Ray Integrates Native gVisor Sandboxing for Scalable AI Workloads

The Ray open-source distributed computing framework has released version 2.58, which introduces native gVisor sandboxing for scalable AI workloads.

This feature enables isolated environments for reinforcement learning and agentic AI tasks, where untrusted code requires secure execution.

Previously, teams relied on external sandbox providers or built custom systems; Ray's native integration simplifies this process using Google's open-source gVisor runtime.

The architecture leverages Ray-native APIs and runtime primitives to create gVisor sandboxes from OCI container images, execute commands, transfer files, and scale environments.