How Achievers load tests Kubernetes

The Achievers team built a load testing framework to improve platform performance and scalability. They set goals for throughput, errors, latency, and scalability, and used observability dashboards in New Relic to track progress. Throughput optimization involved using Istio Load Balancing to distribute traffic evenly among pods, while reducing errors by adding extra IP addresses and bumping port limits on the Google Cloud NAT. Latency improvements were made through code optimizations, including removing unnecessary database locks and upgrading endpoint performance. Caching improvements were achieved by moving images to a CDN and optimizing Redis cache usage. Scaling was ensured through adjusting IP address limitations and introducing topologySpreadConstraints to distribute critical services across worker nodes. The team successfully met their goals, improving throughput by 4x, reducing errors, and scaling the cluster effectively.

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