Microservices vs monolith: when to choose what
The microservices vs monolith debate has evolved beyond religious arguments to pragmatic decision-making. According to O'Reilly's Microservices Adoption Report, while 77% of organizations have adopted microservices, 60% report increased operational complexity. The question isn't whether microservices are "better"—it's whether they're right for your context.
The state of architecture choices in 2025
According to InfoQ's Architecture Trends, there's growing recognition that "microservices are not a universal solution" and many organizations are adopting hybrid architectures.
Understanding the trade-offs
Monolith vs Microservices: Key Trade-offs
| Feature | Monolith | Microservices | Modular Monolith |
|---|---|---|---|
| Initial Velocity | ✓ | ✗ | ✓ |
| Team Independence | ✗ | ✓ | ✓ |
| Scalability | ✗ | ✓ | ✗ |
| Operational Simplicity | ✓ | ✗ | ✓ |
| Transaction Handling | ✓ | ✗ | ✓ |
| Debugging Ease | ✓ | ✗ | ✓ |
The Modular Monolith: Many organizations are discovering the "modular monolith" as a middle ground—clean service boundaries within a single deployable, with the option to extract services later if needed.
When monoliths make sense
Early Stage
Startups finding product-market fit need speed over scale
Small Teams
Teams under 10 engineers work efficiently in shared codebases
Simple Domains
Applications with straightforward, well-understood domains
Tight Budgets
Limited resources for infrastructure and operations
Strong Coupling
Features that naturally share data and transactions
Limited DevOps
Teams without mature CI/CD and infrastructure automation
When microservices make sense
Team Size 50+
Multiple teams need to deploy independently without coordination overhead.
Different Scaling Needs
Some components need 100x more capacity than others.
Technology Diversity
Different problems require different tech stacks (ML, streaming, etc.).
Organizational Boundaries
Conway's Law in action—architecture mirrors team structure.
Regulatory Requirements
Some data/functions need isolation for compliance reasons.
The microservices premium
Organizations pay a "microservices tax" in operational complexity. Based on DORA research and industry surveys:
Typical Microservices Overhead Increase (%)
Hidden Costs: Most organizations underestimate the operational overhead of microservices. Before committing, ensure you have the infrastructure, tooling, and expertise to manage distributed systems effectively.
Architecture decision framework
Team Size
Under 20? Start monolith. Over 50? Consider services.
Domain Maturity
Unclear boundaries? Monolith. Clear services? Extract them.
Scale Requirements
Uniform scale? Monolith. Varied needs? Services.
Team Capabilities
Limited DevOps? Monolith. Strong platform? Services.
Time to Market
Critical? Monolith. Can invest? Services possible.
Risk Tolerance
Low tolerance? Monolith. Can iterate? Services.
Common migration patterns
Strangler Fig
Gradually replace monolith functionality with services while keeping the system running.
Branch by Abstraction
Create abstraction layers in the monolith, then swap implementations to services.
Domain-First
Identify bounded contexts first, extract highest-value domains as services.
Event-Driven Extraction
Introduce event bus, publish events from monolith, build new services as consumers.
Service boundaries done right
Primary Factors for Service Boundary Definition
Communication patterns
Inter-Service Communication Patterns
| Feature | Sync REST/gRPC | Async Messaging | Event Sourcing |
|---|---|---|---|
| Low Latency | ✓ | ✗ | ✗ |
| Loose Coupling | ✗ | ✓ | ✓ |
| Reliability | ✗ | ✓ | ✓ |
| Debugging Ease | ✓ | ✗ | ✗ |
| Transaction Support | ✗ | ✗ | ✓ |
| Scale Independence | ✗ | ✓ | ✓ |
Data management strategies
Own Your Data
Each service owns its data; no direct database access across services
API as Contract
Access other services' data only through their APIs
Eventual Consistency
Accept that data won't always be immediately consistent
Sagas for Transactions
Implement distributed transactions as choreographed or orchestrated sagas
CQRS Where Needed
Separate read and write models for complex query requirements
Outbox Pattern
Ensure reliable event publishing with database transactions
Infrastructure requirements
Infrastructure Necessity for Microservices (%)
Success metrics for architecture decisions
Microservices Migration Impact Over Time
FAQ
Q: We're a startup—should we start with microservices? A: Almost never. Start with a well-structured monolith. You'll move faster, learn your domain, and can extract services later when you have clear boundaries and the team to support them.
Q: How do we know when it's time to migrate? A: Watch for: deployment conflicts between teams, inability to scale specific components, different teams needing different technology choices, or release coordination becoming a bottleneck.
Q: Can we go back from microservices to a monolith? A: Yes, and some companies have. If the complexity isn't providing proportional value, consolidation is a valid choice. The modular monolith pattern often emerges from these experiences.
Q: How many services should we have? A: There's no magic number. Start with the minimum necessary to achieve your goals. A common guideline: one service per team, with teams of 5-8 people. Avoid nano-services.
Sources and further reading
- O'Reilly Microservices Adoption Report
- Martin Fowler: Microservices Prerequisites
- Sam Newman: Building Microservices
- DORA Research on Elite Performers
- ThoughtWorks Technology Radar
Architecture Guidance: Choosing the right architecture requires understanding your team, domain, and growth trajectory. Our architects help organizations make informed decisions and execute successful migrations. Contact us to discuss your architecture strategy.
Need help deciding between microservices and monolith? Connect with our architecture experts to evaluate your specific situation.
