1. Inventory Your Workloads First
Before touching a single server, document every application, database, and service in your environment. Understand their dependencies, data volumes, and traffic patterns. Migrations fail when teams discover unknown dependencies mid-project.
Action: Run a discovery tool (AWS Migration Evaluator, Azure Migrate) against your environment before making any decisions.
2. Classify by Migration Strategy (the 6 R's)
Not everything should be migrated the same way. Evaluate each workload against the 6 R's: Rehost (lift-and-shift), Replatform, Repurchase, Refactor, Retire, or Retain. Moving a legacy monolith to the cloud without refactoring often just moves the problem.
Action: Classify each application before estimating timelines or costs. Lift-and-shift takes weeks; refactoring can take months.
3. Model Your Cloud Costs Realistically
Cloud costs are dramatically different from on-premise costs. Most organizations underestimate egress charges, storage IOPS costs, and the cost of running dev/test environments 24/7. Get your cost model wrong and you'll blow your budget in month two.
Action: Use AWS Pricing Calculator or Azure Cost Management to model costs before migration. Include data transfer costs explicitly.
4. Plan for Security and Compliance From Day One
Shared responsibility models mean your security obligations don't disappear when you move to the cloud — they change. HIPAA, SOC 2, PCI DSS workloads require specific cloud configurations that take time to implement correctly.
Action: Map your compliance requirements to cloud-native controls before migration begins. Don't bolt security on after go-live.
5. Define Rollback Procedures
Every migration has a cutover moment. If something goes wrong during cutover and you don't have a tested rollback plan, you'll be making decisions under pressure with production down. This is where migrations become disasters.
Action: Write and test your rollback procedures before you cut over. Know exactly what triggers a rollback and who authorizes it.