An SA story about hyperscaling GitLab Runner workloads using Kubernetes

This post details the challenges and solutions for hyperscaling GitLab Runner workloads on Kubernetes. It highlights the anti-pattern of over-optimizing for minimal resource profiles in CI environments, leading to increased developer toil in debugging and resource allocation. The post proposes a retrospective solution architecture approach, emphasizing balancing compute efficiency with human toil and suggesting counter-balancing questions for future automation efforts, such as matching compute optimization heuristics to workload characteristics and considering higher-order optimizations like spot compute.