Course Overview of Architecting with Google Cloud Design and Process

Cloud Composer is a fully managed workflow orchestration service built on Apache Airflow. This course provides a comprehensive guide to provisioning Composer instances, creating and managing Airflow Directed Acyclic Graphs (DAGs), and performing essential tasks such as testing, debugging, and monitoring workflows.

After Completing Architecting with Google Cloud Design and Process, students will be able to

  • Apply questions and techniques to define application requirements objectively as KPIs, SLOs, and SLIs.
  • Decompose requirements to identify appropriate microservice boundaries.
  • Set up modern, automated deployment pipelines using Google Cloud developer tools.
  • Select appropriate storage and network architectures, including hybrid options.
  • Implement resilient and scalable applications while balancing performance with cost.
  • Secure cloud infrastructure, data, and applications.
  • Monitor service level objectives and manage service costs.

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Key Features of Architecting with Google Cloud Design and Process

  • Proven Design Patterns- Focuses on using established patterns to build reliable and efficient cloud solutions. 

  •  Hands-On Learning- Features a combination of lectures, design activities, and practical labs. 

  • Expert Toolset- Provides a toolkit of questions and techniques for defining application requirements. 

  • Full Lifecycle Coverage- Covers everything from initial requirements and microservice boundaries to automated deployment and monitoring. 

  •  Operational Excellence- Includes specific modules on reliability, security, and cost optimization. 

Who should Attend Architecting with Google Cloud Design and Process?

  • Cloud Architects
  • Solutions Architects
  • People responsible for designing Google Cloud infrastructure.

Prerequisites of Architecting with Google Cloud Design and Process

Completion of Architecting with Google Compute Engine OR Architecting with Google Kubernetes Engine.

Why choose CloudThat as your training partner for Architecting with Google Cloud Design and Process?

  • Specialized GCP Focus- CloudThat specializes in cloud technologies, offering focused and specialized training programs. We are Authorized Trainers for the Google Cloud Platform. This specialization ensures in-depth coverage of GCP services, use cases, best practices, and hands-on experience tailored specifically for GCP. 
  • Industry-Recognized Trainers- CloudThat has a strong pool of industry-recognized trainers certified by GCP. These trainers bring real-world experience and practical insights into the training sessions, comprehensively understanding how GCP is applied in different industries and scenarios. 
  • Hands-On Learning Approach- CloudThat emphasizes a hands-on learning approach. Learners can access practical labs, real-world projects, and case studies that simulate actual GCP environments. This approach allows learners to apply theoretical knowledge in practical scenarios, enhancing their understanding and skill set. 
  • Customized Learning Paths- CloudThat understands that learners have different levels of expertise and varied learning objectives. We offer customized learning paths, catering to beginners, intermediate learners, and professionals seeking advanced GCP skills. 
  • Interactive Learning Experience- CloudThat's training programs are designed to be interactive and engaging. We utilize various teaching methodologies like live sessions, group discussions, quizzes, and mentorship to keep learners engaged and motivated throughout the course. 
  • Placement Assistance and Career Support- CloudThat often provides placement assistance and career support services. This includes resume building, interview preparation, and connecting learners with job opportunities through our network of industry partners and companies looking for GCP-certified professionals. 
  • Continuous Learning and Updates- CloudThat ensures that our course content is regularly updated to reflect the latest trends, updates, and best practices within the GCP ecosystem. This commitment to keeping the content current enables learners to stay ahead in their GCP knowledge. 
  • Positive Reviews and Testimonials- Reviews and testimonials from past learners can strongly indicate the quality of training provided. You can Check feedback and reviews about our GCP courses that can provide potential learners with insights into the effectiveness and value of the training. 

Learning Objectives of Architecting with Google Cloud Design and Process

  • Requirement Definition- Express requirements as objective performance metrics (KPIs, SLOs, SLIs). 
  • Architectural Design- Choose the right deployment and storage services based on specific needs. 
  • Reliability Engineering- Design services for high availability, durability, and scalability.  
  • Security Governance- Identify best practices for secure systems and leverage organizational policies.
  • Operational Monitoring- Observe services against SLOs and respond to outages using Cloud Monitoring Alerts. 

Course Outline for Architecting with Google Cloud Design and Process Download Course Outline

Lecture Content

  • Core overview of cloud-native architecture patterns
  • Evolution of legacy infrastructure into elastic cloud environments
  • Introduction to the case studies and architecture review frameworks

Learning Objectives

  • Navigate the foundational framework of Google Cloud-recommended design patterns
  • Evaluate cloud architectures against enterprise scaling demands

Lecture Content

  • Differentiating between business metrics and technical system targets
  • Engineering Key Performance Indicators (KPIs) for cloud software
  • Designing Service Level Indicators (SLIs) and quantifiable Service Level Objectives (SLOs)
  • Calculating and managing Error Budgets across system release cycles

Learning Objectives

  • Define, map, and implement precise SLIs, SLOs, and SLAs for application stacks
  • Balance enterprise development velocity with system stability using Error Budgets

Lab Content

  • Defining and Monitoring Performance Indicators and Service Level Objectives

Lecture Content

  • Domain-Driven Design (DDD) principles: Finding subdomains and context boundaries
  • Monolithic breakdown strategies and microservice isolation patterns
  • Decoupling application communications: Synchronous REST/gRPC vs. Asynchronous Pub/Sub
  • Deployment service mapping: Google Kubernetes Engine (GKE), Cloud Run, and Compute Engine

Learning Objectives

  • Establish logical microservice boundaries within a large-scale monolithic application
  • Choose optimal Google Cloud computing platforms based on operational overhead and scale

Lab Content

  • Deconstructing a Monolith into Microservices on GKE and Cloud Run

Lecture Content

  • Principles of Continuous Integration and Continuous Deployment (CI/CD) for microservices
  • Infrastructure as Code (IaC) architectures leveraging Terraform templates
  • Managing multi-environment release branches (Development, Staging, Production)
  • Automating code delivery using Cloud Build, Artifact Registry, and Cloud Deploy

Learning Objectives

  • Construct secure, automated CI/CD deployment pipelines using Google Cloud tools
  • Provision reproducible infrastructure environments programmatically via Terraform

Lab Content

  • Automating Multi-Environment Microservice Deployments with Cloud Build

Lecture Content

  • Storage tier classifications: Object, Block, Relational, and Non-Relational (NoSQL)
  • Evaluating trade-offs between Cloud Storage, Cloud SQL, Cloud Spanner, and Firestore
  • Understanding database parameters: ACID compliance vs. BASE models and global scaling
  • Caching strategies using Memorystore to accelerate application read request paths

Learning Objectives

  • Evaluate business application storage requirements against database limitations
  • Architect globally resilient and performant storage systems using Google Cloud data services

Lab Content

  • Orchestrating Polyglot Persistence Layers for Microservice Applications

Lecture Content

  • Enterprise-grade Virtual Private Cloud (VPC) design and global routing structures
  • Connecting disparate networks: VPC Network Peering, Shared VPC, and Hybrid Networking
  • Hybrid cloud patterns: High Availability Cloud VPN vs. Dedicated Cloud Interconnect
  • Traffic optimization using Cloud DNS routing policies and global Content Delivery Networks (CDN)

Learning Objectives

  • Architect scalable, secure global cloud networks containing strict boundary conditions
  • Implement highly available hybrid connections between on-premises sites and Google Cloud

Lab Content

  • Configuring Global Shared VPCs and Hybrid HA VPN Cross-Connections

Lecture Content

  • Structural engineering patterns for High Availability (HA) and Disaster Recovery (DR)
  • Configuring Managed Instance Groups (MIGs), health checks, and cross-region load balancers
  • Autoscaling triggers, scaling policies, and stateful vs. stateless server patterns
  • Mitigating failures using circuit breakers, retries with exponential backoff, and graceful degradation

Learning Objectives

  • Design a fault-tolerant cloud solution capable of automatic recovery from zonal failures
  • Implement defensive microservice patterns to avoid cascading systemic failures

Lab Content

  • Engineering Resilient Infrastructure with Global Load Balancing and Autoscaling

Lecture Content

  • Implementing Zero-Trust security postures using Identity-Aware Proxy (IAP)
  • IAM best practices: Fine-grained permissions, custom roles, and service account keys
  • Perimeter security management: Cloud Armor policies for Layer 7 WAF and DDoS mitigation
  • Compliance tracking, enterprise resource organization governance, and Cloud KMS encryption keys

Learning Objectives

  • Secure application environments against multi-vector external DDoS and web-application attacks
  • Enforce strict least-privilege identity boundaries using Google Cloud IAM structures

Lab Content

  • Hardening Microservice Architectures with Cloud Armor, IAP, and Strict IAM

Lecture Content

  • Release management paradigms: Blue-Green deployments, Canary rollouts, and automatic rollbacks
  • Continuous cost monitoring, cloud usage forecasting, and pricing optimizations
  • Deep-dive full-stack monitoring: Cloud Logging, Cloud Monitoring, Trace, Profiler, and Error Reporting
  • Configuring synthetic uptime checks, tracking system health trends, and threshold alerting rules

Learning Objectives

  • Execute continuous zero-downtime application upgrades using advanced deployment routing
  • Troubleshoot production microservice bottlenecks using Google Cloud observability suites

Lab Content

  • Setting Up Full-Stack Cloud Monitoring, Trace Diagnostics, and Uptime Alerting

Certification Details of Architecting with Google Cloud Design and Process

    CloudThat Course Completion Certificate will be awarded to all learners who complete the training.

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Course ID: 29162

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FAQs for Architecting with Google Cloud Design and Process

This is a 2-day course. 

It is an Intermediate level course. 

Yes, you should have completed "Architecting with Google Compute Engine" or "Architecting with Google Kubernetes Engine".

Yes, it includes several labs, such as those in Modules 6 and 9.

Yes, Module 9 specifically covers how to forecast, monitor, and optimize service costs.

Yes, it discusses Google Cloud network architectures, including hybrid options.

Each module typically includes lectures, design activities, quizzes, and/or labs.

Yes, the course teaches you to respond to outages using Cloud Monitoring Alerts.

Yes, Module 8 focuses on designing secure systems and mitigating DDoS attacks.

It focuses on setting up modern, automated deployment pipelines using Google Cloud developer tools. 

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