GCP200AZURE
Google Cloud Infrastructure for Azure Professionals
This is a course for cloud architects and engineers with existing Azure knowledge that compares Google Cloud solutions with Azure and guides professionals on their use. In this course, you'll apply the concepts and technologies knowledge in Azure to explore the similarities and differences with concepts and technologies in Google Cloud. You'll get hands-on practice building and managing Google Cloud resources.
What you will learn
- Explain best practices for the Google Cloud solutions that incorporate resources and access management in Google Cloud.
- Implement Google Cloud networks by using best practices for Cloud virtual private network (VPN), Virtual Private Cloud (VPC), and Google Cloud Firewall.
- Create and customize virtual machine (VM) instances using Compute Engine.
- Configure load balancers and autoscaling for VM instances.
- Implement data storage services in Google Cloud.
- Design a solution using Google Kubernetes Engine (GKE) for deploying applications in Google Cloud.
- Examine best practices for deploying and monitoring of Google Cloud infrastructure.
- Identify the purpose and use cases for Cloud Run.
Prerequisites
- Familiarity with Azure terms and concepts
Target audience
- Cloud architects or cloud engineers who are experienced with Azure cloud.
Training Program
8 modules to master the fundamentals
Objectives
- Review the Azure resource hierarchy.
- Explore how IAM lets you apply policies that define who can do what on which resources in Google Cloud.
- Examine service account types and keys in Google Cloud.
- Navigate through Google Cloud console and Cloud Shell to perform basic tasks.
Topics covered
- →Google Cloud resource hierarchy
- →Identity and Access Management (IAM)
- →Service accounts
- →Interacting with Google Cloud
Activities
Lab: Exploring Identity and Access Management
Objectives
- Compare networking concepts in Azure and Google Cloud.
- Understand VPC networking on Google Cloud.
- Explain how Google Virtual Private Cloud (VPC) differs from Azure VPC.
- Create and configure Private Google Access and Cloud NAT.
- Determine which Google Cloud interconnect or peering service to use in specific circumstances.
Topics covered
- →Networking concepts in Azure and Google Cloud
- →Virtual Private Cloud Networking
- →Lab: VPC Networking
- →Cloud Routing
- →Interconnecting Networks
- →Lab: Implement private Google access and Cloud NAT
Activities
Lab: VPC Networking
Lab: Implement private Google access and Cloud NAT
Objectives
- List the various CPU, GPU, and memory options for virtual machines.
- Explore Google Cloud images.
- Explain where you would want to use Spot VMs in Google Cloud.
Topics covered
- →Google Compute Engine
- →Machine types and images
- →Spot VMs
Activities
Lab: Getting started with Compute Engine
Objectives
- Explain Cloud Load Balancing features in Google Cloud.
- Describe Managed instance groups and how to use them.
- Explain how to use Managed Instance Groups with Load Balancers.
Topics covered
- →Load Balancing in Azure and Google Cloud
- →Cloud Load Balancing features in Google Cloud
- →Managed instance groups
Activities
Lab: Configuring an HTTP Load Balancer with Autoscaling
Objectives
- Explore storage options and use cases.
- Explore the features of Cloud SQL and Cloud Spanner.
- Learn about using Cloud Bigtable.
Topics covered
- →Overview of Storage and Database Services
- →Cloud Storage
- →Managed Database Services
- →Data Lake Options
Activities
Lab: Cloud Storage
Lab: Implementing Cloud SQL
Objectives
- Explain how containers can be utilized in Google Cloud.
- Provision a Kubernetes cluster using GKE.
- Explain how Deployments are used in Kubernetes.
- Identify the purpose of hybrid and multi-cloud computing with GKE Enterprise.
Topics covered
- →Containers in Google Cloud
- →Google Kubernetes Engine
- →Kubernetes Concepts and Architecture
- →Deployments and Networking
- →Hybrid and Multi-Cloud Computing with GKE Enterprise
Activities
Lab: Getting started with Google Kubernetes Engine
Lab: Creating Google Kubernetes Engine Deployments
Objectives
- Describe how Cloud Run Functions can support application development.
- Deploy a containerized application on Cloud Run.
Topics covered
- →Development of Applications in Google Cloud
- →Cloud Run Functions
- →Cloud Run
Activities
Lab: Hello Cloud Run
Objectives
- Describe Google Cloud's operations suite.
- Create charts, alerts, and uptime checks for resources with Cloud Monitoring.
- Describe system metrics collection in GKE.
Topics covered
- →Monitoring in the Cloud
- →Cloud Operations
- →Monitoring GKE Clusters
- →Monitoring Tools in Azure and Google Cloud
Activities
Lab: Monitoring a Compute Engine VM using Ops Agent
Quality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
Teaching Methods Used
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
- Guided Labs — Guided practical exercises on software, hardware, or technical environments.
- Quiz / MCQ — Quick knowledge check (paper-based or digital via tools like Kahoot/Klaxoon).
Evaluation and Monitoring System
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Train multiple employees
- Volume discounts (multiple seats)
- Private or custom session
- On-site or remote