Comparing Sandboxing Approaches for AI Agents

A comparison of sandboxing strategies for AI agents, progressing from basic chroot to systemd-nspawn, Docker containers, full VMs, gVisor, and finally Docker Sandbox with MicroVMs. Each approach is evaluated on isolation strength, startup time, and resource cost. Key finding: containers alone are insufficient due to Docker-in-Docker requiring privileged mode, while full VMs are too resource-heavy to scale. Docker Sandbox addresses both concerns by combining VM-level kernel isolation with container-like startup speed, per-sandbox Docker Engine daemons, and cross-platform support on macOS, Windows, and Linux.