Delivering high-quality software quickly is essential in today's fast-paced digital landscape, and a well-designed continuous integration and continuous delivery (CICD) pipeline can help development teams achieve this goal by enabling faster feedback loops and reducing the time between code changes and deployment.

Continuous Integration and Continuous Deployment (CICD) pipelines have become a crucial part of software development in recent years, with multiple deployments being made daily in some cases.

This fast feedback loop has allowed for new features to be developed and bugs to be fixed much quicker. In this article, we will go through an example of implementing CICD pipelines for a client.

The CICD pipeline consists of four stages: development, integration, staging, and production. The development stage is where every new software build is deployed and tested independently, while the integration stage tests software components together. The staging stage deploys software components in a prod-like environment, while the production stage is the stable environment that can be accessed by the end-users. The application is deployed successively from the development environment to the production environment following a fixed process.

The CICD pipeline follows a generic build and deployment process, which is implemented differently based on the language and tools used. For example, a Java/Maven Build with Helm/Helmfile deployment in Kubernetes could be used.

Security testing is an important part of the CICD pipeline. Static Application Security Testing (SAST) and Dynamic Application Security Testing (DAST) are used to detect potential issues before they occur. Sonarqube is an example of a standalone application that can be linked with an existing development environment. Gitlab is an end-to-end software development platform that integrates natively with security testing plugins.

Building Docker images is also a common task in modern development environments. Kaniko is a tool released by Google that can be used to build Docker images in Gitlab. The pipeline reads a docker-compose.yml file to get build information that will be passed to Kaniko to build the Dockerfile present in the project.

Once built, images are deployed to a quay registry, which includes the feature of analyzing container layers against known vulnerabilities. A Python script is implemented in the pipeline to request the results of this analysis, allowing quality gates to be defined in the deployment process.

A GitOps approach is used to manage Docker build dependencies. GitOps is a software development methodology that uses Git as the single source of truth for declarative infrastructure and application configuration. The pipeline creates a file that links the upstream image to the code repository, triggering a build automatically every time a new commit is made.