The GCP Platform Engineer Learning Path equips professionals with the skills needed to design, automate, and manage scalable cloud environments on Google Cloud. This course covers core GCP services, networking, security, Infrastructure as Code (IaC) with Deployment Manager and Terraform, and CI/CD implementation using Cloud Build. Participants will gain hands-on experience in monitoring, cost optimization, and governance while learning to build resilient, high-availability architectures. Through real-world projects and a capstone challenge, learners will deploy and maintain secure cloud solutions, integrating automation and operational best practices. This program is ideal for engineers looking to master GCP platform engineering and prepare for Google Cloud certifications.
Understand the responsibilities of a GCP Platform Engineer, including infrastructure design, automation, and operational excellence.
Learn about Google Cloud’s regions, zones, and edge locations, as well as how its global network supports high availability.
Review key concepts such as IaaS, PaaS, SaaS, and the GCP shared responsibility model.
Dive into essential services such as Compute Engine, Cloud Storage, and Virtual Private Cloud (VPC).
Explore VPC configuration, subnets, firewall rules, and Cloud Load Balancing.
Understand Identity and Access Management (IAM), service accounts, and best practices for securing GCP environments.
Learn how to deploy and manage virtual machines and configure auto-scaling for high performance.
Explore Google Kubernetes Engine for containerized workloads, including cluster setup, management, and security.
Understand how to leverage Cloud Functions, Cloud Run, and App Engine for building scalable serverless applications.
Study load balancing, failover strategies, and design patterns that ensure resilient architectures.
Explore Cloud Storage, Persistent Disks, and Filestore, and learn best practices for data durability and performance.
Dive into Cloud SQL, Cloud Spanner, Firestore, and Bigtable, comparing relational and NoSQL options.
Understand strategies for data ingestion, transformation, backup, and recovery using GCP tools.
Master infrastructure as code using Google Cloud Deployment Manager and Terraform to automate resource provisioning.
Enhance your automation skills with the gcloud CLI, Python, or Bash scripting for repetitive tasks.
Explore how to use Cloud Functions and Cloud Scheduler for event-driven automation within GCP.
Understand the principles of CI/CD and how to apply them using Cloud Build, Container Registry, and Cloud Source Repositories.
Build and manage pipelines that automate application deployment, testing, and security scans.
Incorporate automated testing, vulnerability scanning, and code quality checks into your CI/CD workflows.
Utilize Cloud Monitoring, Cloud Logging, and Cloud Trace to collect performance metrics and monitor system health.
Set up dashboards and alerts to track key performance indicators and proactively manage incidents.
Develop strategies for diagnosing issues, optimizing resource utilization, and ensuring service reliability.
Learn to monitor, analyze, and optimize expenses using GCP Cost Management tools and budgets.
Implement labeling strategies and policies to enforce resource governance and compliance.
Master techniques for forecasting costs, managing budgets, and optimizing resource allocation.
Study advanced design patterns for building scalable, fault-tolerant, and highly available systems on GCP.
Explore strategies for deploying applications across multiple regions and integrating on-premises environments.
Stay updated on the latest GCP services and innovations impacting platform engineering and cloud-native architectures.
Engage in practical projects that integrate the key GCP concepts covered in this learning path. For example, deploy a cloud-native application on GCP using Compute Engine, GKE, Cloud Storage, and Virtual Private Cloud (VPC). Implement automation with Google Cloud Deployment Manager or Terraform and integrate CI/CD pipelines using Cloud Build, Container Registry, and Cloud Source Repositories.
Prepare for Google Cloud certifications such as the Associate Cloud Engineer and Professional Cloud Architect to validate your expertise.
Set up Virtual Private Cloud (VPC) with subnets, firewall rules, and private IP ranges.
Configure Compute Engine instances, Managed Instance Groups, and Load Balancing.
Implement IAM roles and security policies to secure the deployed environment.
Configure GKE clusters and deploy Docker-based microservices.
Implement autoscaling, load balancing, and ingress management.
Secure the GKE cluster using role-based access control (RBAC) and workload identity.
Implement event-driven automation using Cloud Functions and Cloud Scheduler.
Deploy containerized web services using Cloud Run.
Create fully managed web applications using App Engine Standard or Flexible.
Implement encrypted Cloud Storage buckets with lifecycle policies.
Deploy managed databases (Cloud SQL, Cloud Spanner, Firestore) with optimized performance and backups.
Ensure high availability and disaster recovery configurations for data services.
Write and deploy Terraform scripts and Deployment Manager configurations.
Automate deployment workflows using custom scripts (gcloud CLI, Python).
Integrate automated IaC scanning tools (Terrascan, Checkov) for secure deployments.
Set up automated build and deployment workflows using Cloud Build.
Automate container builds, security scans (vulnerability analysis), and deployments to GKE or Cloud Run.
Configure rollbacks and automated notifications in case of deployment failures.
Set up custom dashboards and alerts using Cloud Monitoring.
Implement logging strategies using Cloud Logging for auditing and troubleshooting.
Perform distributed tracing with Cloud Trace to diagnose and improve performance.
Configure budgets, alerts, and forecasts with GCP Cost Management tools.
Implement resource labeling and enforce governance using IAM and Organization Policies.
Identify resource inefficiencies and recommend cost optimization actions.
Deploy comprehensive infrastructure using Terraform and Deployment Manager.
Create a robust CI/CD pipeline integrating automated testing, vulnerability scanning, and security validation.
Implement container orchestration with GKE, leveraging advanced networking and security features.
Ensure high availability through multi-region deployments, load balancing, and automated failover strategies.
Configure monitoring, logging, and alerting solutions for full observability.
Optimize and govern cloud costs through strategic tagging, budgeting, and usage tracking.