The First 5 Chaos Experiments to Run on Kubernetes
Learn how to improve the availability and reliability of Kubernetes clusters using the discipline of Chaos Engineering.
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About the Authors
In this guide, we cover:
- How to improve the availability and reliability of Kubernetes clusters using the discipline of Chaos Engineering
- How to use Chaos Engineering to safely inject failure into your applications and nodes in order to detect weaknesses.
- Specific Chaos Experiments for you to run on Kubernetes to ensure you’ve designed a reliable system.
You'll learn how Chaos Engineering can help you and your team harden your Kubernetes infrastructure, improve reliability, and keep your applications running smoothly
Incident classification: SEV descriptions and levels, and SEV and time-to-detection (TTD) timelines
Organization-wide critical service monitoring, including key dashboards and KPI metrics emails
Service ownership and metrics for organizations maintaining a microservices architecture
Effective on-call principles for site reliability engineers, including rotation structure, alert threshold maintenance, and escalation practices
Chaos Engineering practices to identify random and unpredictable behavior in your system
Monitoring and metrics to detect incidents caused by self-healing systems
Creating a high-reliability culture by listening to people in your organization
Even systems like Kubernetes need to be tested to verify that they can handle turbulent production conditions.
By thoughtfully injecting failure into Kubernetes, engineers can identify bugs before migrating a new service over and ensure successful launches and the stable ongoing performance of their application. This reduces time fighting fires so teams can ship more code, faster.