For full documentation, please see the readthedocs site.
Click here to join the Slack team for stacker, and then join the #stacker channel!
stacker is a tool and library used to create & update multiple CloudFormation stacks. It was originally written at Remind and released to the open source community.
stacker Blueprints are written in troposphere, though the purpose of most templates is to keep them as generic as possible and then use configuration to modify them.
At Remind we use stacker to manage all of our Cloudformation stacks - both in development, staging, and production without any major issues.
- Python 3.7+
The stacker
command has sub-commands, similar to git.
Here are some examples:
build
:- handles taking your stack config and then launching or updating stacks as necessary.
destroy
:- tears down your stacks
diff
:- compares your currently deployed stack templates to your config files
info
:- prints information about your currently deployed stacks
We document these sub-commands in full along with others, in the documentation.
stacker_cookiecutter
: https://github.com/cloudtools/stacker_cookiecutter
We recommend creating your base stacker project using stacker_cookiecutter
.
This tool will install all the needed dependencies and created the project
directory structure and files. The resulting files are well documented
with comments to explain their purpose and examples on how to extend.
stacker_blueprints
: https://github.com/cloudtools/stacker_blueprints
This repository holds working examples of stacker
blueprints.
Each blueprint works in isolation and may be referenced, extended, or
copied into your project files. The blueprints are written in Python
and use the troposphere library.
stacker reference documentation
:
We document all functionality and features of stacker in our extensive reference documentation located at readthedocs.
AWS OSS Blog
: https://aws.amazon.com/blogs/opensource/using-aws-codepipeline-and-open-source-tools-for-at-scale-infrastructure-deployment/
The AWS OSS Blog has a getting started guide using stacker with AWS CodePipeline.
Stack can also be executed from Docker. Use this method to run stacker if you want to avoid setting up a python environment:
docker run -it -v `pwd`:/stacks remind101/stacker build ...