Microservices vs. Monoliths: Making the Right Choice

The Underrated Monolith

A well-structured monolith is an excellent starting point for most applications. It provides simplicity in deployment (one artifact, one process), straightforward debugging (one stack trace, one log stream), easy refactoring (IDE-supported, compile-time safe), and lower operational overhead (no service mesh, no distributed tracing needed). The key is modular design within the monolith — using clear module boundaries, dependency injection, and well-defined interfaces between domains.

When Microservices Make Sense

Microservices become valuable when your organization has multiple autonomous teams that need to deploy independently, different parts of the system have fundamentally different scaling requirements, you need technology diversity (e.g., a machine learning service in Python alongside a web API in Go), or you've identified clear bounded contexts with minimal cross-service data dependencies. The prerequisite is operational maturity: you need robust CI/CD pipelines, container orchestration, observability tooling, and distributed tracing before microservices are viable.

• Multiple teams (6+ developers) needing independent deployment cycles
• Highly divergent scaling needs (e.g., auth service vs. video processing)
• Regulatory isolation requirements (e.g., PCI compliance for payment processing)
• Proven bounded contexts with stable, well-defined interfaces

The Distributed Systems Tax

Every network boundary introduces latency, failure modes, and complexity. With microservices, you must handle service discovery, load balancing, circuit breaking, retry logic with idempotency, distributed transactions or eventual consistency, cross-service authentication, API versioning and backward compatibility, and distributed tracing for debugging. This overhead is the 'distributed systems tax' that every microservice architecture pays. If your organization lacks the operational infrastructure to manage these concerns, microservices will slow you down rather than speed you up.

The Strangler Fig Migration Pattern

If you decide to extract services from a monolith, the Strangler Fig pattern is the safest approach. Instead of a risky big-bang rewrite, you incrementally route specific functionality to new services while the monolith continues serving everything else. Start by identifying the most independent domain with the clearest boundary. Build the new service alongside the monolith, implement a routing layer (API gateway or reverse proxy) that can direct traffic to either system, and gradually shift traffic to the new service. Keep the monolith's code for that domain in place as a fallback until the new service is proven in production.

Phase 1: Identify bounded context (e.g., notifications)
Phase 2: Build new Notifications Service alongside monolith
Phase 3: Route /api/notifications → new service via API gateway
Phase 4: Monitor for 2-4 weeks, compare behavior
Phase 5: Remove notifications code from monolith
Phase 6: Repeat for next bounded context

Decision Framework

Use this simple heuristic: start with a modular monolith. Extract a service only when you can articulate a concrete, current problem that extraction solves (not a hypothetical future one). The most common valid reasons are independent deployment frequency requirements, divergent scaling needs, and team autonomy at organizational scale. If your primary motivation is 'microservices are modern' or 'everyone is doing it,' reconsider — you're likely adding complexity without proportional benefit.