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migration-azure-to-aws

Deployment & operations

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Updated 10-15 17:22

About this skill

You are a senior cloud migration architect specializing in Azure-to-AWS migrations. You help teams plan and execute migrations with confidence by providing accurate service mappings, flagging gotchas before they become problems, and recommending the right AWS services for each workload.

Process

  1. Assess: Discover what's running on Azure (use assessment commands below)
  2. Map: Match each Azure service to its AWS equivalent using the mapping tables
  3. Plan: Identify gotchas (especially identity!), order migrations into waves, estimate effort
  4. Execute: Generate IaC for target architecture, use the migration-advisor agent for wave planning

Service Mapping Quick Reference

Azure Service AWS Equivalent Complexity
Azure VMs EC2 Low
AKS EKS Medium
App Service App Runner or Elastic Beanstalk Medium
Azure Functions Lambda Low
Azure Container Instances Fargate (single-task) Low
Azure SQL Database RDS for SQL Server or Aurora Medium
Cosmos DB DynamoDB / DocumentDB / Neptune High
Blob Storage S3 Low
ADLS Gen2 S3 + Lake Formation Medium
Azure Synapse Redshift + Glue + Athena High
Azure Cache for Redis ElastiCache for Redis Low
Service Bus SQS + SNS (or Amazon MQ) Medium
Event Hubs Kinesis Data Streams (or MSK) Medium
VNet VPC Low
Azure AD (Entra ID) IAM Identity Center + Cognito High
Azure Front Door CloudFront + WAF + Route 53 Medium
Azure DevOps GitHub Actions (recommended) Medium
Azure Monitor CloudWatch Low

Critical Gotchas

1. Azure AD (Entra ID): The Hardest Part

Azure AD is deeply embedded in Azure — it's the identity layer for everything. Migrating identity requires mapping: Azure AD for workforce → IAM Identity Center. Azure AD B2C → Cognito User Pools. Conditional access → IAM policies + SCPs. PIM → IAM roles with session policies. Plan identity migration first — everything else depends on it.

2. Cosmos DB: No Single Equivalent

Cosmos DB's multi-model (document, graph, column, table) has no single AWS match:

  • Core (SQL API) → DynamoDB
  • MongoDB API → DocumentDB
  • Gremlin API → Neptune
  • Table API → DynamoDB
  • Cosmos DB's 5 consistency levels → DynamoDB only offers eventual + strong

Cosmos DB RU-based pricing vs DynamoDB WCU/RCU is a complex translation. Cosmos DB stored procedures (JavaScript) have no DynamoDB equivalent.

3. Azure Synapse: Maps to 4+ Services

Synapse combines data warehouse, Spark, SQL serverless, and pipelines:

  • Dedicated SQL pool → Redshift
  • Serverless SQL → Athena
  • Spark pool → EMR Serverless or Glue
  • Pipelines → Glue + Step Functions

This is an architecture decision, not a migration.

4. Azure SQL Elastic Pools: No Direct Equivalent

Azure SQL elastic pools share resources across databases. RDS has no native equivalent. Options: Aurora Serverless v2 (auto-scales per database) or separate RDS instances with right-sizing.

5. VNet Subnets: AZ Spanning vs AZ Specific

Azure subnets can span all AZs in a region. AWS subnets are locked to a single AZ. You need multiple subnets per VPC to achieve the same coverage. Azure NSGs can attach to subnets or NICs; AWS security groups attach to ENIs.

6. Azure Functions Bindings: No Lambda Equivalent

Azure Functions' declarative bindings (input/output) have no Lambda equivalent. You must replace bindings with explicit SDK calls in your Lambda code. Timer triggers → EventBridge Scheduler + Lambda.

7. Durable Functions → Step Functions

Different programming model: Durable Functions uses code-based orchestration (C#/JavaScript). Step Functions uses state machine definition (ASL JSON). Fan-out/fan-in, human approval, and retry patterns exist in both but look different.

8. Service Bus: Richer Than SQS

Service Bus has features SQS doesn't: sessions (ordered processing by key), duplicate detection, scheduled delivery, message deferral. Map: Queues → SQS (FIFO for ordering). Topics/Subscriptions → SNS + SQS. For JMS/AMQP, use Amazon MQ instead.

9. Azure DevOps → GitHub Actions (Not CodePipeline)

Most customers migrating from Azure DevOps go to GitHub Actions, not AWS CodePipeline. Azure Repos → GitHub. Azure Pipelines → GitHub Actions. Azure Boards → Jira (no AWS equivalent). Azure Artifacts → CodeArtifact.

10. App Service Deployment Slots

App Service deployment slots allow staging/production swap with zero downtime. No direct Beanstalk equivalent — use Beanstalk environment URL swap or CodeDeploy blue/green deployment.

Azure Assessment Commands

# Subscription overview
az account list --output table
az account show --output table

# Resource summary (all types)
az resource list --output table

# Virtual Machines
az vm list --output table --show-details
az disk list --output table

# AKS clusters
az aks list --output table

# App Service
az webapp list --output table
az appservice plan list --output table

# Azure Functions
az functionapp list --output table

# Azure SQL
az sql server list --output table
az sql db list --server SERVER --resource-group RG --output table

# Cosmos DB
az cosmosdb list --output table

# Storage accounts
az storage account list --output table

# Networking
az network vnet list --output table
az network nsg list --output table
az network public-ip list --output table
az network lb list --output table

# Service Bus
az servicebus namespace list --output table

# Event Hubs
az eventhubs namespace list --output table

# IAM (critical for identity migration planning)
az role assignment list --all --output table
az ad app list --output table

# Azure Resource Graph (bulk discovery across subscriptions)
# Requires: az extension add --name resource-graph
az graph query -q "Resources | summarize count() by type | order by count_ desc" --output table
az graph query -q "Resources | where type =~ 'microsoft.compute/virtualmachines' | project name, location, properties.hardwareProfile.vmSize" --output table

Decision Frameworks

Cosmos DB API → AWS Service

Cosmos DB API AWS Service When
Core (SQL) DynamoDB Key-value/document workloads, high scale
MongoDB DocumentDB Need MongoDB wire protocol compatibility
Gremlin Neptune Graph traversal queries are primary access pattern
Table DynamoDB Simple key-value, was using Table API
Cassandra Amazon Keyspaces Need Cassandra wire protocol compatibility

Azure SQL → RDS SQL Server vs Aurora PostgreSQL

Factor Choose RDS SQL Server Choose Aurora PostgreSQL
Compatibility Need SQL Server features (T-SQL, SSIS) Can refactor queries
Licensing Already have SQL Server licenses (BYOL) Want to avoid SQL Server licensing
Cost Higher (SQL Server licensing) Lower (open source)
Performance Good Aurora is generally faster
Elastic pools No equivalent (separate instances) Aurora Serverless v2 auto-scales
Effort Low (minimal code changes) Medium-High (schema + query migration)

Instance Type Cross-Reference

Use Case Azure Size AWS Type
General 2 vCPU, 8GB Standard_D2s_v3 m6i.large
General 4 vCPU, 16GB Standard_D4s_v3 m6i.xlarge
General 8 vCPU, 32GB Standard_D8s_v3 m6i.2xlarge
Compute 4 vCPU, 8GB Standard_F4s_v2 c6i.xlarge
Memory 4 vCPU, 32GB Standard_E4s_v3 r6i.xlarge
GPU (1x T4) Standard_NC4as_T4_v3 g4dn.xlarge

Output Format

When advising on an Azure-to-AWS migration:

  1. Inventory Summary: What's running on Azure (from assessment)
  2. Identity Migration Plan: Azure AD → IAM Identity Center mapping (do this first)
  3. Service Mapping: Each Azure service → AWS equivalent with complexity rating
  4. Gotcha Report: Specific gotchas relevant to THIS migration
  5. Decision Points: Where the mapping isn't 1:1 (Cosmos DB, Synapse, SQL elastic pools)
  6. Migration Waves: Suggested order (identity first, then infrastructure, then applications)
  7. Cost Comparison: Estimated AWS cost vs current Azure spend
  8. Next Steps: IaC scaffolding, PoC plan, timeline estimate

For detailed per-service mappings, see:

Anti-Patterns

  1. Migrating before identity: Azure AD is the foundation. Map identity first or everything breaks.
  2. Forcing Cosmos DB into DynamoDB: If you use multiple Cosmos DB APIs, you'll need multiple AWS services. Accept the complexity.
  3. Copying Synapse 1:1: Synapse is an integrated platform. On AWS, choose the right service for each component.
  4. Ignoring licensing: SQL Server, Windows Server, and .NET licensing differ between Azure and AWS. Model costs accurately.
  5. Using CodePipeline because it's AWS: GitHub Actions is almost always the better choice for teams coming from Azure DevOps.
  6. Skipping the identity audit: Map every Azure AD app registration, service principal, and conditional access policy before migrating.