Architecting with Google Cloud: Design and Process (GCP-DP)

This course teaches participants the following skills:

• Apply a tool set of questions, techniques, and design considerations
• Define application requirements and express them objectively as KPIs, SLOs and SLIs
• Decompose application requirements to find the right microservice boundaries
• Leverage Google Cloud developer tools to set up modern, automated deployment pipelines
• Choose the appropriate Cloud Storage services based on application requirements
• Architect cloud and hybrid networks
• Implement reliable, scalable, resilient applications balancing key performance metrics with cost
• Choose the right Google Cloud deployment services for your applications
• Secure cloud applications, data, and infrastructure
• Monitor service level objectives and costs using Google Cloud tools

To get the most out of this course, participants should have:

• Have completed Architecting with Google Compute Engine, Architecting with Google Kubernetes Engine, or have equivalent experience
• Have basic proficiency with command-line tools and Linux operating system environments
• Have systems operations experience, including deploying and managing applications, either on-premises or in a public cloud environment

This class is intended for the following participants:

• Cloud Solutions Architects, Site Reliability Engineers, Systems Operations professionals, DevOps Engineers, IT managers.
• Individuals using Google Cloud Platform to create new solutions or to integrate existing systems, application environments, and infrastructure

Module 1: Defining the Service

• 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

Module 2: Microservice Design and Architecture

• 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

Module 3: DevOps Automation

• 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

Module 4: Choosing Storage Solutions

• Choose the appropriate Google Cloud data storage service based on 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

Module 5: Google Cloud and Hybrid Network Architecture

• 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 centers using Cloud Interconnect

Module 6: Deploying Applications to Google Cloud

• 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

Module 7: Designing Reliable Systems

• 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

Module 8: Security

• Design secure systems using best practices like separation of concerns, 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

Module 9: Maintenance and Monitoring

• 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