading metrics, poor configurations, and other details. Here are 10 common pitfalls that can break your autoscaling—and how to avoid them.

Since Kaniko is no longer maintained, you might be looking for another tool to build your containers in a Kubernetes-based environment. werf is a CNCF Sandbox project that might be helpful in your case.

werf, a CNCF Sandbox project, announced Nelm as a new tool for deploying Helm charts.

Kubernetes health checks using probes (readiness, liveness, and startup) are essential for ensuring application reliability and high availability. Readiness probes determine if a pod is ready to serve traffic, while liveness probes check if the application is running correctly. Probes can be configured via HTTP, TCP, or command-based methods, with options like initialDelaySeconds and periodSeconds for fine-tuning. Implementing these probes is a key Kubernetes monitoring best practice, enabling automated issue detection, fault tolerance, and improved user experiences.

Kubernetes capacity planning is evolving from traditional resource-based approaches to intent-based planning that focuses on service-level objectives. Key strategies include implementing horizontal pod autoscaling, setting appropriate resource requests/limits, using namespace quotas, and monitoring cluster utilization. Success requires balancing automated scaling with cost optimization while maintaining performance requirements. Essential tools include cluster autoscaling, resource quotas, and comprehensive monitoring.

This blog post provides a comprehensive guide to writing effective Prometheus alert rules. It covers key concepts like alert template fields, PromQL syntax, and best practices for creating and managing alerts. The article also discusses the limitations of Prometheus alerts and provides practical examples of common alert rules. Finally, it emphasizes the importance of incident response handling and the use of tools like Squadcast to streamline alert management and improve overall system reliability.

The blog post explores seven essential best practices for Kubernetes monitoring, guiding DevOps and Site Reliability Engineers (SREs) in developing robust monitoring strategies. It differentiates between monitoring and observability, emphasizing the importance of defining clear objectives, identifying critical metrics, selecting appropriate tools, and implementing comprehensive monitoring across system and application levels. The guide covers key aspects such as choosing between open-source and commercial solutions, monitoring the monitoring system itself, managing data storage, tracking the Kubernetes control plane, and integrating monitoring with incident response.

This definitive guide provides a comprehensive walkthrough for installing Prometheus on Kubernetes, covering essential steps from prerequisites to advanced configuration. Readers will learn how to leverage Helm charts, create custom scrape configurations, manage resources, and implement best practices for Kubernetes monitoring. The tutorial offers practical code examples, troubleshooting tips, and insights into transforming cluster observability through powerful, open-source monitoring techniques.