Architecting with Google Cloud Platform: Design and Process Training in Germany

• Describe users in terms of roles and personas • Write qualitative requirements with user stories • Write quantitative requirements using key performance indicators (KPIs) • Evaluate KPIs using SLOs and SLIs • Determine the quality of application requirements using SMART criteria

• Decompose monolithic applications into microservices • Recognize appropriate microservice boundaries • Architect stateful and stateless services to optimize scalability and reliability • Implement services using 12-factor best practices • Build loosely coupled services by implementing a well-designed REST architecture • Design consistent, standard RESTful service APIs

• Automate service deployment using CI/CD pipelines • Leverage Cloud Source Repositories for source and version control • Automate builds with Cloud Build and build triggers • Manage container images with Google Container Registry • Create infrastructure with code using Deployment Manager and Terraform

• Choose the appropriate Google Cloud data storage service based on the use case, durability, availability, scalability and cost • Store binary data with Cloud Storage • Store relational data using Cloud SQL and Spanner • Store NoSQL data using Firestore and Cloud Bigtable • Cache data for fast access using Memorystore • Build a data warehouse using BigQuery

• Design VPC networks to optimize for cost, security, and performance • Configure global and regional load balancers to provide access to services • Leverage Cloud CDN to provide lower latency and decrease network egress • Evaluate network architecture using the Cloud Network Intelligence Center • Connect networks using peering and VPNs • Create hybrid networks between Google Cloud and on-premises data centres using Cloud Interconnect

• Choose the appropriate Google Cloud deployment service for your applications • Configure scalable, resilient infrastructure using Instance Templates and Groups • Orchestrate microservice deployments using Kubernetes and GKE • Leverage App Engine for a completely automated platform as a service (PaaS) • Create serverless applications using Cloud Functions

• Design services to meet requirements for availability, durability, and scalability • Implement fault-tolerant systems by avoiding single points of failure, correlated failures, and cascading failures • Avoid overload failures with the circuit breaker and truncated exponential backoff design patterns • Design resilient data storage with lazy deletion • Analyze disaster scenarios and plan for disaster recovery using cost/risk analysis

• Design secure systems using best practices like separation of concerns, the principle of least privilege, and regular audits • Leverage Cloud Security Command Center to help identify vulnerabilities • Simplify cloud governance using organizational policies and folders • Secure people using IAM roles, Identity-Aware Proxy, and Identity Platform • Manage the access and authorization of resources by machines and processes using service accounts • Secure networks with private IPs, firewalls, and Private Google Access • Mitigate DDoS attacks by leveraging Cloud DNS and Cloud Armor

• Manage new service versions using rolling updates, blue/green deployments, and canary releases • Forecast, monitor, and optimize service cost using the Google Cloud pricing calculator and billing reports and by analyzing billing data • Observe whether your services are meeting their SLOs using Cloud Monitoring and Dashboards • Use Uptime Checks to determine service availability • Respond to service outages using Cloud Monitoring Alerts