Today’s DevOps platform-centric world is moving steadily towards an "Everything-as-Code" mentality. Add in cloud native, and it's clearly even more important to standardize how you define your DevOps processes.
Thanks to faster iteration, cloud native computing, and [microservices-based architectures] (https://about.gitlab.com/topics/microservices/), as-Code technologies have become the de-facto standard for a lot of different parts of the software development lifecycle.
The need to release faster requires a single spot for teams to collaborate on any kind of change – code, infrastructure, configuration, networking, or testing. And to implement that change quickly we need to be able to see and review it before it goes into production.
As-Code solutions are at the core of cloud native technologies such as Kubernetes, where you utilize YAML or JSON formats to configure and manage. Here are the key advantages of 'as-Code':
These benefits come into play with every piece of technology that moves into as-Code; we have seen it time and again as DevOps processes mature and we automate each piece of the software development lifecycle. Here are the critical 'as-Code' stages:
One of the first steps when building a new pipeline is to implement a way to build your application automatically. Containerization is one of the most common ways: You define your build steps as a Dockerfile and then you have automated the build of the application.
As our deployment frequency and team size scales, the need for test cases to be automated scales as well. So we automate, we write unit tests and test scripts to execute unit tests, and then we ensure the changes can be continuously integrated safely, without introducing unplanned bugs.
To ensure software gets to market quickly, security must be included in your testing process. The testing has to happen either through tools integrated with each individual project, or implemented as code, creating job templates for security scanners that can be ingested by projects as required. These steps enable teams to quickly become compliant with various security frameworks (like PCI-DSS, HIPAA,,or ISO) as they become relevant for the project.
Deployments need to be standardized so they are predictable every time. To ensure successful peer review, production and development environment deployments need to be the same, and there's an added bonus of a quality gate between them. Through scripting and implementation of Deployment-as-Code, we end up with the ability to continuously deploy code and continuously deliver value.
Pipelines are the center of the CI/CD workflow – they're the automation heart that powers all of the benefits of as-Code technologies. Once you have the Build-as-Code, Test-as-Code, Deployment-as-Code, Infrastructure-as-Code, and Configuration-as-Code, you have all the parts needed to ensure that you can reliably and predictably take your application into production environments. But, to move changes in with agility, you need to take all those parts and string them together into a pipeline.
The technology behind Pipelines-as-Code makes it possible to create centralized repositories for your organization's pipelines. Pipelines-as-Code can be set up to fit all boxes for varied languages and use cases (like Auto DevOps) or with a number of options so that developers can pick base pipelines to fit their use case. It's important to have a baseline that conforms to the organization's standards because that always increases the speed to production.
The entire team can collaborate on changes to each part of the workflow. Version history can be easily maintained in the same version control system as everything else that touches the DevOps lifecycle.
The benefits of as-Code technology reach a pinnacle with Pipelines-as-Code, so teams gain increases in efficiency, scalability, auditability, and collaboration. Pipelines-as-Code are at the center of automated GitOps, DevOps, and SecOps workflows.