![]() Changes are applied automatically to bring the live instance into parity with the current state of your repository.įocusing on the end goal cuts out much of the complexity around workflow management. ![]() They consume the files in your repository and diff them against your existing environment. This means your files are written so they describe the currently desired state, instead of the specific steps used to achieve it.ĭeclarative state management is supported by tools like Kubernetes and Terraform. “As code” workflows are best when you use declarative modes of expression. You can begin to streamline business-level stages, as well as the traditional technical procedures. Storing everything as code maximizes your ability to apply automation throughout your entire process. ![]() You could have a pipeline that produces a design document as an artifact each time your specification changes. However pipelines are really just automated scripts that run when a trigger (usually a merge event) occurs. Merging a repository change into your main branch will run the pipeline for you, applying the changes introduced by the new state.ĬI pipelines are commonly discussed in the context of code changes: the canonical example is a pipeline that deploys to production each time you change the code. ![]() Automation is normally built atop “as code” workflows using continuous integration pipelines. ![]()
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