Notes from the work

Welcome to the second part of my series on deployment pipelines. If you missed the intro, check out the video where I describe a typical pipeline here. The other parts of this series are part 1: test phase and part 3: deployment onto an environment.

After the test phase of the pipeline, once the quality of the code has been checked, we must build a deployable artefact for this version (commit) of the code. In case of AWS, this would be an AMI (Amazon Machine Image), which can then be deployed as a new instance in our environment.

Welcome to the first part of my series on deployment pipelines. If you missed the intro, check out the video where I describe a typical pipeline here.

First step of a deployment pipeline, is usually a series of tests. After a commit is made, the code is checked out from the source code repository and tested. Those are usually code style tests and unit tests.

More details on each deployment phase with examples, will be posted at our blog over the coming weeks, so check back soon.

If you’ve ever wrote AWS CloudFormation template, you probably know that it can be a daunting task. Luckily, it can be much easier, if you use Python’s library “Troposphere”.

Troposphere lets you create Python objects in place of CloudFormation elements, does some basic validation of your input and generates the JSON template for CloudFormation for you. It is much easier and cleaner to use that writing JSON templates manually.