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Implement for AWS ECS and Docker Compose what SAM is to Serverless for AWS Lambda

Project description


CodeStyle TDD with pytest BDD with Behave Codecov


Be for AWS ECS and docker-compose what AWS SAM is to Lambda


pip install ecs_composex


usage: ecs_composex [-h] -n NAME -f DOCKERCOMPOSEXFILE
                [-d OUTPUTDIRECTORY]
                [--format {json,yaml,text}]
                [--cfn-config-file CFNCONFIGFILE]
                [--region REGIONNAME]
                [--az ZONES]
                [-b BUCKETNAME] [--no-upload]
                [--vpc-cidr VPCCIDR]
                [--vpc-id VPCID]
                [--public-subnets PUBLICSUBNETS]
                [--app-subnets APPSUBNETS]
                [--storage-subnets STORAGESUBNETS]
                [--discovery-map-id VPCDISCOVERYMAPID]
                [--cluster-name ECSCLUSTERNAME]


Each component can also use the docker-compose file but be deployed on its own, allowing, for production workloads, to deploy each component separately to avoid dependencies on each other.

AWS Resources support

  • AWS ECS: from docker-compose to ECS transparently, using AWS Fargate primarily.
  • AWS VPC: create or use existing VPC to deploy your services
  • AWS AppMesh: Services mesh for your services.
  • AWS SQS: queues for distributed workloads
  • AWS RDS: databases integration made easy
  • AWS EC2: Deploy your services on EC2 for custom settings. Features SpotFleet by default.


Follow the news and technical articles on using ECS ComposeX on the Blog


If you do not need extra AWS resources such as SQS queues to be created as part of these microservices deployments, I would recommend to use AWS ECS CLI which does already a lot of the work for the services. Alternatively, use the AWS CLI v2. It is absolutely smashing-ly awesome and might be just what you need This tool aims to reproduce the original ECS CLI behaviour whilst adding logic for non ECS resources that you want to create in your environment.


This package would not have been possible without the amazing job done by the AWS CloudFormation team! This package would not have been possible without the amazing community around Troposphere! This package was created with Cookiecutter and the audreyr/cookiecutter-pypackage project template.

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