Case Study: Microservice Migration Challenges and Lessons Learned

The company, serving over 20,000 customers, originally used a single API to collect and clean client data.

After a microservice refactor the system grew to 400 private repositories and 70 distinct services, bringing advantages like better visibility, lower configuration and build costs, reduced coupling, and suitability for small‑team collaboration.

Monitoring each microworker with tools such as sysdig, htop, iftop and Datadog made problem isolation easy, allowing memory‑leak bugs to be narrowed down to 50‑100 lines of code.

Microservices are defined as a set of small, single‑purpose network services that improve modularity, testing, and team autonomy compared with monolithic architectures.

Two years post‑migration the team faced “explosive” complexity: slower delivery, higher failure rates, and increased operational burden.

The processing pipeline ingests tens of thousands of events per second, routes them to over a hundred destination types, and distinguishes retryable (e.g., HTTP 500, rate‑limit) from non‑retryable errors, which caused queue‑head blocking when a destination slowed down.

To mitigate blocking, a dedicated router process was added, creating isolated queues per destination so that only the affected destination’s queue stalls while others continue processing.

New challenges emerged: shared‑library version proliferation across 50+ destinations, management overhead for over 140 services, diverse load patterns requiring manual scaling, and scaling‑tuning becoming more art than science.

When the complexity became untenable, the team attempted to revert to a monolith, introducing a “Centrifuge” component to merge destinations, but this added another layer of difficulty.

Additional sacrifices included harder fault isolation (a single bug could crash all services), reduced in‑memory cache efficiency due to dispersed processes, and the risk that updating a single dependency could break many destinations.

The overall conclusion is that while microservices solved performance and isolation issues, they also introduced significant new complexity, requiring careful trade‑offs and continuous architectural evaluation.

Common architectural pitfalls highlighted are blindly chasing patterns, following trends without assessing real needs, trying to address every concern simultaneously, and neglecting long‑term architectural decay.