Harbor Adds Docker Sandboxes to Run Reproducible AI Agent Evals in Isolated MicroVMs
Harbor can now run each agent-evaluation task inside its own Docker Sandbox microVM, separating untrusted agent code from the host and other tasks. Docker reports testing 64 concurrent cloud tasks; network policies can allow dependency setup and then restrict access during evaluation, reducing one source of inconsistent results.
This is a useful isolation and reproducibility option, not a complete answer to eval integrity: the article notes no overhead, cost, or score-variance benchmarks, and sandboxing does not stop an agent from tampering with writable test files. InfoQ has no reader-comment section.