Traffic-driven Testing in Kubernetes

Kubernetes testing evaluates application availability, performance, ingress behavior, autoscaling, and service interactions under varying traffic conditions, helping organizations reduce downtime, identify capacity bottlenecks, improve resource provisioning, meet SLOs and SLAs, and shorten repair times. The tutorial presents Speedscale as a framework that captures real production-like traffic through a sidecar proxy, automatically maps dependencies, and generates test artifacts without manually scripting traffic or mocks. Using a Java Spring Boot demo application, users install the Speedscale operator, deploy the application, inspect inbound and outbound requests in the dashboard, and create traffic snapshots for regression, load, and chaos-oriented testing in Kubernetes clusters. Captured traffic can be replayed with mocked outbound services, scaled to higher volumes such as 100 times original traffic, transformed to change values for different environments, and analyzed through reports that reveal missed latency or performance goals despite successful requests. The platform also supports configurable test goals, data loss protection to redact sensitive fields such as bearer tokens, CI/CD integration through its CLI, and scheduled snapshots or replays, positioning traffic replay as a way to test realistic service behavior without affecting production.

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