Mastering Google Cloud Run: End-to-End CI/CD Pipeline Using Cloud Build, Cloud SQL, Artifact Registry, Cloud KMS, GitHub
Google Cloud Run tutorial.
Stop managing servers - Learn how to deploy, automate, and scale your applications on Google Cloud Run with a production-ready CI/CD pipeline and real-world examples. Modern application deployment has shifted dramatically from managing servers to serverless platforms. Developers and DevOps engineers can now build, deploy, and scale applications without worrying about infrastructure management. One of the most powerful tools in this space is Google Cloud Run - a fully managed serverless platform that allows you to run containerized applications effortlessly. Whether you're deploying a simple API or a microservices-based architecture, Cloud Run provides automatic scaling, high availability, and seamless integration with the Google Cloud ecosystem.
In this guide, you will learn how to build a complete, production-ready CI/CD pipeline using Cloud Build, Docker, Buildpacks, Artifact Registry, Cloud SQL, and Cloud KMS. We’ll start from scratch — creating a new project, setting up authentication, and configuring required services — and move step-by-step toward automated deployments using GitHub integration and build triggers.
By the end of this article, you will have a clear understanding of:
- What Cloud Run is and when to use it
- How to build and deploy applications using both Docker and Buildpacks
- How to set up a secure and automated CI/CD pipeline
- Setting up and managing Cloud SQL Instance
- Setting up Blue-Green Deployment on Cloud Run
- Best practices for managing container images and service accounts
If you’re a DevOps engineer, cloud enthusiast, or developer looking to simplify deployments and adopt modern cloud-native practices, this hands-on guide will help you get there.
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A powerful combination in the CI/CD world: GitOps (Argo CD)+ Cloud (GCP) + Automation (GitHub Actions).
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Step by Step Full DevOps Project: We will create a Kubernetes Cluster with High Availability, Auto-Healing, Reliability, Auto-Scaling, Monitoring, and Security on Amazon EKS using Terraform or CloudFormation. To do these, we will create and use GitOps Workflow(ArgoCD), Jenkins, Rancher, Amazon Elastic Kubernetes Service (EKS), RDS MySQL Database, VPC (with both public and private subnets) for Amazon EKS, AWS Secrets Manager, Amazon Route53, Amazon Cloudfront, AWS Certificate Manager, Let's Encrypt-Cert Manager, CloudWatch, Prometheus, and Grafana. We will do these practically, step by step.
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