This most often involves running unit tests to ensure our code changes are sound and don't introduce nasty regressions before deployment. For scripted languages, it might mean writing out dynamically generated configuration files and downloading required dependent packages from a package manager repository (such as NPM for Node.js or Pip for Python).
For languages such as Java and C#, this means compiling our applications into executable bytecode. Assembling the executable artifacts themselves.
NPM SERVERLESS CODEPIPELINE AWS HOW TO
Our first challenge, then, is how to trigger the creation of a new artifact for deployment whenever we check in a releasable change. Continuous deployment (CD) is the process of releasing this artifact into a given release stage.
NPM SERVERLESS CODEPIPELINE AWS MANUAL
Deploying our application through various stages (dev, test, stage, and production) and running it through various manual and automated validation procedures before making it available to users.Ĭontinuous integration (CI) is the process of preparing a deployable application artifact - usually in an automated fashion triggered by a check-in to a code repository such as Git.Building, validating, and packaging a new version of our application for deployment and.At a minimum, achieving this goal requires: Shipping software in a repeatable and reliable manner at scale is a complex effort. Continuous Integration and Continuous Deployment Finally, we'll talk a bit about how TinyStacks makes using these features of AWS even easier than ever. We'll also walk through a hands-on example using a sample REST API app written in Flask. In this article, we'll look at two key features in AWS - AWS CodeBuild and AWS CodePipeline - that you can use to build, test, package, and deploy your applications. Application development teams require repeatable methods for shipping application changes to customers at scale. One of the core challenges of modern microservices architecture is in deployment.
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