In this advanced lab, you will design and implement a CI/CD pipeline for an e-commerce company deploying services on Google Kubernetes Engine (GKE). The lab focuses on integrating Cloud Build and Cloud Deploy for automating build and deployment processes, implementing secure storage of sensitive information using Secret Manager, and applying security policies utilizing Binary Authorization. Emphasizing security and efficiency, you will also explore scaled deployments using GKE's Horizontal Pod Autoscaler (HPA) and implement strategies for assessing pipeline failures through advanced logging and monitoring. This lab simulates a typical medium-sized enterprise digital transformation scenario, where a legacy system is migrating to cloud-native architectures, requiring careful resource management to stay within operational budgets.
Your company, E-Shop Inc., aims to enhance its deployment processes for the upcoming holiday shopping season by leveraging Google Kubernetes Engine for scalability. Given the expected increase in traffic, you need to ensure the CI/CD pipeline is efficient and can handle rapid deployments while maintaining security standards. You will use Cloud Build and Cloud Deploy to set up automation from code commit to production deployment and manage secrets storage securely to protect sensitive information such as API keys and database credentials. Key metrics include achieving a deployment time under 5 minutes and reducing the average rollback time to under 2 minutes, ensuring high availability and scalability are maintained.
