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

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

3) DevOps Automation

• Automate service deployment using CI/CD pipelines

• Leverage Cloud Source Repositories for source and version control

• Automate builds with Google Cloud Build and build triggers

• Manage container images with Google Container Registry

• Create infrastructure with code using Deployment Manager and Terraform

4) Choosing Storage Solutions

• Storage binary data with Cloud Storage

• Store relational data using Cloud SQL and Spanner

• Store NoSQL data using Firestore and BigTable

• Cache data for fast access using Memorystore

• Build a data warehouse using BigQuery

• Choose the appropriate Google Cloud data storage service based use case, durability, availability, scalability and cost

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 Network Intelligence Center

• Connect networks using peering and VPNs

• Create hybrid networks between Google Cloud and on-premises data centers

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 Google Cloud Functions

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 the 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

8) Security

• Design secure systems using best-practices like separation of concerns,
  principle of least privilege and regular audits

• Leverage Google Cloud Security Command Center to help identify vulnerabilities

• Simplify cloud governance using or organization 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 with private IPs, firewalls and Google Cloud private access

• Mitigate DDoS attacks by leveraging Cloud DNS and Cloud Armor

9) Maintenance and Monitoring

• Forecast, monitor and optimize service cost using the Google Cloud pricing
  calculator, billing reports and by analyzing billing data

• Observe if your services are meeting their SLOs using Stackdriver Monitoring
  and Dashboards

• Use Uptime Checks to determine service availability

• Respond to service outages using Stackdriver Alerts

• Manage new service versions using rolling updates, blue-green deployments
  and canary releases