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Kubernetes Scaling and Container Performance
16.1🔒Validating Kubernetes Auto-ScalingKubernetes HPA promises automatic scaling, but "configured" does not mean "working." Performance testing must validate that auto-scaling…
16.2🔒Lab: k6 Test for HPA ValidationCritical question: What happens to users during T+1:00 to T+3:00 (the scaling gap)?
16.3🔒HPA Configuration for Performance
16.4🔒Architecture-Specific Testing
16.5🔒Testing Cascading Failures in MicroservicesRun this k6 test simultaneously with a Litmus network-latency experiment to validate circuit breakers and fallback logic.
16.6🔒Resource Limits and PerformanceLoad testing is the only way to find the optimal configuration.
16.7🔒Full CI Pipeline: Performance and ChaosThis pipeline ensures every merge to main is validated for performance (Lighthouse + k6) and resilience (Litmus). The system must not only…
16.8🔒Key Takeaways -- Chapter 161. HPA validation requires load testing -- configuration alone does not guarantee correct scaling. 2. The "scaling gap" (time between spike…
16.9🔒Exercises -- Chapter 16Exercise 16.1 (Beginner): Calculate how many pods an HPA should create if baseline is 3 pods at 60% CPU, and traffic suddenly doubles…
16.10🔒Career Translation- Validated Kubernetes HPA behavior through k6 spike tests, discovering a 2.5-minute scaling gap during traffic surges that caused 503…
16.11🔒Q&AInterview Depth CheckPrompt: You configure an HPA to scale based on CPU utilization at 60%. During a k6 spike test, the pods scale up but latency stays high for…