☁️ Cloud Services (AWS & GCP)

Master cloud computing fundamentals and services on Amazon Web Services and Google Cloud Platform

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Cloud Services (AWS & GCP) Curriculum

12
Cloud Units
~110
Cloud Services
30+
Architecture Patterns
50+
Hands-on Labs
1

Cloud Computing Fundamentals

Understand core cloud computing concepts, service models, and deployment strategies.

  • Cloud computing models
  • IaaS, PaaS, SaaS
  • Public vs private cloud
  • Cloud benefits and challenges
  • Shared responsibility model
  • Cloud economics
  • Migration strategies
  • Provider comparison
2

AWS Core Services

Master essential AWS services including compute, storage, and networking.

  • EC2 instances
  • S3 storage
  • VPC networking
  • IAM security
  • RDS databases
  • Lambda functions
  • CloudFormation
  • CLI and SDKs
3

GCP Core Services

Learn Google Cloud Platform's fundamental services and unique capabilities.

  • Compute Engine
  • Cloud Storage
  • VPC networks
  • Cloud Identity
  • Cloud SQL
  • Cloud Functions
  • Deployment Manager
  • gcloud CLI
4

Serverless Computing

Build scalable applications using serverless architectures and functions.

  • Serverless concepts
  • AWS Lambda
  • Google Cloud Functions
  • Event-driven architecture
  • API Gateway
  • Step Functions
  • Cloud Workflows
  • Best practices
5

Container Services

Deploy and manage containerized applications using cloud-native solutions.

  • Container fundamentals
  • Amazon ECS
  • Amazon EKS
  • Google Kubernetes Engine
  • Cloud Run
  • Container registries
  • Service mesh
  • Monitoring containers
6

Data Services

Leverage cloud data services for storage, processing, and analytics.

  • Relational databases
  • NoSQL databases
  • Data warehouses
  • Big data processing
  • ETL services
  • Real-time analytics
  • Data lakes
  • Data governance
7

AI and Machine Learning

Utilize cloud AI/ML services for building intelligent applications.

  • AWS AI services
  • Google AI Platform
  • Pre-trained models
  • Custom model training
  • MLOps pipelines
  • AutoML
  • Model deployment
  • Edge inference
8

Security and Identity

Implement robust security and identity management in cloud environments.

  • Identity and access management
  • Multi-factor authentication
  • Encryption at rest
  • Encryption in transit
  • Network security
  • Compliance frameworks
  • Security monitoring
  • Incident response
9

Monitoring and Operations

Monitor, log, and operate cloud applications effectively.

  • CloudWatch monitoring
  • Stackdriver operations
  • Log aggregation
  • Distributed tracing
  • Alerting strategies
  • Performance optimization
  • Cost monitoring
  • Automation tools
10

DevOps and CI/CD

Implement DevOps practices and continuous integration/deployment pipelines.

  • Infrastructure as Code
  • AWS CodePipeline
  • Google Cloud Build
  • Git integration
  • Automated testing
  • Blue-green deployments
  • Configuration management
  • Release strategies
11

Cost Optimization

Optimize cloud costs through proper resource management and billing strategies.

  • Cost analysis tools
  • Resource tagging
  • Reserved instances
  • Spot instances
  • Auto-scaling
  • Right-sizing
  • Budget controls
  • FinOps practices
12

Multi-Cloud and Migration

Plan and execute cloud migrations and multi-cloud strategies.

  • Migration assessment
  • Migration strategies
  • Multi-cloud architectures
  • Hybrid cloud
  • Data migration
  • Application modernization
  • Vendor management
  • Best practices

Unit 1: Cloud Computing Fundamentals

Understand core cloud computing concepts, service models, and deployment strategies.

Cloud Computing Models

Learn the fundamental service models that define how cloud resources are delivered and consumed.

IaaS PaaS SaaS
Cloud computing is delivered through three primary service models: Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Each model provides different levels of control and management responsibility.
# Cloud Service Models
cloud_service_models = {
  "iaas": {
    "description": "Infrastructure as a Service",
    "provides": ["Virtual machines", "Storage", "Networks", "Load balancers"],
    "customer_manages": ["OS", "Runtime", "Applications", "Data"],
    "provider_manages": ["Physical infrastructure", "Virtualization", "Networking"],
    "examples": {
      "aws": "EC2, VPC, EBS",
      "gcp": "Compute Engine, VPC, Persistent Disks"
    },
    "use_cases": ["Custom applications", "Legacy migrations", "Development environments"]
  },
  "paas": {
    "description": "Platform as a Service",
    "provides": ["Development platform", "Runtime environment", "Database", "Web server"],
    "customer_manages": ["Applications", "Data", "Configuration"],
    "provider_manages": ["OS", "Runtime", "Infrastructure"],
    "examples": {
      "aws": "Elastic Beanstalk, Lambda",
      "gcp": "App Engine, Cloud Functions"
    },
    "use_cases": ["Web applications", "API development", "Microservices"]
  },
  "saas": {
    "description": "Software as a Service",
    "provides": ["Complete applications", "User interface", "Data storage"],
    "customer_manages": ["User data", "Access controls", "Configuration"],
    "provider_manages": ["Everything else"],
    "examples": ["Gmail", "Office 365", "Salesforce", "Slack"],
    "use_cases": ["Email", "CRM", "Collaboration", "Analytics"]
  }
}

Public vs Private Cloud

Understand different cloud deployment models and their appropriate use cases.

Cloud Deployment Models:
• Public Cloud: Multi-tenant, shared infrastructure, cost-effective
• Private Cloud: Dedicated infrastructure, enhanced security and control
• Hybrid Cloud: Combination of public and private clouds
• Community Cloud: Shared among organizations with common requirements
• Multi-Cloud: Using multiple cloud providers simultaneously
Deployment Decision Factors:
Choose deployment models based on security requirements, compliance needs, cost constraints, performance requirements, and existing infrastructure investments.
# Cloud Deployment Models
deployment_models = {
  "public_cloud": {
    "characteristics": ["Shared infrastructure", "Internet accessible", "Pay-per-use"],
    "advantages": ["Lower costs", "Scalability", "No maintenance", "Global reach"],
    "disadvantages": ["Less control", "Security concerns", "Compliance limitations"],
    "best_for": ["Startups", "Variable workloads", "Development/testing", "Web applications"]
  },
  "private_cloud": {
    "characteristics": ["Dedicated infrastructure", "Enhanced security", "Full control"],
    "advantages": ["Security", "Compliance", "Customization", "Performance"],
    "disadvantages": ["Higher costs", "Maintenance overhead", "Limited scalability"],
    "best_for": ["Regulated industries", "Sensitive data", "Consistent workloads"]
  },
  "hybrid_cloud": {
    "characteristics": ["Combines public and private", "Data/workload portability"],
    "advantages": ["Flexibility", "Cost optimization", "Compliance", "Scalability"],
    "challenges": ["Complexity", "Integration", "Management", "Security"],
    "use_cases": ["Burst to cloud", "Data sensitivity", "Regulatory compliance"]
  }
}

Shared Responsibility Model

Understand the division of security and operational responsibilities between cloud providers and customers.

Provider Responsibilities:
• Physical security of data centers
• Infrastructure and network controls
• Host operating system patching
• Hypervisor security
• Service availability and durability
Customer Responsibilities:
• Data classification and protection
• Identity and access management
• Application-level controls
• Operating system updates
• Network traffic