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10. Phases of a Successful Migration

2024-09-01

Every migration to AWS goes through a set of distinct phases. But most failures happen not from skipping phases — but from not treating them seriously enough.

Here is a real-world take on the eight stages you need to manage:

1. Assessment
Most systems are not what you think they are. People forget, documentation is wrong, and dependencies are hidden. Good assessments combine:
  • Monitoring: Instrument your system before interviewing anyone.

  • Multiple perspectives: Ask different roles to describe the same stack — compare their answers.

  • Dependency mapping: Databases, cron jobs, third-party APIs, hardcoded credentials, shared file systems.

  • Risks and unknowns: Surface what might break even before you plan the first step.

Don't trust anyone's memory alone. Confirm everything with logs, metrics, and oppositional interviews.

2. Planning
The goal isn’t a perfect Gantt chart. It’s alignment. Things to address here:
  • Plan around product cycles and seasonality.

  • Include developers, not just DevOps.

  • Define responsibilities clearly: who owns what?

  • Create a map of each layer (network, storage, compute) for old vs. new.

  • Include downtime windows if needed, and know your rollback points.

Most failed plans come from planning in isolation or ignoring the business calendar.

3. Mobilization

This is the setup phase — and often rushed. But your tools, roles, and visibility need to be ready before migrating anything.

Checklist:
  • CI/CD ready for cloud environment

  • IAM roles and permissions created

  • Logging, metrics, and dashboards prepared

  • Load testing tools + scenarios built and validated

  • Plan for test execution (not just writing tests)

  • Whitelist IPs, register staging environments with external systems

  • Warm up email and traffic infrastructure if needed

Also, prepare team communication protocols. Who does what during testing, rollout, rollback?

4. Execution
Now comes the move. Risks and surprises include:
  • Application behavior changes with more resources

  • Graceful shutdown and autoscaling create issues in legacy apps

  • Liveness/readiness probes introduce new failure modes

  • Network throughput behaves differently

This phase isn’t just technical. It’s psychological. If teams see instability, they may resist. Have fast triage paths and confident observability to reduce fear.

5. Stabilization

Just because it’s live doesn’t mean it’s done.

Key tasks:
  • Monitor scaling behavior and resolve edge cases

  • Add any missing metrics, dashboards, or logs

  • Enable support and BI to respond to new alert patterns

  • Watch adoption: Are people routing around the new infra?

If the team doesn’t adopt it, they will start undermining it. Monitor people, not just servers.

6. Optimization

AWS won’t save you money unless you make it.

Post-migration optimization means:
  • Right-sizing instances

  • Moving background workloads to spot instances

  • Replacing temporary migration hacks

  • Tuning queues, caches, and storage performance

This is where you transform AWS from "expensive hosting" into "scalable platform."

7. Training & Handoff

No migration is finished until the team is working confidently in the new world.

Training must include:
  • Developers and DevOps

  • Support and incident responders

  • QA and test engineers

  • BI, analysts, and data consumers

  • Product managers and delivery leads

  • External or contract contributors

Change won’t stick if people keep falling back to what they know. Make training real, and tear down the old scripts and systems.

8. Ongoing Operations
Success isn’t stability — it’s momentum. Ongoing ops must include:
  • Daily/weekly cost reviews early on

  • Regular alert review and tuning

  • Environment drift checks for IaC

  • Periodic architecture reviews post-migration

  • Cleanup of unused resources

  • Retrospectives with affected teams

  • 1:1 interviews for hidden pain points

This is the maturity phase. Your job now is to protect the win, extract the value, and prevent regression.

Migration doesn’t end when the system is live. It ends when the old system is gone, the new one is trusted, and the team can move faster than before.