Course Overview of Google Cloud Infrastructure for AWS Professionals

This course is specifically designed for cloud architects and engineers with existing AWS knowledge. It provides a comparative deep dive into Google Cloud solutions versus AWS equivalents. Through lectures and 11 hands-on labs, professionals will learn to apply their existing cloud knowledge to explore similarities, differences, and best practices for building infrastructure on Google Cloud. 

After completing Google Cloud Infrastructure for AWS Professionals, students will be able to:

  • Map AWS resource and access management concepts to Google Cloud (IAM, Resource Hierarchy).
  • Implement secure, scalable networks using VPC, Cloud VPN, and Google Cloud Firewall.
  • Provision and customize VM instances and manage autoscaling.
  • Select and implement the appropriate data storage services for various workloads.
  • Deploy and manage containerized applications using Google Kubernetes Engine (GKE).
  • Develop serverless applications using Cloud Run and Cloud Run functions.
  • Monitor and maintain infrastructure health using Google Cloud’s operations suite.

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Key Features of Google Cloud Infrastructure for AWS Professionals

  • Tailored for AWS Experts: Uses a comparative approach (e.g., EC2 to Compute Engine, S3 to Cloud Storage) to accelerate learning.

  • Hands-on Intensive: Features 11 practical labs to reinforce theoretical mappings with real-world configuration experience. 

  • Comprehensive Infrastructure Coverage: Includes networking, compute, storage, containers, and serverless application development. 

  • Best Practices Focus: Emphasizes Google-recommended practices for resource management, security, and monitoring.

  • Operations Suite Mastery: Covers the Google Cloud operations suite, including logging, monitoring, and alerting.

Who should Attend Google Cloud Infrastructure for AWS Professionals

  • Cloud Architects and Engineers with existing AWS knowledge.

Prerequisites of Google Cloud Infrastructure for AWS Professionals

  • Professional-level experience with AWS infrastructure
  • Familiarity with core cloud concepts (virtualization, networking, and storage)

Why choose CloudThat as your training partner for Google Cloud Infrastructure for AWS Professionals

  • 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 objective of Google Cloud Infrastructure for AWS Professionals

  • Identity & Governance: Explain best practices for incorporating resources and access management.
  • Networking: Build virtual networks using VPCs and secure them with native firewalls. 
  • Compute Services: Create VM instances, configure load balancers, and implement autoscaling.
  • Storage Solutions: Differentiate and implement Google Cloud storage services.
  • Containerization: Design and deploy solutions using GKE clusters and deployments.
  • Application Development: Identify use cases for Cloud Run and Cloud Run functions. 
  • Operational Excellence: Use Cloud Monitoring to create charts, alerts, and uptime checks.

Course Outline of Google Cloud Infrastructure for AWS Professionals Download Course Outline

Lecture Content

  • Introduction to Google Cloud platform structures
  • Mapping core infrastructure concepts from AWS to Google Cloud solutions
  • Exploring structural similarities and structural differences between AWS and Google Cloud ecosystems

Learning Objectives

  • Apply existing concepts and technologies knowledge in AWS to explore similarities and differences with Google Cloud

Lab Content

  • NA

Lecture Content

  • Enterprise resource hierarchy design (Organizations, Folders, Projects)
  • Identity and Access Management (IAM) permissions, service accounts, and resource grouping
  • Mapping AWS Account structures and AWS IAM tenancy models to Google Cloud

Learning Objectives

  • Explain best practices for Google Cloud solutions that incorporate resources and access management

Lab Content

  • Lab: Access Management

Lecture Content

  • Virtual Private Cloud (VPC) subnets and global architecture
  • Google Cloud Firewall configurations, hierarchical firewall policies, and target tags
  • High Availability Cloud Virtual Private Network (HA VPN) architectures
  • Comparing AWS VPC regional boundaries with Google Cloud's global VPC capabilities

Learning Objectives

  • Implement Google Cloud networks by using best practices for Cloud VPN, Virtual Private Cloud (VPC), and Google Cloud Firewall

Lab Content

  • Lab: Configuring a Virtual Private Cloud (VPC) Network
  • Lab: Configuring an HA VPN

Lecture Content

  • Customizing and creating Virtual Machine (VM) instances using Compute Engine
  • Configuring Managed Instance Groups (MIGs), autoscaling rules, and autohealing
  • Google Cloud Load Balancing choices (HTTP(S), TCP, Internal vs External proxying)
  • Translating Amazon EC2, Auto Scaling Groups, and AWS Elastic Load Balancing (ELB) paradigms

Learning Objectives

  • Create and customize virtual machine (VM) instances using Compute Engine
  • Configure load balancers and autoscaling for VM instances

Lab Content

  • Lab: Configuring an HTTP Load Balancer with Autoscaling
  • Lab: Configuring an Internal Load Balancer

Lecture Content

  • Object storage frameworks with Cloud Storage and lifecycle management policies
  • Managed relational databases with Cloud SQL and enterprise-scale Google Cloud Spanner
  • Scalable NoSQL structures with Cloud Bigtable and Firestore
  • Mapping Amazon S3, Amazon RDS, DynamoDB, and Aurora to Google Cloud storage tiers

Learning Objectives

  • Implement and evaluate data storage services in Google Cloud

Lab Content

  • Lab: Cloud Storage
  • Lab: Cloud SQL

Lecture Content

  • Container optimization principles and Kubernetes fundamentals
  • Google Kubernetes Engine (GKE) concepts and control plane architecture
  • Managing GKE Deployments, pods, services, and cluster networking
  • Hybrid and multi-cloud infrastructure orchestration utilizing GKE Enterprise
  • Comparing Amazon EKS workflows with GKE ecosystems

Learning Objectives

  • Design a containerized solution using Google Kubernetes Engine (GKE) for deploying applications
  • Provision a Kubernetes cluster using GKE and manage Deployments
  • Identify the purpose and architectural use cases of hybrid and multi-cloud computing via GKE Enterprise

Lab Content

  • Lab: Getting started with Google Kubernetes Engine
  • Lab: Creating Google Kubernetes Engine Deployments

Lecture Content

  • Developing, modernizing, and hosting serverless architectures in Google Cloud
  • Microservice deployments using containerized pipelines in Cloud Run
  • Event-driven architectures and lightweight code deployment with Cloud Run functions
  • Aligning AWS App Runner and AWS Lambda competencies with Google Cloud's application development stack

Learning Objectives

  • Identify the purpose, scalability parameters, and core use cases for Cloud Run
  • Deploy a containerized microservice application on Cloud Run
  • Describe how Cloud Run functions can support application development and event-driven backends

Lab Content

  • Lab: Hello Cloud Run

Lecture Content

  • Full-stack tracking methodologies with the Google Cloud operations suite
  • Designing telemetry dashboards, alerting thresholds, and infrastructure uptime checks via Cloud Monitoring
  • Collecting system and application metrics across GKE Clusters
  • Map-matching Amazon CloudWatch and AWS CloudTrail tools into the Google Cloud operations workspace

Learning Objectives

  • Examine best practices for the deployment, monitoring, and debugging of Google Cloud infrastructure
  • Describe Google Cloud's operations suite capabilities
  • Create performance charts, alerts, and active uptime checks for infrastructure resources with Cloud Monitoring
  • Describe systematic log and metric collections within GKE

Lab Content

  • Lab: Monitoring a Compute Engine VM using Ops Agent

Certification details of Google Cloud Infrastructure for AWS Professionals

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

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FAQs for Google Cloud Infrastructure for AWS Professionals

No, it is an intermediate course that assumes you already understand cloud computing through the lens of AWS.

The course features 11 hands-on labs.

Yes, Module 04 covers Compute Engine and how it compares to AWS EC2.

Yes, Module 06 is dedicated to Google Kubernetes Engine (GKE).

You will learn about Cloud Storage, which serves as the equivalent to S3.

Yes, it touches on hybrid and multi-cloud computing using GKE Enterprise.

Yes, Module 07 covers Cloud Run and Cloud Run functions (comparable to AWS Lambda/Fargate).

Module 08 teaches you how to use the Google Cloud operations suite for monitoring and alerting.

It is a 2-day, instructor-led course.

Yes, including VPC design, VPNs, and firewall configuration.

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