From Monolith to Microservices: A Migration Playbook

The monolith-to-microservices journey is one of the most common architectural transitions, and one of the most frequently botched. Having led several of these migrations, here's the playbook I follow.

First, the uncomfortable truth: most applications should stay as monoliths. Microservices solve organizational scaling problems, not technical ones. If your team is under 20 people and your monolith deploys reliably, you probably don't need microservices. The operational complexity of distributed systems is enormous, network failures, data consistency, deployment coordination, distributed tracing.

When it does make sense, start by identifying service boundaries. Domain-Driven Design provides the best framework. Look for bounded contexts, areas of your application that have their own language, their own data, and minimal interaction with other areas. User management, billing, notifications, and content management are often natural boundaries.

The strangler fig pattern is the safest migration strategy. Don't rewrite. Instead, build new features as services, and gradually move existing functionality out of the monolith. Put an API gateway in front of both the monolith and the new services. Route traffic based on the endpoint. The monolith shrinks over time as services take over its responsibilities.

Data is the hardest part. In a monolith, a single database JOIN connects users to orders to products. In microservices, each service owns its data. The user service has a user database. The order service has an order database. Cross-service queries require API calls or event-driven synchronization. This is genuinely harder and slower. Accept the tradeoff or keep those domains together.

Events are the nervous system of microservices. When a user updates their profile, the user service publishes a ProfileUpdated event. Services that care, the notification service, the search indexer, the analytics pipeline, subscribe to this event and update their own state. Google Pub/Sub or Apache Kafka provide the event backbone.

Shared libraries are necessary but dangerous. A common models library creates tight coupling between services, changing a model requires updating and deploying every consumer. Instead, each service defines its own models and uses API contracts (OpenAPI specs or protobuf definitions) to communicate. Shared utility code (logging, tracing, auth middleware) is fine.

Observability becomes non-negotiable. In a monolith, a stack trace tells you everything. In microservices, a single user request might traverse five services. Distributed tracing (OpenTelemetry), centralized logging (Cloud Logging), and service-level metrics (Prometheus) are requirements, not nice-to-haves.

My biggest lesson: extract the easiest service first. Don't start with the core business logic. Start with a peripheral service, email notifications, file processing, reporting. Build confidence in the patterns and tooling before tackling the complex stuff. Early wins build momentum and reveal problems at low stakes.