Cloud Computing

Comprehensive 3-Month Cloud Computing Course Outline

Duration: 3 Months (12 Weeks)

Mode: Online / In-Person

Tools Used: Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP)

Level: Beginner to Intermediate

Prerequisites: Basic knowledge of IT infrastructure and networking (optional)

Module 1: Introduction to Cloud Computing (Weeks 1-2)

Objective:

• Provide a fundamental understanding of cloud computing and its architecture.

Topics Covered:

1. Cloud Computing Overview

   • Definition and characteristics of cloud computing

   • Key concepts: Scalability, Elasticity, and On-Demand Resources

   • Types of cloud services: IaaS, PaaS, SaaS

   • Public, Private, Hybrid, and Multi-Cloud models

2. History and Evolution of Cloud Computing

   • The rise of cloud technologies

   • Traditional IT infrastructure vs. Cloud infrastructure

3. Cloud Service Providers Overview

   • Introduction to major providers: AWS, Microsoft Azure, Google Cloud

   • Comparing features and pricing

4. Setting Up Cloud Environments

   • Creating free-tier accounts on AWS, Azure, and GCP

   • Navigating through cloud provider consoles

   • Basic setup and understanding of cloud infrastructure

Module 2: Core Cloud Services and Infrastructure (Weeks 3-4)

Objective:

• Teach students about essential cloud services like storage, computing, and networking.

Topics Covered:

1. Cloud Storage Services

   • Introduction to object storage (e.g., AWS S3, Azure Blob Storage, GCP Cloud Storage)

   • Setting up and managing storage buckets

   • Security best practices for cloud storage

   • Cloud data lifecycle management (data archiving, retention policies)

2. Cloud Compute Services

   • Virtual machines (e.g., EC2, Azure VMs, GCP Compute Engine)

   • Provisioning and managing VMs

   • Auto-scaling and load balancing

   • Pricing models: On-Demand, Reserved, Spot Instances

3. Cloud Networking

   • Introduction to Virtual Private Cloud (VPC)

   • Subnets, route tables, and internet gateways

   • Managing network security groups (firewalls)

   • Connecting VMs to the internet and configuring DNS

4. Elasticity and Scalability in the Cloud

   • Setting up auto-scaling groups

   • Horizontal vs. vertical scaling

   • Ensuring high availability with multi-region deployments

Module 3: Cloud Security and Compliance (Weeks 5-6)

Objective:

• Equip students with the knowledge to secure cloud infrastructure and ensure compliance.

Topics Covered:

1. Cloud Security Fundamentals

   • Shared Responsibility Model for cloud security

   • Identity and Access Management (IAM) best practices

   • Implementing role-based access control (RBAC)

   • Securing API keys and secrets in the cloud

2. Encryption in the Cloud

   • Data encryption at rest and in transit

   • Implementing encryption using cloud-native tools

   • Key management services (e.g., AWS KMS, Azure Key Vault)

3. Cloud Compliance and Regulations

   • Understanding GDPR, HIPAA, PCI DSS in cloud environments

   • Implementing compliance controls in cloud infrastructure

   • Auditing and logging cloud activities (AWS CloudTrail, Azure Monitor)

4. Security Tools and Best Practices

   • Using security groups, firewalls, and VPNs

   • Configuring DDoS protection

   • Implementing Intrusion Detection Systems (IDS) and Intrusion Prevention Systems (IPS)

Module 4: Cloud Automation and DevOps (Weeks 7-8)

Objective:

• Introduce students to cloud automation and DevOps practices in cloud environments.

Topics Covered:

1. Introduction to DevOps and Cloud Automation

   • Overview of DevOps in the cloud

   • Infrastructure as Code (IaC) concepts

   • Popular automation tools: Terraform, CloudFormation, Azure Resource Manager

2. Automating Cloud Infrastructure

   • Writing basic infrastructure-as-code templates (e.g., Terraform, CloudFormation)

   • Automating virtual machines and networking configuration

   • Deploying automated cloud resources across environments

3. CI/CD in the Cloud

   • Continuous Integration and Continuous Deployment concepts

   • Using CI/CD tools (Jenkins, GitLab CI, AWS CodePipeline, Azure DevOps)

   • Building a cloud-based CI/CD pipeline for applications

4. Monitoring and Managing Cloud Resources

   • Introduction to cloud monitoring tools (e.g., AWS CloudWatch, Azure Monitor)

   • Setting up alerts and performance metrics

   • Automating incident response and remediation

Module 5: Cloud Databases and Big Data (Weeks 9-10)

Objective:

• Explore cloud database services and Big Data solutions for large-scale data management.

Topics Covered:

1. Cloud Database Services

   • Relational databases in the cloud (e.g., AWS RDS, Azure SQL, GCP Cloud SQL)

   • Non-relational databases (e.g., AWS DynamoDB, Azure Cosmos DB, GCP Bigtable)

   • Configuring backup, replication, and failover for cloud databases

2. Big Data and Analytics Services

   • Introduction to Big Data concepts in the cloud

   • Cloud-based data lakes and warehouses (e.g., AWS Redshift, Google BigQuery)

   • Processing Big Data with Hadoop and Spark in the cloud

3. Data Migration to the Cloud

   • Using migration tools (AWS Database Migration Service, Azure Data Migration)

   • Best practices for cloud data migration and replication

   • Handling downtime and data consistency during migration

4. Real-Time Data Processing

   • Streaming data with AWS Kinesis, Azure Stream Analytics, GCP Dataflow

   • Architecting real-time applications in the cloud

Module 6: Cloud Solution Architecting & Final Project (Weeks 11-12)

Objective:

• Prepare students to design cloud architectures and implement solutions, culminating in a final project.

Topics Covered:

1. Cloud Architecture Best Practices

   • Designing highly available, fault-tolerant cloud architectures

   • Utilizing cloud-native services for efficient solutions

   • Multi-cloud and hybrid-cloud strategies

2. Cost Optimization in the Cloud

   • Monitoring and analyzing cloud costs

   • Using tools for cost management (e.g., AWS Cost Explorer, Azure Cost Management)

   • Best practices for reducing cloud infrastructure costs

3. Disaster Recovery and Backup Strategies

   • Planning and implementing cloud disaster recovery solutions

   • Backing up critical data and applications

   • Testing disaster recovery plans

4. Cloud Project: Build a Cloud-Based Solution

   • Choose a cloud project idea (e.g., Deploying a web app, setting up a cloud database, building a serverless architecture)

   • Design and implement the project using AWS, Azure, or GCP

   • Present the final project to the class for evaluation

Additional Resources:

• Official Documentation: Access to AWS, Azure, and GCP documentation

• Community Support: Join our cloud computing community for discussions, problem-solving, and peer reviews

• Career Support: Guidance on preparing for cloud certifications (AWS Certified Solutions Architect, Azure Fundamentals, Google Cloud Professional), building a cloud portfolio, and navigating the cloud job market

Enroll Now to Start Your Journey in Cloud Computing!

This detailed course outline offers a comprehensive roadmap for students, ensuring a structured and engaging learning experience in cloud computing over 3 months.