Designing pipelines

Designing Pipelines

CI/CD of Applications and Infrastructure

CI/CD stands for continuous integration and continuous delivery or deployment. In GCP, CI/CD automates the process of building, testing, and releasing software changes. The pipeline takes code from developers, runs tests to check for errors, creates a deployable package, and then pushes that package to the target environment. Cloud Build is the primary service that executes these pipelines, running each step in isolated containers that can be customized with specific build tools. Infrastructure as code fits into this process because the same pipeline that deploys an application can also deploy the servers, networks, and storage it runs on, ensuring the environment matches the application's requirements.

Artifact Management with Artifact Registry

Artifact Registry is GCP's service for storing and managing the packages that CI/CD pipelines produce, such as container images, language-specific packages, and deployment artifacts. When a pipeline finishes building code, it pushes the result to Artifact Registry, which acts as a central repository where different parts of the pipeline can find and retrieve what they need. The registry organizes artifacts into repositories that can be scoped to specific projects or shared across an organization, and it integrates directly with Cloud Build and GKE. This separation allows teams to version their artifacts, control who can access them, and ensure that deployments pull from a known, tested source rather than rebuilding from scratch each time.

Deployment to Hybrid and Multi-Cloud Environments (e.g., GKE)

GKE (Google Kubernetes Engine) runs containerized applications across clusters of compute resources, and pipelines must be able to deploy to GKE whether those clusters live in Google Cloud, on-premises data centers, or other cloud providers. A hybrid deployment connects Google Cloud resources with local infrastructure, while a multi-cloud deployment spans two or more cloud providers simultaneously. Pipelines targeting these environments need to authenticate to each target cluster, push container images to a registry each cluster can access, and apply configuration files that define how the application runs. This approach lets organizations avoid being locked into a single cloud provider while still using GCP's managed services for part of their infrastructure.

CI/CD Pipeline Triggers

A trigger is an event that starts a pipeline run automatically rather than requiring someone to start it manually. Common triggers include pushing code to a Git repository, creating a pull request, a scheduled time of day, or a manual request through the GCP console or command line. Each trigger can be configured to filter which events matter—for example, running only when changes affect certain folders or file types, or only when commits target the main branch. Triggers connect the pipeline to the source code repository through integrations with services like Cloud Source Repositories, GitHub, or Bitbucket, ensuring that every significant code change passes through the automated testing and deployment process.

Configuring Deployment Processes (e.g., Approval Flows)

Not every code change should reach production automatically, so pipelines can include approval gates that require a person to review and authorize the deployment before it proceeds. An approval flow pauses the pipeline at a defined stage, sends a notification to the approver, and resumes only after the approver approves the request through the GCP console or API. These flows are especially important for production deployments or changes that affect sensitive systems, because they add a human checkpoint without stopping the automated testing that happens earlier in the pipeline. Teams can configure multiple approval stages, different approvers for different environments, and automatic rejection if approvals are not given within a set time window.