Zirlen Cloud Technologies

Cloud Technologies –Teaching Module Document (30 Hours)

This Cloud Technologies course provides a comprehensive overview of modern cloud platforms and services.
Learners explore key concepts such as virtualization, cloud architecture, and service models.
The course emphasizes hands-on learning with real-world cloud tools and environments.
It equips participants with the skills needed to build, deploy, and manage cloud-based solutions effectively. (Focused on AWS, Microsoft Azure, and Google Cloud Platform)

Course Structure Overview

Part I (5 Hours) – Foundations

  • Introduction to Cloud Computing
  • Cloud Computing Fundamentals
  • Cloud Storage
  • Virtual Private Network (VPN)
  • Cloud Access

 

Part II (21 Hours Total – 7 Hours per Cloud Platform)

  • Amazon Web Services (AWS)
  • Microsoft Azure
  • Google Cloud Platform (GCP)

 

Part III (4 Hours) – Case Studies

  • Real-world implementations
  • Comparative analysis across platforms

PART I – CLOUD FUNDAMENTALS (5 Hours)

  1. Introduction to Cloud Computing
  • Definition and evolution
  • Benefits: scalability, flexibility, cost-efficiency
  • Cloud vs Traditional IT infrastructure
  1. Cloud Computing Fundamentals
  • Service Models:
    • IaaS, PaaS, SaaS
  • Deployment Models:
    • Public, Private, Hybrid, Multi-cloud
  1. Cloud Storage
  • Types:
    • Object Storage
    • Block Storage
    • File Storage
  • Concepts:
    • Durability, availability, redundancy
  • Use cases and cost considerations
  1. Virtual Private Network (VPN)
  • Concept of secure communication
  • Site-to-Site VPN
  • Client VPN
  • Encryption and tunnelling
  1. Cloud Access
  • Identity and Access Management (IAM)
  • Role-based access control
  • Multi-factor authentication (MFA)

API access and CLI tools

PART II – CLOUD PLATFORMS (7 Hours Each)

  1. AMAZON WEB SERVICES (AWS)
  2. Core Services
  • Compute: EC2, Lambda
  • Storage: S3, EBS
  • Database: RDS, DynamoDB
  1. Networking
  • Virtual Private Cloud (VPC)
  • Subnets and routing
  • Internet Gateway & NAT Gateway
  1. Security
  • IAM roles and policies
  • Key Management Service (KMS)
  • Security Groups and NACL
  1. DevOps & Automation
  • CloudFormation
  • CodePipeline
  • CI/CD basics
  1. Monitoring
  • CloudWatch
  • Logging and alerts
  1. Advanced Concepts
  • Auto Scaling
  • Load Balancing
  • Serverless architecture

 

B. MICROSOFT AZURE

  1. Core Services
  • Virtual Machines
  • Azure App Services
  • Azure Storage
  1. Networking
  • Virtual Network (VNet)
  • Subnets and NSG
  • VPN Gateway
  1. Security
  • Azure Active Directory
  • Role-Based Access Control (RBAC)
  • Azure Security Center
  1. DevOps
  • Azure DevOps pipelines
  • ARM Templates
  1. Monitoring
  • Azure Monitor
  • Log Analytics
  1. Advanced Concepts
  • Azure Functions (serverless)
  • Load Balancer & Application Gateway
  • Scaling strategies

 

C. GOOGLE CLOUD PLATFORM (GCP)

  1. Core Services
  • Compute Engine
  • App Engine
  • Cloud Storage
  1. Networking
  • Virtual Private Cloud (VPC)
  • Firewall rules
  • Cloud VPN
  1. Security
  • IAM roles
  • Cloud Identity
  • Encryption
  1. DevOps
  • Cloud Build
  • Deployment Manager
  1. Monitoring
  • Cloud Monitoring
  • Cloud Logging
  1. Advanced Concepts
  • Kubernetes Engine (GKE)
  • Serverless (Cloud Functions)
  • Load balancing

PART III – CASE STUDIES (4 Hours)

  1. AWS Case Study
  • Example: E-commerce application
  • Architecture:
    • EC2 + S3 + RDS
    • Load Balancer + Auto Scaling
  • Outcome:
    • High availability
    • Cost optimization

 

  1. Azure Case Study
  • Example: Enterprise business application
  • Architecture:
    • Azure VM + SQL Database
    • Azure Active Directory integration
  • Outcome:
    • Secure identity management
    • Scalable infrastructure

 

  1. GCP Case Study
  • Example: Real-time analytics system
  • Architecture:
    • BigQuery + Cloud Storage
    • Data streaming pipeline
  • Outcome:
    • Fast data processing
    • Scalable analytics

 

  1. Comparative Analysis
Feature AWS Azure GCP
Strength Market leader Enterprise integration Data & AI
Best For Startups & scale Microsoft ecosystem Analytics workloads

Learning Outcomes

After completing this course, students will:

  • Understand cloud fundamentals and architecture
  • Work with AWS, Azure, and GCP services
  • Design secure and scalable cloud solutions
  • Implement real-world cloud-based systems

Suggested Practical Sessions

  • Deploy a web app on AWS
  • Create a VM in Azure
  • Build a storage system in GCP
  • Configure VPN and IAM policies