Crtl-Alt-Defeat

Openenv Autoscaling Control Center is a packaged OpenEnv environment for training and evaluating agents on cloud-service autoscaling and service stability tasks. The environment simulates a Kubernetes-like service under changing traffic conditions and exposes an action space for scaling decisions. We built a formal OpenEnv package, a heuristic baseline and RL training scaffolding, and a demo UI. The environment is designed to test whether agents can make good operational decisions under dynamic load. It includes realistic metrics such as incoming requests per second, ready pods, queue depth, latency, and reward. I also added richer scenario families such as traffic spikes, bad deploys, and dependency slowdowns in our advanced branch to move toward incident-response style control.