Architecting with Google Cloud: Design and Process
Already comfortable working in Google Cloud? Take the next step with Architecting with Google Cloud Platform: Design and Process—a two-day instructor-led course that equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns and architectural best practices.
This design and process training combines a combination of presentations, design activities, and hands-on labs. It assumes hands-on experience with the technologies covered in either the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course. You’ll analyze key performance indicators, apply service level objectives, and explore how to design and operate cloud deployments that are highly reliable in production.
This Google Cloud training equips students to apply real-world architectural strategies to operate deployments in a highly available and cost-effective manner. You’ll learn how to define application needs using KPIs and SLOs, select the right Google Cloud storage and compute services, and balance performance, reliability, and cost. You'll also explore cloud infrastructure design, CI/CD automation, and security and access management. This course supports professionals designing solutions on Google Cloud using tools and design principles aligned with Google’s best practices.
Ideal for cloud solutions architects, DevOps engineers, site reliability engineers, IT managers, and systems operations professionals, this instructor-led course is for individuals using Google Cloud to create new solutions or integrate existing systems in modern application environments.
- Architecting with Google Compute Engine (AGCE), Architecting with Google Kubernetes Engine (AGKE), or have equivalent experience
- Basic proficiency with command-line tools and Linux operating system environments
- Systems Operations experience including deploying and managing applications, either on-premises or in a public cloud environment
- Identify user roles and personas
- Define app needs using key performance indicators and SMART criteria
- Translate needs into service level objectives
- Decompose monoliths into microservices
- Apply 12-factor best practices
- Use RESTful API design
- Build CI/CD pipelines with Cloud Build
- Manage repositories and containers
- Automate deployment with Deployment Manager and Terraform
- Compare Google Cloud storage options for use cases and cost
- Use Cloud SQL, Spanner, BigQuery, Memorystore, Firestore, Bigtable
- Select optimal tools for scalability and data availability
- Design VPC networks for performance and cost-effective routing
- Configure load balancing, Cloud CDN, and hybrid connectivity
- Use Network Intelligence Center for architecture review
- Choose the right deployment model for app needs
- Use Cloud Functions, App Engine, GKE
- Apply serverless and scalable cloud computing practices
- Avoid common failure points in cloud infrastructure
- Plan disaster recovery with cost/risk analysis
- Address reliability with patterns like exponential backoff
- Apply least privilege and audit practices
- Use IAM, IAP, Identity Platform, and Private Google Access
- Secure your systems with Cloud Armor, DNS, and firewalls
- Use blue/green, canary, and rolling updates
- Monitor uptime, alerts, and billing via dashboards
- Optimize SLO compliance and cost using Google Cloud tools