Microservices vs Monoliths Part 3: Technical Considerations That Actually Matter

This is Part 3 of our five-part series on microservices versus monoliths. In Parts 1 and 2, we examined the motivations and business drivers behind architectural decisions. Now we’ll explore the technical considerations that should inform your choice.

Technical Considerations That Matter

Once you’ve clarified your business drivers, certain technical factors can help refine your decision. These aren’t abstract theoretical concerns—they have real implications for system reliability, performance, and maintainability.

State Management Complexity

Applications with complex state management, particularly those requiring transactions across multiple domains, often face significant challenges in a microservices architecture. The distributed transaction problem is notoriously difficult to solve elegantly.

Consider an e-commerce system where placing an order requires:

• Verifying inventory availability
• Processing payment
• Updating customer order history
• Triggering fulfillment workflows

In a monolithic architecture, this entire process can occur within a single database transaction, guaranteeing consistency. If any step fails, the entire transaction rolls back cleanly.

In a microservices architecture, these operations might span multiple services and databases. Implementing consistency across these services requires patterns like saga orchestration or event sourcing, which add significant complexity. You’re not just writing business logic anymore—you’re implementing distributed systems protocols.

Scaling Patterns

Not all scaling is equal. Understand whether your application needs to scale as a whole or if specific functions face disproportionate load. Microservices excel when different components have vastly different scaling requirements.

A video streaming platform provides a clear example. The video transcoding service might require massive computational resources and scale to hundreds of instances during peak upload times. Meanwhile, the user authentication service might run comfortably on a handful of instances. Separating these into microservices allows independent scaling, potentially reducing infrastructure costs significantly.

However, if your application scales uniformly—where all components need to grow proportionally—the operational overhead of microservices might not justify the complexity. A monolith can scale horizontally too, and doing so is often simpler than managing dozens of microservices.

Data Gravity and Service Boundaries

Data has gravity—functionality tends to cluster around data. Many teams underestimate how challenging it becomes to maintain data consistency across service boundaries, especially when transactions span multiple services.

When decomposing a system into microservices, the quality of your service boundaries directly impacts success. Poor boundaries result in services constantly reaching across to other services for data or functionality, creating a distributed monolith—the worst of both worlds.

Good service boundaries align with business domains and minimize cross-service communication. Achieving this requires deep understanding of your business domain, which often only comes from experience with the system.

Performance Requirements and Network Latency

In a monolith, function calls between components happen in-process, measured in nanoseconds. In microservices, those same interactions become network calls, measured in milliseconds—three orders of magnitude slower.

For many applications, this latency is acceptable or even negligible. But for systems with tight performance requirements or chatty communication patterns, the network overhead of microservices can become a significant bottleneck.

A financial trading platform processing thousands of trades per second might find that the network latency of microservices unacceptably slows transaction processing. Meanwhile, a content management system where users expect second-scale response times easily absorbs this latency.

Existing Technical Debt

Your starting point matters. Organizations with significant technical debt in a monolith sometimes see microservices as an escape hatch. However, decomposing a problematic monolith often means distributing that technical debt across multiple services, making it even harder to address.