Monolith migration war story

On slides, the move from monolith to microservices looks clean: smaller codebases, independent teams, infinite scale. In reality, migrations are messy. Here are some hard-earned lessons from real projects where we broke apart monoliths into dozens of services.

Communication is the first wall you hit

In a monolith, function calls are just in-process. Once you break things apart, every call becomes a network hop. Latency, retries, and partial failures suddenly matter. We thought a simple REST contract between services would be enough — it wasn’t. We ended up adopting gRPC for performance and schema contracts, and later layered in a service mesh (Istio) for retries and circuit breaking. The mesh solved problems, but it also added complexity: debugging a request path across Envoy sidecars at 3 a.m. is no fun.

Data is where the pain lives

Splitting databases was harder than splitting code. Our monolith had a single Postgres schema. Every service wanted its own database for autonomy, but cross-service transactions don’t exist anymore. We had to implement sagas and idempotent retries for distributed writes. The first time an order event failed halfway through a multi-service flow, we learned the hard way why idempotency is non-negotiable. If I could redo it, I’d start with event sourcing or at least a message bus (Kafka) from day one.

Deployments multiply

With a monolith, one build pipeline → one deployment. With microservices, every service gets its own CI/CD, infra config, dashboards, and alerts. We underestimated the operational overhead. “Ten services isn’t so bad,” we thought. By the time we had forty, keeping pipelines consistent was a full-time job. A platform team and a standardized template repo saved us. Without them, the sprawl would have sunk us.

The trade-off

Migrating to microservices gave us real benefits: teams shipped independently, scaling bottlenecks were isolated, and failures were better contained. But we also traded in a simple deployment model for distributed systems complexity. Monitoring, tracing, and automated testing went from “nice to have” to “survival tools.”

If you’re starting your own migration:

• Introduce a message bus early — it decouples services and smooths failures.
• Invest in observability before you need it. Distributed tracing saved us.
• Don’t split everything at once. Strangle the monolith piece by piece.
• Expect productivity to dip before it rises.

Moving from a monolith to microservices isn’t a silver bullet. It’s a trade: you swap scaling limits for operational complexity. If you make the trade intentionally and with the right tooling, you’ll survive the war stories and come out stronger.