Summary

In this chapter, we delved into the operational aspects of workload autoscaling in Kubernetes, focusing on troubleshooting and monitoring techniques for HPA, VPA, and KEDA. We explored common issues that can arise when implementing autoscaling and provided practical approaches to diagnose and resolve these problems.

We began by examining how to troubleshoot HPA, emphasizing the importance of reviewing conditions and events. Similarly, for VPA, we discussed the process of verifying component status, reviewing events, and analyzing logs from all the VPA components. Then we focused on KEDA. We covered how to review events from ScaledObject and ScaledJob resources and how to interpret logs from KEDA’s components. We also stressed the importance of centralizing logs and events for more effective troubleshooting in larger environments.

Beyond troubleshooting, we explored monitoring strategies for KEDA, introducing key metrics that can be used to understand the health...