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Overview

This two-day instructor-led class equips students to build highly reliable and efficient solutions on Google Cloud using proven design patterns. It is a continuation of the Architecting with Google Compute Engine or Architecting with Google Kubernetes Engine course and assumes hands-on experience with the technologies covered in either of those courses.

Through a combination of presentations, design activities, and hands-on labs, participants learn to define and balance business and technical requirements to design Google Cloud deployments that are highly reliable, highly available, secure, and cost-effective.

Target audience

This course is intended for the following participants:

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

Prerequisites

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

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

Learning Outcomes

  • 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

Course Outline

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

GCP Learning Paths

Want to boost your career in GCP? Click on the roles below to see QA‘s learning pathways, specially designed to give you the skills to succeed.

= Required
= Certification
Data Scientist
Data Engineer
Developer Software Development Experience
Architect Enterprise Architecture Experience
Administrator Windows Administrator Experience
Data Engineer Average salary: £70,000*

Total individual course price: £7,996 ex VAT

Bundle price: £6,505 ex VAT

Saving: £1,491

10 days

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Administrator Average salary: £51,250*

Total individual course price: £3,840 ex VAT

Bundle price: £3,090 ex VAT

Saving: £750

5 days

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Key for bundle contents
= Exam Preparation
= Exam
= Practice Exam
= Exam Voucher
= Tutor Support
= Pre Course Work
*This is based on QA research

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