Migrating from AWS to Azure means re-mapping compute, storage, database, and networking services to their closest Azure equivalents (EC2 to Virtual Machines, S3 to Blob Storage, RDS to Azure SQL Database), then executing a phased assess-pilot-migrate-optimize process that typically runs 4-9 months for a mid-size estate. Most organizations move for enterprise licensing consolidation (Microsoft 365/EA credits), hybrid Azure Arc requirements, or a specific Azure-only capability, not because AWS is technically deficient. Budget discipline matters more than the technology gap: 38% of cloud migrations exceed their original budget, with average overruns of 23% (Medha Cloud, 2026).

Why Do Companies Migrate From AWS to Azure?

Companies rarely migrate clouds because AWS "doesn't work." They migrate because of a business or contractual lever that outweighs the switching cost. In our engagements, three drivers show up repeatedly.

Enterprise Agreement economics. Organizations already paying for Microsoft 365, Windows Server, and SQL Server licensing under an Enterprise Agreement can apply Azure Hybrid Benefit and negotiated EA discounts that make Azure compute meaningfully cheaper for Windows-heavy workloads than equivalent AWS pricing. If 60-70% of your VM fleet is Windows or SQL Server, this is usually the single biggest line item in the business case.

M&A and org-wide standardization. When a company acquires or merges with a Microsoft-shop organization, leadership often standardizes on one cloud to cut duplicate SRE/DevOps headcount, one identity plane (Entra ID vs IAM), and one billing relationship rather than run both indefinitely.

Regulatory, hybrid, or data-residency requirements. Azure Government, Azure Stack HCI, and Azure Arc give a more mature on-prem/edge story for regulated industries (defense, healthcare, financial services) that need consistent tooling across cloud and on-prem data centers.

What rarely justifies a migration on its own: marginally better raw compute pricing. Both platforms are within single-digit percentages of each other on like-for-like instance pricing before discounts; the savings case almost always comes from licensing, not infrastructure.

What Is the AWS to Azure Service Equivalence Map?

The fastest way to scope a migration is a service-by-service mapping table. Naming conventions and defaults differ even when the underlying capability is similar, and the gaps below are where most technical debt hides.

The two items that consistently blow up estimated timelines: IAM/identity re-platforming (because every service permission has to be re-expressed) and the RDS-to-Azure-SQL fork (Managed Instance vs single Database changes your connection strings, HA topology, and DR runbook).

How Do You Estimate AWS to Azure Migration Costs?

Cost estimation fails when teams only price compute and storage. In practice, the line items that determine whether a migration comes in on budget are labor, data egress, dual-running period, and re-architecture work — not the destination cloud's list prices.

Benchmark ranges by workload complexity (based on current market cost guidance): lift-and-shift of a single VM-based workload runs $3,000-$8,000; a mid-complexity application with a managed database and moderate integration runs $20,000-$100,000; a full enterprise program spanning legacy systems, multiple databases, and compliance requirements runs $250,000-$2 million-plus (Medha Cloud, 2026).

Four cost drivers to model explicitly, in order of how often teams underestimate them:

1. Data egress from AWS. AWS charges for data leaving its network; moving terabytes of S3 data to Blob Storage has a real, often five- or six-figure, one-time cost that must be in the business case, not discovered mid-migration.
2. Dual-running period. Running both AWS and Azure in parallel during cutover — for validation, rollback safety, and phased cutover of dependent services — typically adds 15-30% to your total infrastructure spend for the migration window (usually 4-12 weeks per major workload group).
3. Re-architecture vs rehost. Straight rehost (VM-to-VM) is cheapest but carries forward technical debt. Refactoring to PaaS (e.g., RDS to Azure SQL Database instead of SQL on a VM) costs more upfront but reduces run-rate operational cost — model both and pick per-workload, not as a blanket policy.
4. Licensing reconciliation. Azure Hybrid Benefit can offset Windows/SQL Server licensing costs significantly if you already own qualifying licenses — this is where the real savings case usually lives, and it needs your EA/licensing team in the room during estimation, not just infrastructure engineers.

AWS holds roughly 31% of global cloud infrastructure market share versus Azure's 23-25% (Synergy Research Group, Q1 2026) — a gap worth knowing because it affects vendor leverage: AWS has more room to negotiate retention discounts when it senses a migration risk, and that counter-offer should be part of your cost comparison before you commit engineering hours to the move.

What Is a Realistic Phased Migration Process?

A phased approach controls risk and cost overrun better than a big-bang cutover. We run four phases, and skipping the first one is the most common cause of the 23% average budget overrun cited above.

Phase 1 — Assess and inventory (2-4 weeks). Full application and dependency mapping: every service, its Azure equivalent, data volumes, integration points, and compliance requirements. Output is the service-mapping table (see above) populated with your actual estate, plus a rehost-vs-refactor decision per workload.

Phase 2 — Pilot migration (3-6 weeks). Migrate one low-risk, well-understood workload end-to-end — ideally a stateless web app or an internal tool, not your primary revenue system. This validates your IaC tooling (Bicep/Terraform), identity mapping (IAM to Entra ID), and monitoring setup (CloudWatch to Azure Monitor) before you commit to the full estate. Treat pilot findings as inputs that should revise your Phase 1 cost estimate.

Phase 3 — Phased production migration (2-6 months, workload-group by workload-group). Migrate in dependency order — data stores and identity first, then stateless services, then stateful/critical services last — running dual environments during each group's cutover window. Every group gets its own rollback plan; do not migrate group N+1 until group N is validated in production for at least one full business cycle (e.g., a billing run, a month-end close).

Phase 4 — Optimize and decommission (ongoing, starting week 1 post-cutover). Right-size Azure resources against real usage (not AWS-sized assumptions — instance-to-VM mapping is rarely 1:1 on performance), apply Azure Hybrid Benefit and reserved instances, and decommission AWS resources only after a defined bake period (typically 30-60 days) to preserve rollback capability.

Teams that compress phases 1 and 2 to save time are the ones we most often get called in to rescue mid-migration — the cost of discovering an identity or database-tier mismatch during Phase 3 is far higher than finding it during the pilot.

FAQ

Is AWS to Azure migration more expensive than staying on AWS?

Not inherently — the migration itself has one-time costs (data egress, dual-running, re-architecture, labor), but ongoing run-rate costs can be lower on Azure if you have unused Microsoft Enterprise Agreement credits or Azure Hybrid Benefit eligibility. Model the one-time migration cost separately from the 3-year total cost of ownership; they answer different questions.

How long does an AWS to Azure migration take?

For a mid-size estate (20-100 workloads), expect 4-9 months across assessment, pilot, phased production migration, and optimization. Simple, stateless-workload-only migrations can complete in 6-8 weeks; estates with legacy databases, custom IAM policies, or compliance requirements often run 12+ months.

Can Terraform manage both AWS and Azure during migration?

Yes — Terraform's provider model supports both clouds, which is why many teams adopt or standardize on Terraform before migrating rather than rewriting CloudFormation into Bicep. This also gives you a single IaC codebase during the dual-running period, reducing configuration drift risk.

What is the biggest technical blocker in AWS to Azure migrations?

Identity and access management. IAM and Entra ID (Azure AD) use fundamentally different permission models, and every service-level permission, service-to-service role, and federated login needs to be re-expressed, not just copied — this is consistently the most underestimated line item in migration timelines.

Should we rehost or refactor when moving from RDS to Azure SQL?

It depends on the database engine and workload criticality: SQL Server workloads with heavy stored-procedure logic often fit Azure SQL Managed Instance (near-full compatibility, faster migration); greenfield or already-cloud-native apps benefit more from refactoring to Azure SQL Database (PaaS) for lower long-term operational cost. Decide per-database, not as an estate-wide policy.

Do we need a partner for AWS to Azure migration, or can our in-house team do it?

Small, stateless estates are reasonable for an experienced in-house cloud team to migrate directly. Estates with legacy databases, custom IAM structures, compliance requirements, or tight cutover windows benefit from a partner who has run the identity-migration and database-tier decisions before — those are the two areas where in-house teams most often discover scope mid-project.