AWS Builder Center

Builder Center

Multi-Cloud Strategy with AWS + Microsoft Azure

Multi-Cloud Strategy with AWS + Microsoft Azure

Explore how to build a secure and governed multi-cloud operating model across AWS and Microsoft Azure. This guide covers workload placement, identity, networking, Kubernetes, Terraform, CI/CD, GitOps, security, observability, FinOps, disaster recovery, and practical AWS + Azure DevOps architecture.

Building a Secure, Governed Cloud Operating Model

Introduction

Multi-cloud is often misunderstood.
It does not mean deploying the same application on AWS and Azure simply because both clouds are available.
A good multi-cloud strategy starts with a business or technical reason, defines which workloads belong on which provider, standardizes the controls that must be consistent, and allows each cloud to use its native strengths where that creates value.
A practical AWS + Azure model is:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
ENTERPRISE
|
v
+------------------------+
| Multi-Cloud Governance |
| Security / FinOps / IAM|
+-----------+------------+
|
+--------------+--------------+
| |
v v
+-------------+ +-------------+
| AWS | | Azure |
| | | |
| VPC | | VNet |
| EKS | | AKS |
| EC2 | | VMSS |
| RDS | | Azure SQL |
| S3 | | Blob |
| CloudWatch | | Azure |
| IAM | | Monitor |
+------+------+ +------+------+
| |
+-------------+---------------+
|
v
Shared DevOps Model
Terraform / Git / CI/CD / Policy
The goal is not to make AWS and Azure identical.
The goal is to make the operating model consistent while allowing the infrastructure to remain cloud-native.

1. What Is Multi-Cloud?

Multi-cloud means using two or more cloud service providers for significant workloads.
For this article:
1
Multi-Cloud = AWS + Microsoft Azure
Common drivers include:
  • Existing enterprise investments
  • Microsoft ecosystem integration
  • AWS-native capabilities
  • Data sovereignty
  • Business-unit requirements
  • Specialized services
  • Acquisitions
  • Resilience requirements
  • Customer requirements
  • Geographic requirements
  • Strategic workload placement
The important point is that the reason should be explicit.

2. Multi-Cloud vs Hybrid Cloud

Single Cloud

1
2
3
4
Company
|
v
 AWS

Hybrid Cloud

1
2
3
4
5
Company
|
+---- On-Premises
|
+---- AWS

Multi-Cloud

1
2
3
4
5
Company
|
+---- AWS
|
+---- Azure

Hybrid Multi-Cloud

1
2
3
4
5
6
Company
|
+------------+------------+
| | |
v v v
On-Premises AWS Azure

3. Why AWS + Azure?

A multi-cloud strategy should solve a real problem.
DriverExample
Existing investmentCompany already operates on both clouds
Microsoft ecosystemEntra ID, Microsoft 365, Windows
AWS ecosystemEKS, S3, RDS, Lambda
Data sovereigntyDifferent regulatory requirements
Specialized capabilityProvider-specific services
AcquisitionAcquired company already uses another CSP
Business autonomyDifferent teams have different requirements
ResilienceSelected workloads need independent capacity
Contractual requirementsCustomer requires a specific CSP
The strategy should be driven by business value, not simply “avoid vendor lock-in.”

4. The Biggest Multi-Cloud Mistake

One of the biggest mistakes is:
1
"Let's use AWS and Azure everywhere."
This creates unnecessary complexity.
A better approach:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Business Requirement
|
v
Workload Analysis
|
v
Provider Selection
|
v
Architecture
|
v
Security + Governance
|
v
Deployment + Operations

5. Primary Cloud + Secondary Cloud

A strong enterprise model can define:
1
2
3
4
5
6
7
8
9
10
11
12
13
Primary Cloud
|
+--> Default landing zone
+--> Default platform
+--> Core governance
+--> Main engineering skills

Secondary Cloud
|
+--> Specific workloads
+--> Business requirements
+--> Specialized capabilities
+--> Regulatory / contractual needs
This is often easier to operate than pretending every workload must be equally distributed.

6. Workload Placement Strategy

Create a decision framework before deploying.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Workload
|
v
Business requirements
|
+------------+------------+
| |
v v
AWS better? Azure better?
| |
+------------+------------+
|
v
Security / Cost
|
v
Final Placement
Evaluate:
  • Performance
  • Security
  • Compliance
  • Cost
  • Data gravity
  • Latency
  • Availability
  • Existing skills
  • Service maturity
  • Operational complexity
  • Exit requirements

7. AWS vs Azure Service Mapping

CapabilityAWSAzure
Virtual networkVPCVNet
Virtual machinesEC2Azure VM
KubernetesEKSAKS
Object storageS3Blob Storage
Managed relational DBRDS / AuroraAzure SQL / Azure Database services
IdentityIAMEntra ID / Azure RBAC
MonitoringCloudWatchAzure Monitor
SecretsSecrets ManagerKey Vault
Container registryECRACR
ServerlessLambdaAzure Functions
Load balancingALB / NLBApplication Gateway / Load Balancer
IaCCloudFormation / CDK / TerraformARM/Bicep / Terraform
The objective is not to make the clouds identical.
Instead, define the capability and select the native implementation.

8. Multi-Cloud Architecture Principles

Principle 1 — Standardize Controls

Security, identity, tagging, logging, policy, CI/CD and incident management should be consistent.

Principle 2 — Keep Workloads Cloud-Native

Do not remove useful managed services just to make two clouds look identical.

Principle 3 — Avoid Unnecessary Cross-Cloud Dependencies

A workload should not constantly move data between AWS and Azure without a strong reason.

Principle 4 — Automate Everything

Use Infrastructure as Code, GitOps and policy automation.

Principle 5 — Make Placement Explicit

Every production workload should have an owner and documented placement rationale.

9. Landing Zones

AWS

1
2
3
4
5
6
7
8
AWS Organization
|
+-- Security Account
+-- Log Archive
+-- Network
+-- Shared Services
+-- Development
+-- Production

Azure

1
2
3
4
5
6
7
8
9
10
11
12
Microsoft Entra ID
|
+-- Management Groups
|
+-- Platform
| +-- Identity
| +-- Connectivity
| +-- Management
|
+-- Landing Zones
+-- Development
+-- Production
The exact account/subscription structure depends on the organization, but the operating model should be deliberate.

10. Identity Strategy

Identity is one of the most important cross-cloud concerns.
A practical architecture can use Microsoft Entra ID as an enterprise identity layer while integrating authentication and authorization into AWS according to organizational requirements.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
Enterprise Identity
|
v
 Microsoft Entra ID
|
+-----------+-----------+
| |
v v
 AWS Azure
| |
IAM / Roles Azure RBAC
| |
v v
AWS Resources Azure Resources
Important concepts:
  • SSO
  • Federation
  • MFA
  • Conditional access
  • RBAC
  • Short-lived credentials
  • Least privilege
  • Privileged access management
Avoid permanent administrator credentials for automation.

11. AWS IAM vs Azure RBAC

Think in terms of capabilities rather than identical syntax.
1
2
3
4
5
6
7
8
9
10
11
AWS
IAM User / Role
Policies
STS
Resource Policies

Azure
Entra Identity
Service Principal / Managed Identity
Azure RBAC
Resource Policies
For automation, prefer short-lived or workload identities where supported.

12. Network Architecture

A common mistake is treating networking as an afterthought.
Define:
  • Address space
  • DNS
  • Routing
  • Egress
  • Ingress
  • Private connectivity
  • Firewalling
  • Inspection
  • Cross-cloud connectivity
  • Observability
Example:
1
2
3
4
5
6
7
8
9
10
Corporate Network
|
+----------+----------+
| |
v v
 AWS Network Azure Network
| |
VPC / TGW VNet / Hub
| |
Workloads Workloads

13. AWS + Azure Connectivity

For workloads that genuinely need private communication across providers, establish deliberate connectivity.
Possible options include:
  • Dedicated connectivity providers
  • Site-to-site VPN
  • Cloud interconnect services
  • Partner networking
  • AWS Interconnect – multicloud
AWS announced Azure connectivity for AWS Interconnect – multicloud in public preview in August 2026.
The design still needs careful routing, DNS, security, availability and cost planning.

14. DNS Strategy

Cross-cloud DNS becomes important when applications communicate across providers.
1
2
3
4
5
6
7
8
9
Enterprise DNS
|
+--------------+--------------+
| |
v v
 AWS DNS Azure DNS
| |
v v
 AWS Apps Azure Apps
Define:
  • Internal domains
  • Public domains
  • Split-horizon DNS
  • Service discovery
  • Private endpoints
  • DNS forwarding
  • Disaster recovery records

15. Kubernetes Multi-Cloud

Kubernetes can provide a common application platform across clouds.
1
2
3
4
5
6
7
8
9
10
11
12
Git Repository
|
v
 CI/CD Pipeline
|
+---------+---------+
| |
v v
 AWS EKS Azure AKS
| |
v v
 Application Application
But Kubernetes does not magically remove multi-cloud complexity.
You still need to manage:
  • Networking
  • Storage
  • IAM integration
  • Ingress
  • DNS
  • Load balancing
  • Cluster upgrades
  • Observability
  • Cost
  • Cloud-specific controllers

16. Terraform for AWS + Azure

Terraform is useful when an organization wants one declarative workflow across providers.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
terraform/
├── modules/
│ ├── aws-vpc/
│ ├── aws-eks/
│ ├── azure-vnet/
│ ├── azure-aks/
│ └── monitoring/
│
├── environments/
│ ├── dev/
│ ├── qa/
│ └── prod/
│
└── providers.tf
Example:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
terraform {
required_providers {
aws = {
source = "hashicorp/aws"
}

azurerm = {
source = "hashicorp/azurerm"
}
}
}

provider "aws" {
region = var.aws_region
}

provider "azurerm" {
features {}
}
Use separate modules and state boundaries where appropriate instead of creating one giant Terraform configuration.

17. Terraform State Strategy

Define:
  • Remote state storage
  • State locking
  • Access controls
  • Encryption
  • Backup
  • State ownership
  • Environment boundaries
  • Recovery procedures
Avoid one massive state file for every cloud and application.
A better model:
1
2
3
4
5
6
7
AWS Network State
AWS EKS State
AWS Data State

Azure Network State
Azure AKS State
Azure Data State
with carefully managed dependencies.

18. CI/CD Strategy

Use a common software delivery model.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
Developer
|
v
Git Repository
|
v
CI Pipeline
|
+--> Test
+--> Security Scan
+--> Build
+--> Image Scan
|
v
Artifact Registry
|
+-------------------+
| |
v v
AWS Deployment Azure Deployment
| |
v v
EKS / ECS / EC2 AKS / VM / Functions
The pipeline can remain consistent while deployment targets differ.

19. Container Strategy

1
2
3
4
5
6
7
8
9
10
11
Application Source
|
v
Docker Build
|
v
Container Image
|
+------> Amazon ECR
|
+------> Azure Container Registry
Define whether:
  • Images are replicated
  • Each cloud has its own registry
  • One registry is the source of truth
  • Image signing is required
  • Vulnerability scanning is mandatory
  • SBOMs are generated

20. GitOps Strategy

1
2
3
4
5
6
7
8
9
Git
|
+--------+--------+
| |
v v
 AWS GitOps Azure GitOps
| |
v v
 EKS AKS
Application configuration remains version controlled.
Cloud-specific infrastructure remains cloud-specific.

21. Security Architecture

Multi-cloud security should use common control objectives.
1
2
3
4
5
6
7
8
9
10
Security Baseline
|
+-------------------+-------------------+
| | |
v v v
Identity Network Data
| | |
v v v
AWS IAM AWS VPC KMS / S3
Azure RBAC Azure VNet Key Vault
Common controls:
  • MFA
  • Least privilege
  • Encryption
  • Centralized logging
  • Vulnerability management
  • Secrets management
  • Network segmentation
  • Policy as code
  • Incident response

22. Secrets Management

Do not manually copy secrets between cloud environments.
1
2
3
4
5
AWS
Secrets Manager / Parameter Store

Azure
Key Vault
Application identities should retrieve secrets at runtime where practical.
Never commit:
1
2
3
4
5
AWS_ACCESS_KEY_ID
AWS_SECRET_ACCESS_KEY
AZURE_CLIENT_SECRET
DATABASE_PASSWORD
API_KEY
to Git repositories.

23. Encryption Strategy

1
2
3
4
5
6
7
8
9
10
11
Enterprise Crypto Policy
|
+--------------+--------------+
| |
v v
AWS Azure
| |
KMS Key Vault
| |
v v
AWS Data Stores Azure Data Stores
Define:
  • Key ownership
  • Rotation
  • Access policy
  • Separation of duties
  • Backup/recovery
  • Audit requirements

24. Observability

A multi-cloud organization needs a unified operational view.
1
2
3
4
5
6
7
8
9
10
11
AWS Metrics / Logs Azure Metrics / Logs
| |
+----------------+------------------+
|
v
Observability Layer
|
+--------------+--------------+
| | |
v v v
Metrics Logs Traces
Potential tooling:
  • CloudWatch
  • Azure Monitor
  • OpenTelemetry
  • Prometheus
  • Grafana
  • SIEM
  • Incident management
The goal is not necessarily one dashboard.
The goal is consistent telemetry standards.

25. FinOps Across AWS + Azure

Define common dimensions:
1
2
3
4
5
6
7
Owner
Application
Environment
Business Unit
Cost Center
Project
Data Classification
Example:
1
2
3
4
5
Environment = production
Owner = platform-team
Application = recruitment-platform
CostCenter = CC-102
ManagedBy = terraform
Compare:
MetricAWSAzure
Compute$X$Y
Storage$X$Y
Network$X$Y
Managed DB$X$Y
Kubernetes$X$Y
Total$X$Y
Do not optimize only for infrastructure price. Include engineering and operational cost.

26. Disaster Recovery

Multi-cloud does not automatically equal disaster recovery.
Ask:
  • What failure are we protecting against?
  • What is the RTO?
  • What is the RPO?
  • Where is the data?
  • How is data replicated?
  • Can DNS fail over?
  • Can credentials work during a failure?
  • Can the team actually operate the secondary environment?
For many applications, multi-region within one cloud can be simpler than active-active across two clouds.

27. Data Gravity

Data is often harder to move than compute.
1
2
3
4
5
6
7
8
9
10
11
AWS Application
|
v
AWS Database
|
X
Massive cross-cloud data transfer
X
|
v
Azure Application
Cross-cloud data movement can introduce:
  • Latency
  • Egress cost
  • Synchronization complexity
  • Consistency challenges
  • Security complexity
  • Operational risk
Therefore:
Place compute close to the data whenever practical.

28. Avoid Cross-Cloud Chaining

Consider:
1
2
3
4
5
6
7
8
9
10
AWS API
|
v
Azure Service
|
v
AWS Database
|
v
Azure Analytics
Every cross-cloud hop increases operational complexity.
A better architecture is often:
1
2
3
AWS Workload ---> AWS Data

Azure Workload ---> Azure Data
Then integrate at deliberate boundaries such as APIs, events, or data products.

29. Policy as Code

Examples:
1
2
3
4
5
6
7
No public storage buckets
No unrestricted security groups
No unencrypted production databases
Mandatory owner tag
Mandatory environment tag
Approved regions only
No public Kubernetes API
Use cloud-native policy engines and tools such as OPA/Conftest or Terraform policy frameworks according to organizational standards.

30. Cloud Center of Excellence

A mature multi-cloud organization benefits from a CCoE.
1
2
3
4
5
6
7
8
9
10
11
12
13
CCoE
|
+--------------+--------------+
| | |
v v v
Architecture Security FinOps
| | |
+--------------+--------------+
|
v
Cloud Teams
/ \
AWS Azure
A CCoE can define:
  • Reference architectures
  • Security guardrails
  • Landing-zone standards
  • Naming conventions
  • Tagging
  • Identity patterns
  • Observability standards
  • DR patterns
  • Cost controls
  • Training

31. Skills Strategy

Do not expect every engineer to become an expert in every cloud service.
1
2
3
4
5
6
7
8
9
10
11
12
13
Platform Team
|
+--> AWS specialists
|
+--> Azure specialists
|
+--> Network specialists
|
+--> Security specialists
|
+--> DevOps / SRE
|
+--> Cloud architecture
Engineers should understand cross-cloud architecture while maintaining deep expertise in their primary platform.

32. Practical Project: AWS + Azure Multi-Cloud DevOps Platform

Build a portfolio project using:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
AWS
- VPC
- EKS
- ECR
- RDS MySQL
- ALB
- CloudWatch
- IAM

Azure
- VNet
- AKS
- ACR
- Azure Database service
- Application Gateway / Load Balancer
- Azure Monitor
- Entra ID

Shared
- Terraform
- GitHub Actions
- Docker
- Kubernetes
- OpenTelemetry
- GitOps

33. Project Architecture

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
Developer
|
v
 GitHub
|
v
 GitHub Actions
|
+-------------+-------------+
| |
v v
 AWS Pipeline Azure Pipeline
| |
v v
 ECR ACR
| |
v v
 EKS AKS
| |
v v
 AWS Services Azure Services
| |
+-------------+-------------+
|
v
Unified Observability

34. GitHub Actions + OIDC

A strong automation pattern is:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
GitHub Actions
|
v
OIDC Identity Token
|
+----------+----------+
| |
v v
AWS IAM Role Azure Federated Identity
| |
v v
Terraform Terraform
| |
v v
AWS Resources Azure Resources
This reduces the need for long-lived cloud credentials in CI/CD.

35. Multi-Cloud Security Reference

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Identity
|
+--------------+--------------+
| |
v v
AWS Azure
| |
+-----+-----+ +-----+-----+
| | | | | |
IAM KMS Guardrails RBAC KeyVault Policy
| | | | | |
+-----+-----+ +-----+-----+
| |
+--------------+--------------+
|
v
SIEM / SOC / Audit

36. Common Multi-Cloud Mistakes

Mistake 1 — Using Two Clouds Just for Resume Value

Multi-cloud adds real complexity.

Mistake 2 — Copying Everything to Both Clouds

This increases cost without automatically increasing resilience.

Mistake 3 — No Workload Placement Rules

Teams choose clouds independently and create uncontrolled sprawl.

Mistake 4 — Ignoring Data Egress

Large cross-cloud transfers can become expensive and slow.

Mistake 5 — Different Security Standards

AWS and Azure should not have completely different enterprise security baselines.

Mistake 6 — Static Credentials Everywhere

Use federation and workload identity where practical.

Mistake 7 — One Giant Terraform State

Separate state boundaries by environment, platform and dependency.

Mistake 8 — Treating Kubernetes as a Magic Abstraction

EKS and AKS still have cloud-specific networking, identity, storage and operations.

Mistake 9 — No Exit Strategy

Know how data, applications and identities would move if requirements changed.

37. Production Checklist

Strategy

  • Document why multiple clouds are required
  • Define primary and secondary providers
  • Define workload placement criteria
  • Define exit requirements

Governance

  • Establish CCoE or equivalent governance
  • Standardize naming
  • Standardize tagging
  • Define ownership
  • Define account/subscription strategy

Identity

  • Central identity strategy
  • MFA
  • Least privilege
  • Short-lived credentials
  • Workload identity

Networking

  • Address planning
  • DNS strategy
  • Private connectivity
  • Routing controls
  • Egress controls

Security

  • Encryption
  • Secrets management
  • Vulnerability scanning
  • Central logging
  • Security monitoring
  • Incident response

DevOps

  • Terraform
  • CI/CD
  • GitOps
  • Container registry strategy
  • OIDC
  • Policy as code

Operations

  • Metrics
  • Logs
  • Traces
  • Alerting
  • Runbooks
  • DR testing

FinOps

  • Cost allocation
  • Tags
  • Budgets
  • Rightsizing
  • Egress analysis
  • Unit economics

38. DevOps Career Perspective

For a DevOps or Cloud Engineer, multi-cloud teaches you to separate cloud concepts from cloud implementations.
1
2
3
4
5
6
7
8
9
Concept AWS Azure
-------------------------------------------------
Virtual Network VPC VNet
Kubernetes EKS AKS
Object Storage S3 Blob
Identity IAM Entra/RBAC
Secrets Secrets Manager Key Vault
Monitoring CloudWatch Azure Monitor
Container Registry ECR ACR
The real skill is not memorizing the table.
The real skill is understanding:
1
2
3
4
5
6
7
8
9
10
Networking
Identity
Security
Compute
Containers
Storage
Databases
Observability
Automation
Governance
and implementing those concepts correctly on each provider.

39. Final Architecture Mindset

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
BUSINESS
|
v
 Cloud Strategy
|
+--------------+--------------+
| |
v v
 AWS Strategy Azure Strategy
| |
v v
 Landing Zone Landing Zone
| |
v v
 Security + IAM Security + IAM
| |
v v
 EKS / Apps AKS / Apps
| |
+--------------+--------------+
|
v
Shared Operating Model
|
 +-------------------+-------------------+
| | |
v v v
 DevOps Security FinOps
| | |
+-------------------+-------------------+
|
v
Business Outcomes

40. Key Takeaway

Multi-cloud is not about having two cloud consoles. It is about building a cloud operating model that can deliberately use more than one provider without losing security, governance, reliability, or engineering velocity.
AWS and Azure can coexist successfully when:
  • Workload placement is intentional
  • Identity is centralized and controlled
  • Networking is designed before deployment
  • Security policies are consistent
  • Terraform and CI/CD automate delivery
  • Kubernetes is used where it adds value
  • Data stays close to the compute that needs it
  • Observability spans the environment
  • FinOps measures total cost
  • A CCoE or platform team establishes standards
  • Multi-cloud is used only where its benefits justify its complexity
The strongest architecture is not:
1
AWS + Azure = Better
It is:
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Business Requirement
+
Right Workload Placement
+
Common Governance
+
Cloud-Native Engineering
+
Automation
+
Security
+
Observability
=
Sustainable Multi-Cloud

Final Thought

Cloud is not the destination. The operating model is the advantage.
AWS and Azure give organizations different capabilities. The job of a modern DevOps, SRE, Cloud, or Platform Engineering team is to decide where each workload belongs, automate the path to production, and make the entire environment secure and observable.
That is the real meaning of a multi-cloud strategy.
# multi-cloud# azure# aws-builders# devops# aws-community-builders
Any opinions in this article are those of the individual author and may not reflect the opinions of AWS.
Enjoyed reading this content? Let the author know!

Your likes, comments, shares, and saves help creators reach more builders.

Loading recommendations

Loading article