Multi-Cloud Architect

Design and manage solutions across AWS, Azure, and Google Cloud with confidence. Build multi-cloud expertise to optimize performance, cost, and flexibility for modern enterprises

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Course Outline

Multi-Cloud Architect Prerequisites

Basic knowledge of cloud computing concepts
Familiarity with at least one major cloud platform (AWS, Azure, or GCP)
Understanding of networking and virtualization fundamentals
Prior experience with IT infrastructure or DevOps is helpful (but not mandatory)

Amazon Web Services

Chapter 1 : Amazon VPC

Overview and introduction to Amazon VPC
Core advantages and main capabilities
Key components: VPCs, subnets, subnet sizing, and security layers
Using VPC endpoints for private connectivity
Understanding and configuring VPC peering

Chapter 2 : Elastic Compute Cloud (EC2)

Introduction to EC2 and its core use cases
Major benefits and technical features
Types of EC2 instances and their workloads
Working with Amazon Machine Images (AMI)
Understanding Amazon Elastic Block Store (EBS)
Overview of EC2 pricing models and cost optimization

Chapter 4 : Amazon Simple Storage Service (S3)

Overview of Amazon S3
Core concepts and architecture
Storage features, durability, and data management

Chapter 5 : Amazon RDS

Introduction to Amazon RDS
Database engines, capabilities, and key features
Overview of Amazon Aurora and its performance benefits

Micosoft Azure

Chapter 2 : Azure Virtual Machine

Planning and sizing virtual machines
Deploying and managing Azure VMs
Ensuring availability and redundancy
Working with VM extensions for automation and management

Chapter 3 : Azure Loadbalancer

Introduction to Azure Load Balancer
Public and Internal Load Balancer types
Load Balancer SKUs and configurations
Managing backend pools and load balancing rules
Session persistence and health probe configurations

Chapter 4 : Azure Blob Storage

Understanding Blob Storage and containers
Blob access tiers and lifecycle management
Uploading and managing blob data
Pricing and cost considerations

Google Cloud Platform

Chapter 1 : Google Virtual Private Cloud

Introduction to Google Cloud VPC
Global architecture and scalability
Sharable and expandable VPC concepts
Key features and use cases
Understanding VPC pricing models

Chapter 2 : Google Compute Engine

Overview of Compute Engine
Key performance and scalability features
High-performance, cost-efficient virtual machines
Networking efficiency and global infrastructure
Sustainability and environmental design
Flexibility for various workloads

Chapter 3 : Google Loadbalancer

Introduction to Google Cloud Load Balancing
Types, features, and benefits

Chapter 4 : Google Cloud Storage

Introduction to Cloud Storage
Choosing the right storage class
Main features and advantages
Understanding total cost and optimization strategies

Chapter 5 : Google Cloud Database

Overview of Google Cloud database solutions
Core benefits and use cases
Cloud SQL and managed relational databases
Cloud Bigtable for large-scale NoSQL storage
Cloud Spanner for global transactional databases
Cloud Memorystore for in-memory caching
Cloud Firestore and Firebase Realtime Database for app data

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Our Multi-Cloud instructor is skilled in AWS, Azure, and GCP, with expertise in designing and managing hybrid cloud strategies. They help learners gain the flexibility to work across multiple platforms with real-world best practices