Architecting with Google Cloud: Design and Process

This two-day instructor-led class equips students to build highly reliable and efficient Google Cloud solutions using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine courses, and supposes a practical experience with the technologies covered in any of these courses.
Through a combination of presentations, design activities, and hands-on labs, participants learn to define and balance business and technical requirements to design highly reliable, highly available, secure, and cost-effective Google Cloud deployments.

Objectives

In this course, participants will learn the following skills:
  • Apply a set of question tools, techniques, and design considerations.
  • Define the application requirements and express them objectively as KPI, SLO and SLI
  • Decompose application requirements to find the correct microservice limits
  • Leverage Google Cloud development tools to configure modern, automated deployment channels
  • Choosing the right cloud storage services based on application requirements
  • Architect cloud and hybrid networks
  • Deploy reliable, scalable, and resilient applications that balance key performance metrics with cost
  • Choosing the right Google Cloud deployment services for your apps
  • Protect applications, data and infrastructure in the cloud
  • Monitor service level goals and costs using Google Cloud tools

Audience

This class is aimed at the following audience:

Prerrequisites

To fully benefit from this course, participants must comply with the following criteria:

Duration

16 hours (2 days)

Investment

Check the next open public class in our enrollment page.
If you are interested in a private training class for your company, contact us.
Architecting with Google Cloud: Design and Process dependencies with other courses and certifications
Architecting with Google Cloud: Design and Process dependencies with other courses and certifications

Course Outline

The course includes presentations, demonstrations, and hands-on labs.
  • 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 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 centers 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, 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