Accelerating agentic RL and evaluation research velocity with 45x faster GKE Agent Sandbox

Google Cloud has released an optimised sandbox architecture for Google Kubernetes Engine designed to streamline agentic reinforcement learning and model evaluation. The service addresses cold-start delays and container image distribution bottlenecks that frequently leave high-cost accelerator clusters underutilised. By cutting startup latency, the cloud provider aims to reduce research expenditure and expedite frontier model training workflows.