3.4.1.4. Phased Migration and Cutover Strategies
3.4.1.4. Phased Migration and Cutover Strategies
š” First Principle: A structured, incremental approach to migration, combined with a well-planned and tested cutover strategy, is essential for minimizing business disruption and reducing the risks associated with large-scale transitions.
Scenario: A company is planning a phased migration of a critical web application to AWS. They need a cutover strategy that ensures near-zero downtime and allows for immediate rollback to the old environment if any issues are detected after switching traffic. Which cutover strategy best meets these requirements?
Migrating applications is rarely a single, "big bang" event. A phased approach is typically employed to de-risk the process.
- Phased Migration: Breaking down the migration into smaller, manageable waves.
- Practical Relevance: Reduces risk, allows teams to learn and optimize with each wave, and minimizes the blast radius of any issues. Can involve migrating non-critical apps first, then less complex critical apps, finally highly complex/critical apps.
- Cutover Strategies: The method used to switch users from the old (on-premises) environment to the new (AWS) environment.
- Big Bang Cutover: All traffic is switched at once. High risk, high downtime. Only suitable for very small, non-critical applications or planned outages.
- Rolling Cutover: Gradually move traffic to the new environment.
- Practical Relevance: Can involve updating
"DNS"records gradually, using load balancer weighting, or migrating users in batches. Reduces downtime and risk compared to big bang.
- Practical Relevance: Can involve updating
- Blue/Green Cutover: Run both environments simultaneously and switch traffic when the new environment is fully validated.
- Practical Relevance: Achieves near-zero downtime and enables instant rollback if issues arise. Ideal for critical web applications.
- Canary Cutover: Gradually shift a small percentage of traffic to the new environment, observe, and then slowly increase traffic if no issues are detected.
- Practical Relevance: Minimizes the impact of potential issues to a small user base. Ideal for microservices or frequent updates.
- Rollback Planning: Always have a clear, tested plan to revert to the old environment if the cutover fails.
Visual: Application Cutover Strategies
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ā ļø Common Pitfall: Having an inadequate or untested rollback plan. The ability to quickly and reliably revert a failed change is just as important as the deployment plan itself.
Key Trade-Offs:
- Risk vs. Complexity: A "Big Bang cutover" is simple but very risky.
"Blue/Green"and"Canary"strategies are more complex to set up but significantly reduce the risk and impact of a failed deployment.
Reflection Question: Which cutover strategy would you recommend for a phased migration of a critical web application to AWS to ensure near-zero downtime and immediate rollback capability if issues are detected after switching traffic? What are the primary benefits of this approach compared to others, and why is a tested rollback plan crucial?
