What problem does it solve?
Running untrusted code, multi-tenant workloads, or long-lived sessionful servers requires strong isolation that standard Lambda functions (15-minute limit, per-invocation model) cannot provide. This Skill guides AI agents through packaging, building, running, and operating AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable compute environments with up to 8-hour lifetimes.
Core Features & Use Cases
- Image build and run workflow: Package a Dockerfile-based zip to S3, create a MicrovmImage with lifecycle hooks, run MicroVMs with idle policies, and authenticate traffic with scoped auth tokens.
- Lifecycle and snapshot guidance: Implement /ready, /validate, /run, /resume, /suspend, and /terminate hooks correctly, and avoid the snapshot-uniqueness pitfall (shared PRNG seeds, UUIDs, secrets across instances).
- Networking, IAM, and troubleshooting: Configure ingress/egress network connectors, WebSocket shell access for agents, build vs. execution IAM roles, and diagnose build failures, 502s, and hook timeouts.
- Use Case: An AI coding agent needs a sandbox to execute user-supplied code. Use this Skill to build a MicroVM image, run an isolated environment per session, attach SHELL_INGRESS for command execution, and suspend/resume between turns.
Quick Start
Ask the agent to package a Flask app with a Dockerfile, create a Lambda MicroVM image from an S3 artifact, run a MicroVM, and call its endpoint with an auth token.