Best Practices for Integrating AWS and Azure Environments
Integrating AWS and Azure into a cohesive multicloud environment
Marin Frankovic
Amazon Employee
Published Jun 11, 2025
Integrating AWS and Azure into a cohesive multicloud environment unlocks flexibility, resilience, and cost efficiency—but requires careful planning. Below are technical best practices, supported by real-world examples, to ensure seamless interoperability, security, and performance.
Connecting AWS and Azure networks is foundational. Key strategies include:
- Use Azure ExpressRoute and AWS Direct Connect to establish dedicated, low-latency connections (reducing latency by up to 42% compared to public internet routes).
- For hybrid setups, deploy VPN tunnels between AWS Virtual Private Cloud (VPC) and Azure Virtual Network (VNet) using IPsec/IKEv2 protocols.
Example:
A financial services firm combined ExpressRoute and Direct Connect to sync transactional data between AWS S3 and Azure Blob Storage, achieving 1.2 Gbps throughput with sub-10ms latency.
A financial services firm combined ExpressRoute and Direct Connect to sync transactional data between AWS S3 and Azure Blob Storage, achieving 1.2 Gbps throughput with sub-10ms latency.
Additional reading: https://www.megaport.com/blog/3-ways-to-connect-aws-and-azure/
Unified identity management prevents security gaps:
- Integrate Azure Active Directory (AAD) with AWS IAM using SAML 2.0 for single sign-on (SSO).
- Apply role-based access control (RBAC) consistently. For instance, map AWS IAM roles to Azure AD groups to enforce least-privilege policies.
Example:
A healthcare provider used AAD to manage access to both AWS EC2 instances and Azure VMs, reducing unauthorized access incidents by 35%.
A healthcare provider used AAD to manage access to both AWS EC2 instances and Azure VMs, reducing unauthorized access incidents by 35%.
Additional reading: https://docs.aws.amazon.com/vsts/latest/userguide/security-iam.html
Leverage each cloud’s strengths while maintaining flexibility:
- Containers: Deploy Kubernetes clusters (e.g., AWS EKS, Azure AKS) with Helm charts for consistent orchestration. Use Azure Container Registry (ACR) and AWS Elastic Container Registry (ECR) for cross-cloud image storage.
- Serverless: Route event-driven workloads using AWS Lambda for high-throughput tasks and Azure Functions for .NET-centric processes.
Example:
An e-commerce platform runs AI/ML inference on AWS SageMaker and real-time analytics on Azure Synapse, reducing processing costs by 22%.
An e-commerce platform runs AI/ML inference on AWS SageMaker and real-time analytics on Azure Synapse, reducing processing costs by 22%.
Ensure consistency across clouds using IaC tools:
- AWS CloudFormation and Azure Bicep for resource provisioning.
- Terraform for multicloud orchestration (e.g., deploying AWS RDS and Azure SQL DB with identical configurations).
Template Snippet (Terraform):
Additional reading: https://docs.aws.amazon.com/prescriptive-guidance/latest/choose-iac-tool/introduction.html
Centralize visibility to troubleshoot performance bottlenecks:
- Use Azure Monitor and AWS CloudWatch with third-party tools like Datadog for unified dashboards.
- Enable distributed tracing for microservices spanning both clouds (e.g., AWS X-Ray + Azure Application Insights).
Example:
A media company reduced mean time to resolution (MTTR) by 50% by correlating logs from AWS CloudTrail and Azure Monitor.
A media company reduced mean time to resolution (MTTR) by 50% by correlating logs from AWS CloudTrail and Azure Monitor.
Additional reading: https://aws.amazon.com/blogs/mt/observe-your-azure-and-aws-workloads-simultaneously-with-amazon-cloudwatch/
- Encryption: Use AES-256 for data storage (AWS KMS, Azure Key Vault) and TLS 1.3 for cross-cloud API calls.
- Firewalls: Deploy AWS Network Firewall and Azure Firewall to segment traffic between production and development environments.
Example:
A UK-based SMB achieved GDPR compliance by encrypting sensitive customer data in AWS S3 and Azure SQL DB, with keys managed in Azure Key Vault.
A UK-based SMB achieved GDPR compliance by encrypting sensitive customer data in AWS S3 and Azure SQL DB, with keys managed in Azure Key Vault.
Simplify operations with platform-agnostic tools:
| Tool | Use Case | AWS Integration | Azure Integration |
|---|---|---|---|
| Kubernetes | Container orchestration | EKS | AKS |
| Ansible | Configuration management | EC2, Lambda | VMs, Functions |
| Jenkins | CI/CD pipelines | CodePipeline | DevOps Pipelines |
Additional reading: https://aws.amazon.com/blogs/mt/use-aws-systems-manager-for-multi-cloud-operations-management-part-1/
- Cost Savings: A retail chain reduced cloud spend by 30% by migrating batch processing to Azure Spot VMs and real-time analytics to AWS Graviton instances.
- Resilience: An enterprise achieved 99.99% uptime by load-balancing traffic between AWS and Azure during regional outages.
- Compliance: A financial institution met Basel III requirements by replicating audit logs across AWS CloudTrail and Azure Log Analytics.
Integrating AWS and Azure demands a strategic blend of networking, security, automation, and workload optimization. By adopting these best practices—supported by tools like Terraform, Kubernetes, and ExpressRoute/Direct Connect—organizations can build a future-proof multicloud environment that balances innovation with operational efficiency.
Any opinions in this post are those of the individual author and may not reflect the opinions of AWS.