Introduction to Amazon Code Pipeline with Java part 6: third party action overview

Introduction

In the previous post we looked at the most important keywords related to AWS CodePipeline. A pipeline is a workflow of stages that together describe the delivery process for a piece of software. This piece of software is called an artifact and goes through various revisions as it is passed from one stage to another. Each stage can consist of one or more actions. An action is a task performed on an artifact. If all actions in a stage have completed without a failure then the stage transitions into the next stage in the pipeline. It’s possible to disable the transition e.g. if it’s necessary to enforce a manual activation.

In this post we’ll start looking at a global overview for third party action development.

Read more of this post

Introduction to Amazon Code Pipeline with Java part 5: architecture key terms

Introduction

In the previous post we looked at some key differences between TeamCity/Jenkins and AWS CodePipeline. There are a number of aspects where these CI tools differ such as the installation, the deployment and custom build runner development.

In this post we’ll start looking at the CP architecture. We’ll concentrate on the key terms to begin with.

Read more of this post

Introduction to Amazon Code Pipeline with Java part 3: adding custom job runners

Introduction

In the previous post we went through the steps to set up a brand new pipeline in AWS Code Pipeline. If you are entirely new to the AWS tools then you might find it overwhelming at first as you have to learn about other AWS tools as well such as S3 and Elastic Beanstalk. However, you might not need all of it since a pipeline can be quite little and consist of only 2-3 steps. The pipeline will start executing as soon as it has been set up. The arrows connecting the steps enable us to cut the execution of the pipeline at a specific step.

In this post we’ll see how to update a pipeline. Updating the pipeline also makes it possible to add custom build runners to the pipeline. I’ll use the load test job runner I referred to in the first part. Note that you’ll need an Apica Loadtest account to fully follow along these steps. The main point is to demonstrate the process of adding a new custom job runner to an existing pipeline. The implementation details are not important at this moment.

Read more of this post

Introduction to Amazon Code Pipeline with Java part 2: setup

Introduction

In the previous post we set out the main topic of this series. We’ll be talking and Amazon Code Pipeline and what it can do for you in terms of Continuous Delivery. The larger part of the post dealt with the differences between 3 related topics: Continuous Integration, Continuous Deployment and Continuous Delivery.

Code Pipeline is an example of an automated Continuous Delivery tool which can help you with the often tedious steps of builds, test runners and deployments. The idea is that the developer can concentrate on the exciting stuff, such as writing some fantastically well-written code which is then pushed into a code repository, like GitHub. The rest of the steps is then handled by a CI/CD tool like Jenkins.

In this post we’ll take a quick visual tour of Code Pipeline so that you get the idea how to set up a new pipeline. We won’t yet add a custom job runner as that is not part of the initial setup process.

Read more of this post