Multi-Cloud Architecture: AWS vs Azure vs GCP

Choosing between cloud providers—or designing for multiple clouds—requires understanding their strengths, service mappings, and pricing models. This guide compares AWS, Azure, and GCP across key dimensions to inform architectural decisions.

Service Comparison

Compute Services

Category	AWS	Azure	GCP
VMs	EC2	Virtual Machines	Compute Engine
Containers (Managed K8s)	EKS	AKS	GKE
Serverless Containers	Fargate	Container Apps	Cloud Run
Functions	Lambda	Azure Functions	Cloud Functions
PaaS	Elastic Beanstalk	App Service	App Engine

Database Services

Category	AWS	Azure	GCP
Relational (Managed)	RDS, Aurora	Azure SQL, PostgreSQL	Cloud SQL, AlloyDB
NoSQL Document	DynamoDB	Cosmos DB	Firestore
In-Memory Cache	ElastiCache	Azure Cache	Memorystore
Data Warehouse	Redshift	Synapse Analytics	BigQuery
Graph Database	Neptune	Cosmos DB (Gremlin)	-

Networking

Category	AWS	Azure	GCP
Virtual Network	VPC	VNet	VPC
Load Balancer	ALB/NLB	Load Balancer	Cloud Load Balancing
CDN	CloudFront	Azure CDN	Cloud CDN
DNS	Route 53	Azure DNS	Cloud DNS
VPN	Site-to-Site VPN	VPN Gateway	Cloud VPN
Direct Connect	Direct Connect	ExpressRoute	Cloud Interconnect

Identity & Security

Category	AWS	Azure	GCP
Identity	IAM, Cognito	Azure AD, B2C	Cloud Identity, Firebase Auth
Secrets	Secrets Manager	Key Vault	Secret Manager
Key Management	KMS	Key Vault	Cloud KMS
WAF	AWS WAF	Azure WAF	Cloud Armor

Architectural Patterns

Multi-Cloud Strategy Options

Multi-Cloud Patterns:

1. Workload Distribution
   ┌─────────┐   ┌─────────┐   ┌─────────┐
   │   AWS   │   │  Azure  │   │   GCP   │
   │ Web App │   │  ML/AI  │   │  Data   │
   └─────────┘   └─────────┘   └─────────┘

2. Active-Active (Disaster Recovery)
   ┌─────────────────────────────────────┐
   │           Global Load Balancer       │
   └──────────┬───────────────┬──────────┘
              │               │
       ┌──────▼─────┐  ┌──────▼─────┐
       │    AWS     │  │   Azure    │
       │  Primary   │  │  Secondary │
       └────────────┘  └────────────┘

3. Hybrid Cloud
   ┌────────────┐       ┌────────────┐
   │ On-Premise │◄─────►│   Cloud    │
   │   (VMware) │       │ (Any CSP)  │
   └────────────┘       └────────────┘

4. Cloud-Agnostic (Kubernetes)
   ┌─────────────────────────────────────┐
   │         Kubernetes Platform          │
   │    (Portable across EKS/AKS/GKE)    │
   └─────────────────────────────────────┘

Service Abstraction Layer

// cloud-abstraction/storage.ts
interface CloudStorage {
  upload(bucket: string, key: string, data: Buffer): Promise<string>;
  download(bucket: string, key: string): Promise<Buffer>;
  delete(bucket: string, key: string): Promise<void>;
  getSignedUrl(bucket: string, key: string, expiresIn: number): Promise<string>;
}

// AWS Implementation
class S3Storage implements CloudStorage {
  private s3: S3Client;

  constructor() {
    this.s3 = new S3Client({ region: process.env.AWS_REGION });
  }

  async upload(bucket: string, key: string, data: Buffer): Promise<string> {
    await this.s3.send(new PutObjectCommand({
      Bucket: bucket,
      Key: key,
      Body: data
    }));
    return `s3://${bucket}/${key}`;
  }

  // ... other methods
}

// Azure Implementation
class BlobStorage implements CloudStorage {
  private blobService: BlobServiceClient;

  constructor() {
    this.blobService = BlobServiceClient.fromConnectionString(
      process.env.AZURE_STORAGE_CONNECTION_STRING!
    );
  }

  async upload(bucket: string, key: string, data: Buffer): Promise<string> {
    const containerClient = this.blobService.getContainerClient(bucket);
    const blockBlobClient = containerClient.getBlockBlobClient(key);
    await blockBlobClient.upload(data, data.length);
    return blockBlobClient.url;
  }

  // ... other methods
}

// GCP Implementation
class GCSStorage implements CloudStorage {
  private storage: Storage;

  constructor() {
    this.storage = new Storage();
  }

  async upload(bucket: string, key: string, data: Buffer): Promise<string> {
    const file = this.storage.bucket(bucket).file(key);
    await file.save(data);
    return `gs://${bucket}/${key}`;
  }

  // ... other methods
}

// Factory
const getStorageProvider = (): CloudStorage => {
  switch (process.env.CLOUD_PROVIDER) {
    case 'aws': return new S3Storage();
    case 'azure': return new BlobStorage();
    case 'gcp': return new GCSStorage();
    default: throw new Error('Unknown cloud provider');
  }
};

Pricing Comparison

Compute Pricing (Approximate)

Instance Type	AWS (m6i.large)	Azure (D2s_v5)	GCP (n2-standard-2)
vCPU	2	2	2
Memory	8 GB	8 GB	8 GB
On-Demand/hour	$0.096	$0.096	$0.097
1-yr Reserved	~$0.060	~$0.060	~$0.061
3-yr Reserved	~$0.040	~$0.038	~$0.043
Spot/Preemptible	~$0.029	~$0.019	~$0.029

Serverless Pricing

Metric	AWS Lambda	Azure Functions	GCP Cloud Functions
Free tier	1M requests	1M requests	2M requests
Per 1M requests	$0.20	$0.20	$0.40
Per GB-sec	$0.0000166	$0.000016	$0.0000025
Min billing	1ms	1ms	100ms

Data Transfer

Direction	AWS	Azure	GCP
Ingress	Free	Free	Free
Egress (first 10TB)	$0.09/GB	$0.087/GB	$0.12/GB
Same region	Free	Free	Free
Cross region	$0.02/GB	$0.02/GB	$0.01/GB

Strengths by Provider

AWS Strengths

AWS Leadership Areas:
├── Market Share & Maturity
│   └── Largest ecosystem, most services
├── Enterprise Adoption
│   └── Widest enterprise feature set
├── Edge & IoT
│   └── Outposts, Wavelength, Greengrass
├── Machine Learning
│   └── SageMaker, comprehensive ML services
└── Global Infrastructure
    └── Most regions and availability zones

Azure Strengths

Azure Leadership Areas:
├── Microsoft Integration
│   └── Azure AD, Office 365, Teams
├── Enterprise/Hybrid
│   └── Azure Arc, Stack HCI
├── Windows Workloads
│   └── Native Windows support
├── Developer Tools
│   └── Visual Studio, GitHub integration
└── AI/Cognitive Services
    └── OpenAI partnership, Azure AI

GCP Strengths

GCP Leadership Areas:
├── Data & Analytics
│   └── BigQuery, Dataflow, Looker
├── Kubernetes
│   └── GKE (original K8s developers)
├── Machine Learning
│   └── TensorFlow, Vertex AI, TPUs
├── Network Performance
│   └── Premium tier networking
└── Sustainability
    └── Carbon-neutral since 2007

Decision Framework

Selection Criteria

# cloud-selection-criteria.yml
evaluation_criteria:
  technical_requirements:
    - Compute requirements (VMs, containers, serverless)
    - Data services (relational, NoSQL, analytics)
    - Networking (global, hybrid, edge)
    - Security and compliance certifications

  business_requirements:
    - Existing vendor relationships
    - Skill availability in team
    - Support and SLA requirements
    - Geographic presence requirements

  cost_considerations:
    - Workload pricing comparison
    - Committed use discounts
    - Data transfer costs
    - Hidden costs (support, training)

  strategic_factors:
    - Vendor lock-in concerns
    - Multi-cloud strategy
    - Innovation and roadmap
    - Partner ecosystem

recommendation_matrix:
  - scenario: Microsoft-centric enterprise
    recommendation: Azure
    reason: Azure AD integration, Office 365 synergy

  - scenario: Data-heavy analytics workloads
    recommendation: GCP
    reason: BigQuery superiority, data engineering tools

  - scenario: Broad service requirements
    recommendation: AWS
    reason: Widest service catalog, mature ecosystem

  - scenario: Kubernetes-native architecture
    recommendation: GCP
    reason: GKE maturity, Anthos for multi-cloud

  - scenario: AI/ML development
    recommendation: GCP or AWS
    reason: Both have strong ML platforms

Migration Patterns

Migration Approaches:

Lift and Shift
├── Fastest migration
├── Minimal changes
└── May not optimise for cloud

Replatform
├── Minor modifications
├── Use managed services
└── Better cost optimisation

Refactor
├── Significant changes
├── Cloud-native design
└── Maximum benefit

Rebuild
├── Complete rewrite
├── Modern architecture
└── Highest effort/reward

Key Takeaways

No universal winner: Each provider excels in different areas
Avoid lock-in where possible: Use containers and abstraction layers
Consider total cost: Include support, training, and hidden costs
Skills matter: Choose platforms your team can operate effectively
Hybrid is common: Most enterprises use multiple clouds
Data gravity: Consider where your data lives when choosing providers
Compliance requirements: Some industries have specific provider requirements
Start small: Pilot workloads before committing to large migrations

Multi-cloud strategies provide flexibility but add complexity. Choose providers based on specific workload requirements and organisational capabilities.