######################
11.0.6 Cloud Providers
######################

=========================
Market Landscape Overview
=========================

**Major Cloud Providers Q4 2024:**

.. code-block:: text

   Market Share by Revenue (Latest):
   
   1 Amazon Web Services (AWS)     - 31%
   2 Microsoft Azure               - 25%  
   3 Google Cloud Platform (GCP)   - 12%
   ──────────────────────────────────────
   4 Alibaba Cloud                 - 4%
   5 IBM Cloud                     - 2%
   6 Oracle Cloud                  - 2%
   7 Salesforce                    - 2%
   8 Others                        - 22%

.. note::
   **Key Trend (2024)**: Azure is closing the gap with AWS, while GCP
   is growing fastest in AI/ML workloads. All three now offer similar
   core services but with different strengths.

.. note::
   This course provides comprehensive hands-on tutorials for the **top three cloud providers**:
   
   - **AWS** (Chapter 11_cloud_aws) - Market leader with broadest service catalog
   - **Azure** (Chapter 11_cloud_azure) - Enterprise-focused with strong hybrid capabilities  
   - **GCP** (Chapter 11_cloud_gcp) - Innovation leader in data analytics, ML, and Kubernetes
   
   Each chapter includes practical examples of deploying your containerized applications.

========================
The Big Three: Deep Dive
========================

============================
1. Amazon Web Services (AWS)
============================

**The Pioneer (Launched 2006)**

.. code-block:: text

   AWS Strengths:

   + Largest service catalog (200+ services)
   + Most mature platform
   + Biggest global presence (84+ regions)
   + Largest partner ecosystem
   + Best documentation and community
   + Most third-party integrations

**Container Services:**

.. code-block:: text

   AWS Container Stack:
   ┌─────────────────────────────────────┐
   │ Amazon EKS (Managed Kubernetes)     │
   │ ├─ Fully managed control plane      │
   │ ├─ Integrates with AWS services     │
   │ └─ Supports Fargate (serverless)    │
   ├─────────────────────────────────────┤
   │ Amazon ECS (Container Service)      │
   │ ├─ AWS-native orchestration         │
   │ ├─ Simpler than Kubernetes          │
   │ └─ Good for AWS-only deployments    │
   ├─────────────────────────────────────┤
   │ Amazon ECR (Container Registry)     │
   │ ├─ Private Docker registry          │
   │ ├─ Vulnerability scanning           │
   │ └─ Integrates with CI/CD            │
   ├─────────────────────────────────────┤
   │ AWS Fargate (Serverless Containers) │
   │ ├─ No server management             │
   │ ├─ Pay per container execution      │
   │ └─ Works with EKS and ECS           │
   └─────────────────────────────────────┘

**Your GitHub Actions Integration:**

.. code-block:: yaml

   # .github/workflows/aws-deploy.yml
   name: Deploy to AWS EKS
   
   on:
     push:
       branches: [main]
   
   jobs:
     deploy:
       runs-on: ubuntu-latest
       steps:
         - uses: actions/checkout@v3
         
         - name: Configure AWS credentials
           uses: aws-actions/configure-aws-credentials@v1
           with:
             aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
             aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
             aws-region: us-west-2
         
         - name: Login to Amazon ECR
           run: |
             aws ecr get-login-password --region us-west-2 | 
             docker login --username AWS --password-stdin $ECR_REGISTRY
         
         - name: Build and push Docker image
           run: |
             docker build -t $ECR_REGISTRY/myapp:$GITHUB_SHA .
             docker push $ECR_REGISTRY/myapp:$GITHUB_SHA
         
         - name: Deploy to EKS
           run: |
             aws eks update-kubeconfig --name my-cluster --region us-west-2
             kubectl set image deployment/myapp myapp=$ECR_REGISTRY/myapp:$GITHUB_SHA
             kubectl rollout status deployment/myapp

**Best For:**

- Enterprises needing comprehensive services
- Applications requiring AWS-specific features
- Teams with AWS expertise
- Projects needing maximum flexibility

**Popular Services:**

- **EC2** (Virtual machines)
- **S3** (Object storage)
- **RDS** (Managed databases)
- **Lambda** (Serverless functions)
- **EKS** (Managed Kubernetes)

==================
2. Microsoft Azure
==================

**The Enterprise Champion**

.. code-block:: text

   Azure Strengths:

   + Best Microsoft integration (Office 365, Active Directory)
   + Strong hybrid cloud capabilities
   + Enterprise security and compliance
   + Excellent Windows support
   + Strong .NET and Microsoft stack integration
   + Competitive pricing

**Container Services:**

.. code-block:: text

   Azure Container Services (2024 Updates):
   ┌─────────────────────────────────────────┐
   │ Azure Kubernetes Service (AKS)          │
   │ ├─ Free control plane (cost advantage)  │
   │ ├─ Azure Active Directory integration   │
   │ ├─ Virtual nodes (Azure Container Inst.)│
   │ ├─ KEDA integration (event-driven scale)│
   │ └─ Confidential containers (2024)       │
   ├─────────────────────────────────────────┤
   │ Azure Container Apps (2024 Focus)       │
   │ ├─ Serverless containers platform       │
   │ ├─ Built-in Dapr integration            │
   │ ├─ Revision-based deployment            │
   │ └─ Scale-to-zero capabilities           │
   ├─────────────────────────────────────────┤
   │ Azure Container Registry (ACR)          │
   │ ├─ Geo-replication and caching          │
   │ ├─ Microsoft Defender integration       │
   │ ├─ Artifact streaming (faster pulls)    │
   │ └─ Teleport for air-gapped scenarios    │
   ├─────────────────────────────────────────┤
   │ Azure DevOps + GitHub Integration       │
   │ ├─ Native Azure integration             │
   │ ├─ Enterprise-grade security            │
   │ └─ Advanced compliance features         │
   └─────────────────────────────────────────┘

**Your GitHub Actions Integration:**

.. code-block:: yaml

   # .github/workflows/azure-deploy.yml
   name: Deploy to Azure AKS
   
   on:
     push:
       branches: [main]
   
   jobs:
     deploy:
       runs-on: ubuntu-latest
       steps:
         - uses: actions/checkout@v3
         
         - name: Login to Azure
           uses: azure/login@v1
           with:
             creds: ${{ secrets.AZURE_CREDENTIALS }}
         
         - name: Login to Azure Container Registry
           run: |
             az acr login --name ${{ env.ACR_NAME }}
         
         - name: Build and push Docker image
           run: |
             docker build -t $ACR_NAME.azurecr.io/myapp:$GITHUB_SHA .
             docker push $ACR_NAME.azurecr.io/myapp:$GITHUB_SHA
         
         - name: Deploy to AKS
           run: |
             az aks get-credentials --resource-group $RESOURCE_GROUP --name $CLUSTER_NAME
             kubectl set image deployment/myapp myapp=$ACR_NAME.azurecr.io/myapp:$GITHUB_SHA
             kubectl rollout status deployment/myapp

**Best For:**

- Microsoft-centric organizations
- Hybrid cloud deployments
- Enterprise applications with strict compliance
- .NET applications
- Organizations using Office 365

**Popular Services:**

- **Virtual Machines** (Compute)
- **Blob Storage** (Object storage)
- **Azure SQL Database** (Managed database)
- **Azure Functions** (Serverless)
- **AKS** (Managed Kubernetes)

==============================
3. Google Cloud Platform (GCP)
==============================

**The Innovation Leader**

.. code-block:: text

   GCP Strengths:

   + Best-in-class data analytics and AI/ML
   + Kubernetes originated here (Google created it)
   + Competitive pricing and sustained-use discounts
   + Excellent network performance
   + Strong open-source commitment
   + Clean, intuitive interfaces

**Key Container Services:**

- **Google Kubernetes Engine (GKE)**: Most advanced managed Kubernetes
- **Cloud Run**: Serverless containers with auto-scaling to zero  
- **Artifact Registry**: Universal package manager with vulnerability scanning
- **Cloud Build**: Native CI/CD with Git integration

**Best For:**

- Data-heavy applications
- AI/ML projects
- Kubernetes-native applications
- Startups and cost-conscious organizations
- Applications needing global performance

**Popular Services:**

- **Compute Engine** (Virtual machines)
- **Cloud Storage** (Object storage)
- **BigQuery** (Data warehouse)
- **Cloud Functions** (Serverless)
- **GKE** (Managed Kubernetes)

.. note::
   **For Detailed GCP Coverage**: See Chapter 11_cloud_gcp for comprehensive 
   hands-on tutorials including GKE, Cloud Run, compute services, databases, 
   networking, security, and cost optimization specific to Google Cloud Platform.

=======================
Side-by-Side Comparison
=======================

**Container Platform Comparison:**

.. code-block:: text

   ┌─────────────────┬─────────────┬─────────────┬─────────────┐
   │ Feature         │     AWS     │    Azure    │     GCP     │
   ├─────────────────┼─────────────┼─────────────┼─────────────┤
   │ Kubernetes      │ EKS         │ AKS         │ GKE         │
   │ Control Plane   │ $0.10/hour  │ Free        │ Free*       │
   │ Registry        │ ECR         │ ACR         │ Artifact    │
   │ Serverless      │ Fargate     │ ACI         │ Cloud Run   │
   │ CI/CD           │ CodePipeline│ DevOps      │ Cloud Build │
   │ Monitoring      │ CloudWatch  │ Monitor     │ Operations  │
   │ Auto-scaling    │ Good        │ Good        │ Best        │
   │ Multi-region    │ Excellent   │ Good        │ Excellent   │
   │ Documentation   │ Excellent   │ Good        │ Good        │
   └─────────────────┴─────────────┴─────────────┴─────────────┘
   
   * GKE Autopilot is pay-per-pod

**Pricing Comparison (Similar Workload):**

.. code-block:: text

   Small Web App (2 CPU, 4GB RAM, 3 replicas):
   
   AWS EKS:
   ├─ Control plane: $73/month
   ├─ Worker nodes: $150/month
   ├─ Load balancer: $18/month
   └─ Total: ~$241/month
   
   Azure AKS:
   ├─ Control plane: $0/month
   ├─ Worker nodes: $140/month
   ├─ Load balancer: $20/month
   └─ Total: ~$160/month
   
   GCP GKE Autopilot:
   ├─ Pay per pod: $120/month
   ├─ Load balancer: $18/month
   ├─ No node management
   └─ Total: ~$138/month

============================
Regional Strengths and Focus
============================

**Geographic Presence:**

.. code-block:: text

   Global Reach:
   
   AWS: 84 Availability Zones across 26 regions
   ├─ Strongest in: North America, Europe
   ├─ Growing in: Asia Pacific, Latin America
   └─ First mover advantage globally
   
   Azure: 60+ regions worldwide
   ├─ Strongest in: Europe, North America
   ├─ Growing in: Government/compliance markets
   └─ Excellent hybrid connectivity
   
   GCP: 35 regions and 106 zones
   ├─ Strongest in: Asia Pacific, data centers
   ├─ Growing in: Europe, enterprise
   └─ Excellent network performance

**Industry Focus:**

.. code-block:: text

   AWS:
   + Startups and unicorns (Netflix, Airbnb)
   + E-commerce and retail
   + Media and entertainment
   + Financial services
   
   Azure:
   + Enterprise and Fortune 500
   + Government and public sector
   + Healthcare and manufacturing
   + Traditional IT organizations
   
   GCP:
   + Tech companies and startups
   + Data analytics companies
   + AI/ML research organizations
   + Gaming and media companies

============================
Choosing Your Cloud Provider
============================

**Decision Framework:**

.. code-block:: text

   Start with these questions:
   
   1. "What's our primary use case?"
   ├─ General purpose → AWS
   ├─ Microsoft integration → Azure  
   ├─ Data/AI focus → GCP
   └─ Cost optimization → Compare all three
   
   2. "What's our team's experience?"
   ├─ AWS certified → AWS
   ├─ Microsoft background → Azure
   ├─ Google/open source → GCP
   └─ No preference → Start with free tiers
   
   3. "What's our compliance needs?"
   ├─ Government → Azure or AWS GovCloud
   ├─ Healthcare → All three (check specific certs)
   ├─ Financial → AWS or Azure
   └─ General → Any provider
   
   4. "What's our budget?"
   ├─ Startup → GCP (best discounts)
   ├─ Enterprise → Azure (volume discounts)
   ├─ Variable workload → AWS (most options)
   └─ Predictable → Compare reserved instances

**Multi-Cloud Strategy:**

.. code-block:: text

   Smart Multi-Cloud Approach:
   
   Primary Cloud (70% of workloads):
   ├─ Choose based on team expertise
   ├─ Focus on this for deep knowledge
   └─ Get volume discounts
   
   Secondary Cloud (20% of workloads):
   ├─ For specific use cases
   ├─ Disaster recovery
   └─ Avoid vendor lock-in
   
   Third Cloud (10% of workloads):
   ├─ Experimental workloads
   ├─ Special requirements
   └─ Future options

===========================
Getting Started: Free Tiers
===========================

**All Three Offer Free Tiers:**

.. code-block:: text

   AWS Free Tier:
   ├─ 12 months free for new accounts
   ├─ 750 hours/month of t2.micro EC2
   ├─ 5GB S3 storage
   ├─ Some services always free
   └─ Credit card required
   
   Azure Free Tier:
   ├─ 12 months free for new accounts
   ├─ $200 credit for first 30 days
   ├─ B1S virtual machine (750 hours)
   ├─ Some services always free
   └─ Credit card required
   
   GCP Free Tier:
   ├─ $300 credit for new accounts (90 days)
   ├─ Always free tier (limited usage)
   ├─ f1-micro instance (1 per region)
   ├─ 5GB Cloud Storage
   └─ Credit card required for verification

**Recommendation for Learning:**

.. code-block:: bash

   # Try all three with the same application!
   
   # 1. Start with GCP (most generous credits)
   gcloud container clusters create learning-cluster
   kubectl apply -f your-app.yaml
   
   # 2. Try Azure (free control plane)
   az aks create --name learning-cluster
   kubectl apply -f your-app.yaml
   
   # 3. Test AWS (largest ecosystem)
   eksctl create cluster --name learning-cluster
   kubectl apply -f your-app.yaml
   
   # Compare experiences and costs!

==============================
2024 Cloud Provider Comparison
==============================

**Head-to-Head Comparison for DevOps Teams:**

.. code-block:: text

   Container Services Maturity (2024):
   
   ┌─────────────────┬──────────┬───────────┬─────────────┐
   │ Feature         │    AWS   │   Azure   │     GCP     │
   ├─────────────────┼──────────┼───────────┼─────────────┤
   │ Kubernetes      │ EKS (★★★)│ AKS (★★★★)│ GKE (★★★★★) │
   │ Serverless      │ Lambda   │ Functions │ Cloud Run   │
   │ Container Reg.  │ ECR      │ ACR       │ Artifact R. │
   │ Cost-Effective  │ ★★★      │ ★★★★      │ ★★★         │
   │ Enterprise      │ ★★★★★    │ ★★★★★     │ ★★★         │
   │ Innovation      │ ★★★★     │ ★★★       │ ★★★★★       │
   └─────────────────┴──────────┴───────────┴─────────────┘

**Choosing Your Cloud in 2024:**

.. code-block:: text

   Choose AWS if:
   ├─ You need the largest service ecosystem
   ├─ You're building complex, multi-service architectures
   ├─ You have AWS expertise on the team
   ├─ You need maximum flexibility and control
   └─ You're okay with higher complexity/cost

   Choose Azure if:
   ├─ You use Microsoft technologies (.NET, Office 365)
   ├─ You need strong hybrid cloud capabilities
   ├─ You want enterprise-grade security by default
   ├─ You prefer integrated development tools (Azure DevOps)
   └─ You want competitive pricing with good features

   Choose GCP if:
   ├─ You're building AI/ML-heavy applications
   ├─ You need the best Kubernetes experience
   ├─ You prioritize developer experience and simplicity
   ├─ You're working with big data and analytics
   └─ You want cutting-edge cloud-native services

**Multi-Cloud Reality Check:**

.. code-block:: text

   2024 Enterprise Trends:
   
   84% of enterprises use multiple clouds
   ├─ Average: 2.6 different cloud providers
   ├─ Primary reasons: Avoid vendor lock-in, best-of-breed
   ├─ Challenges: Complexity, skills, networking costs
   └─ Tools helping: Kubernetes, Terraform, service mesh

.. note::

   **Your Container Skills Work Everywhere!**
   
   The same Docker images and Kubernetes YAML files work on all three clouds:
   
   - Same `kubectl` commands
   - Same container concepts
   - Portable CI/CD pipelines
   - Cloud-agnostic monitoring tools

   **Pro Tip**: Start with one cloud, master the fundamentals, then expand to 
   multi-cloud as your needs grow. Don't optimize for "what-if" scenarios early on.
   - Same monitoring approaches
   - Same CI/CD patterns
   
   Focus on learning cloud-specific services (networking, storage, databases) rather than relearning containers!