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AWS Lambda Microvms

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  • Skill
  • Tool integration
  • Cloud and DevOps
  • Apache-2.0
  • Low risk

From the author

Builds, runs, debugs, and operates applications on AWS Lambda MicroVMs — Firecracker-isolated, snapshot-resumable serverless compute environments running inside a container with up to 8 hr lifetimes. Applicable when workloads need strong isolation between tenants, isolated serverless compute, sandbox compute, or secure multi-tenant execution. Also suited for AI/agent code-execution sandboxes, interactive code playgrounds and notebooks (Jupyter, REPLs, dev environments running user-supplied code), reinforcement-learning environments, multi-tenant CI executors and build runners, sessionful game or simulation servers, or isolated security scanners. Also applicable when the workload needs long-lived sessions, a real port-listening server (gRPC, WebSocket, custom TCP protocols), state preserved across periods of inactivity (suspend/resume), container-level access (FUSE, eBPF, custom syscalls), or session-affine routing.
— the description by AWS

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

AWS Lambda MicroVMs provide a serverless compute environment that leverages Firecracker VM isolation combined with container-like efficiency. This skill enables developers to run applications in secure, isolated environments that support long-lived sessions up to 8 hours, state preservation via suspend/resume, and direct container-level access. It is designed for workloads requiring strong tenant isolation, such as AI code-execution sandboxes, interactive notebooks, multi-tenant CI runners, and sessionful simulation servers.

What it does

  • Packages applications into Firecracker-isolated MicroVMs using Dockerfiles.
  • Supports snapshot-based booting to skip application initialization at runtime.
  • Provides lifecycle hooks for managing application state during run, resume, suspend, and termination.
  • Enables secure, token-authenticated ingress for HTTP, gRPC, and WebSocket traffic.
  • Allows for optional shell access for debugging and agent-driven workflows.
  • Supports advanced OS capabilities like FUSE, eBPF, and nested containers.

When to use it

  • When you need strong tenant isolation for secure multi-tenant execution.
  • When your application requires long-lived sessions or state preservation across inactivity.
  • When building interactive code playgrounds, notebooks, or AI agent sandboxes.
  • When you need to run custom network protocols like gRPC or WebSockets in a serverless environment.
  • When you require container-level access to system resources like eBPF or FUSE.

Advantages

  • Strong security isolation via Firecracker microVMs.
  • Fast startup times through memory and disk snapshots.
  • Flexible lifecycle management with suspend and resume capabilities.
  • Support for long-running sessions up to 8 hours.
  • Consistent local development experience using standard Dockerfiles.

Usage examples

“How do I create a new MicroVM image from my Dockerfile?”
The agent provides the 'aws lambda-microvms create-microvm-image' command, specifying the S3 artifact location, build role, and base image ARN.
“How can I securely connect to my running MicroVM?”
The agent explains how to use 'aws lambda-microvms create-microvm-auth-token' to generate a short-lived token for header-based authentication.
“How do I implement lifecycle hooks for my application?”
The agent provides a code example for implementing HTTP endpoints (e.g., /ready, /run, /suspend) that the platform calls to manage the MicroVM state.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/aws/aws-lambda-microvms/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip aws-lambda-microvms.zip -d .agents/skills

Documentation by AWS

AWS Lambda MicroVMs

The AWS MCP server is recommended for sandboxed execution and audit logging.

AWS Lambda MicroVMs are serverless compute environments that combine Firecracker VM isolation with container-like efficiency. Each MicroVM:

  • Runs your application as a container inside a Firecracker microVM — you can reproduce the environment locally.

  • Runs Amazon Linux 2023 as the base OS inside the MicroVM.

  • Boots from a memory + disk snapshot captured at image build time, so application init is skipped on run.

  • Has a dedicated, TLS-terminated HTTPS endpoint reachable with an auth token.

  • Can be suspended and resumed with state preserved; lives up to 8 hours.

Two-resource model:

  • MicrovmImage — a versioned artifact built from {S3 zip with Dockerfile} + baseImageArn. Each version has per-architecture/chipset Builds.

  • Microvm — a running instance created (RunMicrovm) from an image version.

Two roles:

  • buildRoleArn — used during image build (S3 read, CloudWatch logs, optional ECR).

  • executionRoleArn — assumed at runtime by the running MicroVM.

When to use

Choose Lambda MicroVMs when
  • Analytics workloads — isolated compute for data processing, ETL jobs, or query execution with strong tenant separation.

  • AI / agent code execution sandboxes — fresh, isolated environment per session, fast resume between turns.

  • Interactive code playgrounds & notebooks — Jupyter, REPLs, dev environments executing user code.

  • Reinforcement-learning environments — clean per-episode envs with tool access.

  • Multi-tenant CI executors / build runners — strong tenant isolation.

  • Game / simulation servers — sessionful, long-lived (up to 8 hr) workloads.

  • Security scanning — running untrusted analyzers in isolation.

In general, Lambda MicroVMs are suited for long-lived sessions, real port-listening servers (gRPC, WebSocket, custom TCP protocols), state preserved across periods of inactivity (suspend/resume), container-level access (FUSE, eBPF, custom syscalls), or session-affine routing to a specific compute environment.

Choose Lambda Event Functions when
  • The workload fits in 15 minutes.

  • Per-function isolation is sufficient; if ordinary event/request handlers need execution environments dedicated to one invoker or tenant, use Event Functions on On-Demand with tenant isolation mode. Do not assume Lambda creates a fresh Firecracker VM or execution environment for every invocation.

  • No session state needs to remain in memory, on disk, or in running processes between interactions.

  • Fully automatic scaling is preferred (no RunMicrovm to manage).

  • Event-source integrations (S3, SQS, EventBridge, etc.) drive the function.

Choose something else when
  • Continuous compute beyond 8 hr → ECS / EKS / EC2.

  • Lift-and-shift workloads needing kernel modifications or a non-Linux OS → EC2.

Typical workflow

  1. Check regional availability — confirm Lambda MicroVMs is available in your target region (run aws lambda-microvms list-managed-microvm-images). Your S3 artifact bucket and any network connectors must be in the same region as the image.

  2. Package an app: zip with a Dockerfile at the root, upload to S3 (same region as the image).

  3. Implement lifecycle hooks (optional but recommended) — HTTP endpoints on a port you specify (commonly 9000) for /run, /resume, /suspend, /terminate, /ready, /validate.

  4. CreateMicrovmImage — pointing at the S3 artifact, a managed base image, and a build role. Lambda compiles the Dockerfile into an OCI image, starts your app, calls /ready, snapshots disk + memory, optionally validates with /validate. Lambda will periodically release new managed image versions, and customers should re-build using the latest version to ensure they have up to date images.

  5. RunMicrovm — pick an image version, attach executionRoleArn, set idlePolicy, ingress/egress connectors, and (optionally) a runHookPayload. Receive an endpoint URL and microvmId.

  6. CreateMicrovmAuthToken — get an auth token (max 60 min) with allowedPorts specifying which ports the token grants access to. Send traffic to the endpoint with X-aws-proxy-auth: <token>.

  7. Suspend / Resume / Terminate — explicit APIs, or let the idlePolicy drive it (maxIdleDurationSeconds, suspendedDurationSeconds, autoResumeEnabled).

ARN partitions

Every ARN in this skill is written arn:<partition>:.... Set the partition from the target region. Do not default to arn:aws:, because an ARN with the wrong partition is rejected.

Only the partition segment changes. The aws account field in managed base image ARNs (arn:<partition>:lambda:<region>:aws:microvm-image:...) and default network connector ARNs stays aws. Where possible, copy ARNs from API output (list-managed-microvm-images, create-microvm-image, get-microvm-image) instead of building them by hand.

MicroVM endpoint domains also differ in China. Endpoints are <microvm-id>.lambda-microvm.<region>.on.aws in commercial regions and <microvm-id>.lambda-microvm.<region>.on.amazonwebservices.com.cn in China regions. Use the endpoint value returned by run-microvm or get-microvm instead of building the hostname. The VPC endpoint service name, com.amazonaws.<region>.lambda-microvm, is the same in every partition.

Core CLI commands
# Create an image (zip with Dockerfile at root in S3, plus a managed base image)
aws lambda-microvms create-microvm-image \
  --name my-image \
  --base-image-arn arn:<partition>:lambda:<region>:aws:microvm-image:al2023-1 \
  --build-role-arn arn:<partition>:iam::<acct>:role/MicroVMBuildRole \
  --code-artifact '{"uri":"s3://<bucket>/<key>.zip"}'

# Run a MicroVM (returns endpoint + microvmId). --image-identifier takes the
# image ARN and --image-version is the full major.minor string.
aws lambda-microvms run-microvm \
  --image-identifier arn:<partition>:lambda:<region>:<acct>:microvm-image:my-image \
  --image-version 1.0 \
  --execution-role-arn arn:<partition>:iam::<acct>:role/MicroVMExecutionRole \
  --idle-policy '{"maxIdleDurationSeconds":900,"suspendedDurationSeconds":300,"autoResumeEnabled":true}'

# Mint an auth token and call the endpoint
TOKEN=$(aws lambda-microvms create-microvm-auth-token \
  --microvm-identifier microvm-... --expiration-in-minutes 30 \
  --allowed-ports '[{"port":8080}]' \
  --query 'authToken."X-aws-proxy-auth"' --output text)
curl "<endpoint>/" -H "X-aws-proxy-auth: $TOKEN"

# Lifecycle
aws lambda-microvms suspend-microvm   --microvm-identifier microvm-...
aws lambda-microvms resume-microvm    --microvm-identifier microvm-...
aws lambda-microvms terminate-microvm --microvm-identifier microvm-...

See references/getting-started.md for the full walkthrough including --hooks config and lifecycle hooks.

Hook configuration

Hooks are organized into two groups under the --hooks parameter:

microvmImageHooks (build-time)

Recommendation: Implement the image build hooks (/ready and /validate) for best performance. They enable the platform to capture a complete snapshot and prefetch the portions accessed at run time.

HookPurposeTimeout range
readyCalled during application boot. When this hook returns a 200 status code, it signals to the platform that the application is ready to be snapshotted. Use this to ensure your application is fully booted before a snapshot is taken. If your application is not yet ready, return a 503 status code until it is ready for snapshotting.1–3600s (default 30s)
validateCalled after running your application from the microVM snapshot. Use this hook to validate the application is ready to serve traffic. This hook additionally allows the platform to sample the portions of the snapshot that are used when your application is ran, allowing Lambda to prefetch those portions of the snapshot to reduce latency. To get the best performance, run mock payloads through the application during validate. When this hook returns a 200, it signals to the Lambda the MicroVM image is valid. If your application needs more time to run its validate workflow, return a 503 status code.1–3600s (default 30s)

Why implement /ready? It signals the platform that your application has fully booted. Without it, the snapshot may be taken mid-initialization, meaning the cached state is incomplete and every run repeats part of the boot sequence.

Why implement /validate? It lets the platform verify the snapshot is correct, and also samples which portions of the snapshot are accessed during RunMicrovm. This allows the platform to prefetch those portions on future launches, reducing cold-start times.

microvmHooks (runtime)
HookPurposeTimeout range
runFires once after run from snapshot1–60s (default 1s)
resumeFires after SUSPENDED → RUNNING1–60s (default 1s)
suspendFires before RUNNING → SUSPENDED1–60s (default 1s)
terminateFires before termination1–60s (default 1s)

See references/getting-started.md for a full example enabling all hooks.

Per-MicroVM size limits

ResourceLimit
Maximum vCPUs per MicroVM16
Maximum memory per MicroVM32 GB

For all other quotas — concurrent MicroVMs per account, launch rate, image count, max execution duration, auth token TTL, Lambda Network Connector (LNC) limits, per-ENI bandwidth, etc. — check the AWS docs / Service Quotas console. Most are soft quotas, raisable through Service Quotas / Support.

Additional capabilities

By default, the container runs with a restricted set of Linux capabilities. Set --additional-os-capabilities '["ALL"]' at image creation time only when required by your use case:

  • Filesystem mounts — EFS, FUSE-based filesystems.

  • Nested containers — running additional containers with containerd inside the MicroVM.

  • eBPF programs — tracing, profiling, or custom network policies.

aws lambda-microvms create-microvm-image \
  --name my-image \
  --base-image-arn arn:<partition>:lambda:<region>:aws:microvm-image:al2023-1 \
  --build-role-arn arn:<partition>:iam::<acct>:role/MicroVMBuildRole \
  --code-artifact '{"uri":"s3://<bucket>/<key>.zip"}' \
  --additional-os-capabilities '["ALL"]'
Shell ingress for agent use cases

For programmatic shell access (agent workflows, remote command execution), use the SHELL_INGRESS network connector:

# 1. Run with SHELL_INGRESS enabled
aws lambda-microvms run-microvm \
  --image-identifier arn:<partition>:lambda:<region>:<acct>:microvm-image:my-image \
  --execution-role-arn arn:<partition>:iam::<acct>:role/MicroVMExecutionRole \
  --ingress-network-connectors '["arn:<partition>:lambda:<region>:aws:network-connector:aws-network-connector:SHELL_INGRESS"]' \
  --idle-policy '{"maxIdleDurationSeconds":900,"suspendedDurationSeconds":300,"autoResumeEnabled":true}'
# Response includes microvmId and endpoint

# 2. Mint a shell auth token (max 60 min; use shortest duration needed)
# Treat the token as a secret — avoid logging, storing in files, or shell history.
TOKEN=$(aws lambda-microvms create-microvm-shell-auth-token \
  --microvm-identifier microvm-... \
  --expiration-in-minutes 15 \
  --query 'authToken."X-aws-proxy-auth"' --output text)

# 3. Connect via WebSocket (port 8022)
# CLI args are visible in process listings (ps aux). For shared hosts,
# pipe the header via a file descriptor or use a wrapper script.
websocat "wss://<endpoint>/shell" \
  -H "Sec-WebSocket-Protocol: lambda-microvms.authentication.${TOKEN}, lambda-microvms, lambda-microvms.port.8022"

The shell drops into the same container as the running application — same network namespace, filesystem, and process tree. This provides an interactive PTY over a WebSocket-based shell channel accessible from any client (terminal or browser), suitable for agent-driven workflows that need to execute commands inside the MicroVM.

Prerequisites: MicroVM must be run with SHELL_INGRESS attached, and caller also needs lambda:CreateMicrovmShellAuthToken.

Known constraints

  • Image is single-size — you can't ship multiple instance sizes from one image. Plan one image per size.

  • Image versions incur storage cost even when no MicroVMs are running on them. Use delete-microvm-image-version to clean up.

  • Suspend → resume can't switch network connectors. LNC is bound at run time.

  • No self-suspend from inside the MicroVM. Call SuspendMicrovm from outside (via the public API).

  • Auth token max TTL is 60 min. Refresh ahead of expiry for long-running clients.

  • Runtime hooks (/run, /resume, /suspend, /terminate) are fast-notification only (1–60s timeout). Don't use them for slow init.

Reference index

Pick the reference that matches your task:

  • references/getting-started.md — prerequisites (S3 bucket, build role trust policy), packaging, end-to-end CLI walkthrough, first run + token + curl.

  • references/lifecycle-model.md — image vs. MicroVM state machines, the six lifecycle hooks (paths, timeouts, what to do in each), idle/suspend/resume semantics, hook payloads.

  • references/snapshots-and-uniqueness.md — what gets snapshotted, the uniqueness pitfall, CSPRNGs by language, env vars vs. run configuration, snapshot size inspection.

  • references/networking.md — ingress vs. egress connectors, port routing, X-aws-proxy-* headers, WebSocket subprotocols, HTTP/2 / gRPC, VPC egress.

  • references/iam-and-security.md — build role vs. execution role, trust policies, auth tokens (regular vs. shell), lambda:PassNetworkConnector.

  • references/troubleshooting.md — image build error codes, run/connect failures, hook timeouts, network connector issues, debugging via shell access.

Conventions used in references

  • The runtime-side default proxy port is 8080. Override per-request with X-aws-proxy-port or per-WebSocket with subprotocol lambda-microvms.port.<n>.

Security considerations

  • Confused deputy prevention — add aws:SourceAccount (or aws:SourceArn) condition keys to trust policies. See references/iam-and-security.md.

  • Snapshot uniqueness — snapshots share memory state. Reseed CSPRNGs and rotate secrets on resume. See references/snapshots-and-uniqueness.md.

  • Network isolation — use VPC egress connectors to restrict outbound traffic.

  • Least-privilege execution roles — scope IAM policies to specific regions, accounts, and resource prefixes.

  • Logging — enable CloudTrail for MicroVM lifecycle events.

Files

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Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs a command-line tool

Security

What our scanner noticed· Low risk

  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

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aws/agent-toolkit-for-aws · skills/specialized-skills/serverless-skills/aws-lambda-microvms · commit 0a218f8
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