AWS Lambda

Deploy your dotflow pipeline as a container-based AWS Lambda function.

Create project

dotflow init
# Select cloud: lambda

Or generate files for an existing project:

dotflow cloud generate --platform lambda

Generated files

File	Description
Dockerfile	Lambda container image
handler.py	Lambda entry point that calls your workflow
template.yaml	SAM template defining the function
samconfig.toml	Pre-configured deployment settings

Prerequisites

• pip install dotflow[aws]
• AWS CLI configured (aws configure)
• Docker

Deploy

Option 1: dotflow deploy

dotflow deploy --platform lambda --project my_pipeline

Option 2: SAM CLI

aws ecr create-repository --repository-name my_pipeline --region us-east-1
sam build
sam deploy

Invoke

# Via dotflow deploy
aws lambda invoke --function-name my_pipeline --region us-east-1 /dev/stdout

# Via SAM
sam remote invoke

View logs

sam logs --stack-name my_pipeline --tail

Variants

Platform	Trigger	Deploy method
lambda	Manual invocation	dotflow deploy or sam deploy
lambda-scheduled	EventBridge cron/rate	dotflow deploy --schedule or sam deploy
lambda-s3-trigger	S3 file upload	dotflow deploy or sam deploy
lambda-sqs-trigger	SQS message	dotflow deploy or sam deploy
lambda-api-trigger	HTTP POST via API Gateway	dotflow deploy or sam deploy

Important

• Do not rename handler.py or the handler() function — the Dockerfile CMD is handler.handler
• Do not rename workflow.py or the main() function — handler.py imports it
• The samconfig.toml has stack name, region, and ECR repository pre-configured