Organizations planning to migrate workloads from Amazon Web Services (AWS) to Microsoft Azure face a significant undertaking that requires careful planning, stakeholder alignment, and strategic execution. Based on practical experience and established migration patterns, this guide outlines the complete migration lifecycle and the critical decisions cloud architects must navigate at each stage.
The core migration principle: Like-for-like architecture
The foundation of a successful migration is maintaining a like-for-like architecture during the transition. This means replicating your existing AWS architecture on Azure with equivalent services, preserving the same operational patterns, performance characteristics, and the same known issues that exist today.
This approach may seem counterintuitive. Why migrate if you're not modernizing? The answer lies in risk management. If you attempt to modernize during migration, you introduce potential scope creep, increase complexity, and erode confidence in the workload. Once the workload is stable on Azure and meeting the same KPIs it achieved on AWS, you can pursue optimization and technical debt reduction from a position of stability.
The five-phase migration lifecycle
Successful AWS-to-Azure migrations follow a structured five-phase approach, with each phase building on the previous one:
Phase 1: Plan
The planning phase is where migrations succeed or fail. Incomplete discovery or unclear migration objectives risk misaligned expectations and missed dependencies.
Automated discovery tools provide a starting point, but they cannot capture everything. Subject matter experts throughout your workload team must be engaged to identify critical components that tools often miss—scheduled scripts, undocumented integrations, legacy configurations, and authentication dependencies.
Essential planning deliverables include:
- Complete workload architecture documentation with all dependencies mapped
- Authentication and authorization configuration details
- Performance baselines covering throughput, latency, and error rates
- Current monitoring and alerting configurations
- Rollback trigger criteria, not just rollback procedures
Service mapping decisions during this phase determine the Azure services that will replace each AWS component. For example, AWS RDS may map to Azure SQL Database or Azure Database for PostgreSQL, while AWS Lambda functions typically map to Azure Functions.
Migration strategy selection is critical. The recommended approach for most workloads is blue/green deployment, where both AWS (blue) and Azure (green) environments run in parallel. While this incurs costs for both cloud providers during the transition, the reduction in risk and operational burden typically justifies the expense.
| Migration Strategy | Downtime | Risk Level | Rollback Capability |
|---|---|---|---|
| Big Bang | High | High | Difficult |
| Phased | Low | Medium | Moderate |
| Blue/Green | Low | Low | Easy |
Phase 2: Prepare
The preparation phase is where readiness becomes tangible. Any misconfigured infrastructure, insufficient testing, or lack of team readiness can result in delays, security vulnerabilities, or failed deployments during execution.
Critical preparation activities:
Infrastructure deployment should use Infrastructure as Code (IaC) to ensure consistency and repeatability. Whether using Bicep, Terraform, or ARM templates, codified infrastructure reduces human error and provides a reliable deployment mechanism.
CI/CD pipeline updates must target Azure while maintaining the ability to deploy to both AWS and Azure during the transition period. This dual-deployment capability is essential for blue/green execution.
Code refactoring involves replacing AWS-specific libraries and SDKs with Azure equivalents or platform-agnostic alternatives. This includes updating AWS SDK calls, replacing CloudWatch logging with Application Insights, and adjusting any AWS-specific service integrations.
Testing with Azure Chaos Studio helps simulate potential faults such as VM failures, network outages, or service disruptions. This proactive testing identifies weaknesses before they impact production.
Operations team preparation requires implementing Azure Monitor and Application Insights with dashboards and alerts equivalent to the AWS CloudWatch setup. Operations engineers must be comfortable with Azure's monitoring tools before cutover.
Phase 3: Execute
The execution phase carries the highest risk of service disruption. Data synchronization issues, network misconfigurations, or unexpected application behaviors can cause outages or data loss.
Your detailed migration runbook becomes the operational guide during this phase. It should define step-by-step procedures, validation checkpoints, and clear rollback criteria.
During cutover execution:
- Maintain a real-time health dashboard using Azure Monitor or custom telemetry, actively monitored by the migration team and operations engineers
- Keep rollback readiness by maintaining the AWS environment in its pre-migration state throughout your validation window
- Ensure stakeholder communication about cutover progress, any timeline impacts, and validation results
Post-cutover verification is not optional. Before declaring success, run regression tests, monitor costs and usage patterns, and ensure all monitoring signals are healthy. Only after thorough validation should you consider the migration complete.
Phase 4: Evaluate
Migration completion and validation completion are not the same thing.
Comprehensive validation includes:
Baseline comparison against the performance metrics documented during planning—throughput, latency, error rates, and resource utilization. The migrated workload should meet or exceed AWS performance.
Cutover validation via AWS CloudTrail logs ensures no unintended workload traffic continues hitting AWS services. This verification confirms the migration is truly complete.
Data cutover confirmation involves stopping continuous replication once Azure holds the authoritative copy of all data. Until this point, data consistency between environments must be maintained.
Operational validation includes performing key management operations such as certificate rotation, backup procedures, and incident response to confirm the operations team has sufficient control.
Formal sign-off should only occur after meeting all predefined success criteria established during the planning phase.
Post-mortem sessions capture lessons learned, discuss what worked well and what could improve, and share findings with other teams planning migrations. These insights become organizational knowledge.
Phase 5: Decommission
The decommissioning phase is often overlooked, yet premature deletion of AWS resources, overlooked dependencies, or insufficient final checks risk data loss, unexpected downtime, or ongoing costs from orphaned assets.
Essential decommissioning steps:
Final backups and snapshots should be taken for archival purposes before any resource deletion.
AWS Config inventory helps ensure no workload-related resources remain active and accruing costs. Orphaned resources—unused volumes, snapshots, or networking components—are common oversights.
Establish a new performance baseline for the Azure-hosted workload, reflecting its steady-state behavior. This baseline will guide future capacity planning and optimization.
Azure Well-Architected Framework Review provides a structured assessment across reliability, security, performance efficiency, cost optimization, and operational excellence. This baseline identifies opportunities for future improvements.
Retire AWS monitoring by removing CloudWatch alarms, dashboards, and logging configurations once you've confirmed all critical monitoring has shifted to Azure.
Who should perform the migration?
A principle often violated in practice: the workload team currently responsible for the workload in AWS and who will ultimately own it in Azure should perform the migration.
Outsourcing the entire migration to external resources can lead to:
- Surprise discoveries late in the process when the workload team finally engages
- An under-trained workload team inheriting a system they don't understand
- A loss of ownership and accountability
The recommended model: External partners with Azure expertise, such as System Integrators or Microsoft's Industry Solutions Delivery team, can lead planning and preparation activities, develop runbooks, and build automation. However, the workload team should execute the production cutover using these partner-developed assets. This approach transfers knowledge while leveraging specialized expertise.
Setting realistic expectations
Migrations require work, coordination, and cooperation across teams. Late-hour verification sessions and unexpected challenges are part of the process.
Success requires:
- A concrete, well-documented plan with clear objectives
- Relevant stakeholders aligned and committed
- A solid target architecture based on like-for-like principles
- The right migration strategy for each workload component
- A phased approach with clear validation checkpoints
Leverage available expertise. Whenever possible, engage colleagues or Microsoft experts who have successfully migrated AWS workloads to Azure. Their experience helps navigate challenges and adopt proven practices.
Final thoughts
Migrating from AWS to Azure is a strategic initiative requiring careful planning and stakeholder alignment. Without proper preparation, you risk introducing disruption that erodes confidence in your workload.
When executed properly, using a like-for-like architecture, blue/green deployment, comprehensive testing, and operational readiness, migrations can be completed confidently with mechanisms in place to handle issues as they arise.
After successful migration and decommissioning, take time to celebrate the achievement. Then begin the optimization journey.
Further reading
Read the full series and share it with cloud architects, IT leaders, and DevOps teams in your network who are planning or executing migrations:
https://learn.microsoft.com/en-us/azure/migration/migrate-workload-from-aws-introduction
Share your experiences in the comments. What migration strategies have worked in your environment? What challenges did you encounter during planning, execution, or validation? Your insights help others navigate similar journeys.
Ask questions. If specific aspects of the migration process are unclear or you'd like deeper exploration of particular topics, let me know. The best content comes from addressing real practitioner needs.
For cloud architects currently planning AWS-to-Azure migrations: What migration strategies have worked best in your environment? What challenges did you encounter during planning, execution, or validation? Your experiences can help others navigate similar journeys.
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