Microservices vs Monolith: Making the Right Choice

Few topics in software architecture generate as much debate as the monolith vs. microservices discussion. After helping dozens of companies navigate this decision, here's our honest take.

The uncomfortable truth

Here's something the microservices evangelists won't tell you:

Most companies would be better served by a well-designed monolith than a poorly implemented microservices architecture.

We've seen too many teams adopt microservices because it's "what Netflix does" without understanding why Netflix does it — and without having Netflix's scale or engineering resources.

Understanding the tradeoffs

Monoliths: The underrated choice

Advantages:

1. Simplicity — One codebase, one deployment, one debugging experience
2. Performance — In-process calls are faster than network calls
3. Consistency — No distributed transaction headaches
4. Development speed — Especially for small teams (under 20 engineers)
5. Refactoring — IDE support for codebase-wide changes

When to choose a monolith:

• You're a startup validating product-market fit
• Your team is under 20 engineers
• You don't have clear service boundaries yet
• You can't afford dedicated DevOps resources
• Speed of iteration is your top priority

Microservices: The complex choice

Advantages:

1. Team scalability — Teams can work independently
2. Technology flexibility — Different services, different stacks
3. Fault isolation — One service failing doesn't take down everything
4. Independent scaling — Scale only what needs scaling
5. Clear ownership — Service boundaries = team boundaries

When to choose microservices:

• You have 50+ engineers working on the same product
• You have clear, stable domain boundaries
• You need to scale specific components independently
• You have dedicated platform/DevOps teams
• Different parts of your system have different scaling patterns

The decision framework

We use this framework when advising clients:

Question 1: How many engineers?
  < 20  → Lean toward monolith
  20-50 → Consider modular monolith
  > 50  → Microservices may make sense

Question 2: How clear are your domain boundaries?
  Unclear/Changing → Monolith (easier to refactor)
  Stable/Well-defined → Either approach works

Question 3: What's your DevOps maturity?
  Low  → Monolith (microservices need solid DevOps)
  High → Either approach works

Question 4: What's your scale?
  < 10K users → Monolith handles this easily
  10K-100K → Depends on workload type
  > 100K → May need selective microservices

The modular monolith: Best of both worlds?

There's a middle ground that often gets overlooked: the modular monolith.

Traditional Monolith:
├── controllers/
├── services/
├── repositories/
└── models/

Modular Monolith:
├── modules/
│   ├── users/
│   │   ├── api/
│   │   ├── domain/
│   │   └── infrastructure/
│   ├── orders/
│   │   ├── api/
│   │   ├── domain/
│   │   └── infrastructure/
│   └── payments/
│       ├── api/
│       ├── domain/
│       └── infrastructure/
└── shared/

The modular monolith:

• Enforces boundaries like microservices
• Deploys simply like a monolith
• Can be extracted into services when you have data to justify it

When we recommend microservices

Despite our cautionary tone, there are legitimate use cases:

1. Genuine scale requirements

If your authentication service handles 1M requests/minute while your reporting service handles 100 requests/minute, microservices let you scale them independently.

2. Team topology demands it

When you have multiple teams that need to deploy independently without coordination, service boundaries help.

3. Technology-driven separation

If part of your system genuinely needs Python's ML libraries while another part needs Rust's performance, separate services make sense.

4. Compliance and security

Sometimes you need certain data handled in a completely isolated system for regulatory reasons.

The migration path

If you're considering moving from monolith to microservices, here's our recommended approach:

Phase 1: Modularize the monolith

• Identify logical boundaries
• Enforce module boundaries in code
• Create internal APIs between modules

Phase 2: Extract strangler services

• Pick the most obvious extraction candidate
• Extract it as a service behind the monolith
• Route traffic gradually
• Learn from the experience

Phase 3: Evaluate and repeat

• What worked? What didn't?
• Is the added complexity worth it?
• Does the next candidate make sense?

Common microservices mistakes

If you do go the microservices route, avoid these:

1. Distributed monolith

Services that must be deployed together aren't microservices — they're a distributed monolith with all the downsides of both.

2. Shared database

If multiple services read/write the same tables, you've coupled them together regardless of how you've deployed them.

3. Synchronous everything

Microservices that make synchronous calls to each other in chains create fragile systems. Embrace async patterns.

4. Too small

"Nano-services" that only contain a few functions create unnecessary network overhead and operational burden.

Our real recommendation

Here's what we actually tell most clients:

1. Start with a monolith — Prove your idea works first
2. Keep it modular — Make future extraction possible
3. Measure before splitting — Extract services based on data, not theory
4. Invest in DevOps regardless — Good CI/CD benefits any architecture

The best architecture is the one that helps your team ship quality software efficiently. Sometimes that's microservices. Usually, especially early on, it's not.

Facing an architecture decision and want an honest second opinion? Let's talk — we'll help you make the right choice for your specific situation.