To help you get started, we've collected the most common ways that stacker is being used within popular public projects.

remind101 / stacker_blueprints / tests / test_route53.py View on Github

blueprint = DNSRecords('route53_both_hosted_zone_id_and_name_error',
                               self.ctx)
        blueprint.resolve_variables(
            [
                Variable(
                    "RecordSets",
                    [
                        {
                            "Name": "host.testdomain.com.",
                            "Type": "A",
                            "ResourceRecords": ["10.0.0.1"],
                        },
                    ]
                ),
                Variable("HostedZoneId", "fake_zone_id"),
                Variable("HostedZoneName", "fake_zone_name"),
            ]
        )
        with self.assertRaises(ValueError):
            blueprint.create_template()

View more ways to use stacker

stacker

For full documentation, please see the readthedocs site.

Click here to join the Slack team for stacker, and then join the #stacker channel!

About

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.

Requirements

• Python 2.7
• Python 3.5+

Stacker Command

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.

Getting Started

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:

> 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:

> The AWS OSS Blog has a getting started guide using stacker with AWS > CodePipeline.

Docker

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 ...