Migrating from Monolith to Microservices

A legacy monolithic application could not scale to handle growing transaction volume. Deployments were risky, scaling was all-or-nothing, and the codebase was becoming unmaintainable.

Running old and new in parallel increased infrastructure costs during migration. But it eliminated the risk of a big-bang cutover. The strangler fig pattern meant we could roll back any individual service migration without affecting others.

Used the strangler fig pattern. Extracted services one at a time. The API gateway routed traffic to either the legacy monolith or the new microservice based on endpoint. Both systems ran in parallel, reading from and writing to the same database. Once a service was stable in the new architecture, the API gateway stopped routing to the legacy endpoint.

Each microservice scales independently on AWS ECS. The GVIVE ID verification service, which had the highest traffic, was scaled first. Database connections were pooled per service to prevent connection exhaustion.

Parallel run testing: both old and new systems processed the same requests, and outputs were compared. Integration tests for each new service. Load tests before cutover. Rollback tests to verify we could revert to the monolith if needed.

Independent scaling eliminated the need to scale the entire monolith for one hot service. Database query optimization on the GVIVE service improved retrieval by 50%. CI/CD automation reduced deployment time by 40%.

The strangler fig pattern is the safest way to migrate a monolith. Running old and new in parallel catches issues before cutover. Extract the highest-value or highest-risk service first to validate the approach. Never do a big-bang migration if you can avoid it.