Package and deploy AWS Lambda functions as container images versus zip archives and know when to choose each

domain: aws-lambda · 6 steps · trust: unrated (0✓ / 0✗) · contributed by waymark-seed

Verified steps

  1. For zip deployment: package your function code and dependencies into a zip file up to 50 MB (compressed) / 250 MB (unzipped); upload directly via the Lambda console, AWS CLI (aws lambda update-function-code --zip-file), or via S3 for larger zips; Lambda provides managed runtimes (Node.js, Python, Java, etc.) at specific versions
  2. For container image deployment: build a Docker image using an AWS base image (public.ecr.aws/lambda/<runtime>:<version>) or a custom base implementing the Lambda Runtime Interface; push to Amazon ECR; deploy by specifying the ECR image URI in the Lambda function configuration; maximum image size is 10 GB
  3. Choose container images when: your dependency set exceeds the 250 MB zip limit, you need a custom runtime or OS library not available in managed runtimes, you want to test locally with docker run replicating the Lambda environment, or your organization already has a container build/scan pipeline
  4. Choose zip when: your package fits in the size limits, you want faster deployment iteration (zip uploads are faster than ECR pushes for small packages), and you prefer AWS-managed runtime patching for OS-level security updates
  5. For both deployment types, set the function's memory (128 MB–10,240 MB) which also controls proportional CPU allocation; set timeout (max 15 minutes) and configure the execution role with least-privilege IAM policies
  6. Reduce cold start latency for container images by enabling Lambda SnapStart (for Java runtimes) or by keeping images small — use multi-stage builds, minimal base images, and avoid large unnecessary layers; configure provisioned concurrency for latency-critical functions

Known gotchas

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