Microservices have become the default “modern” architectural choice. The promises sound incredible: independent teams, autonomous deployments, faster iteration, cleaner scaling.

But here’s the truth: microservices shift complexity — they don’t remove it. Without real design rigor and production-grade practices, they can make your life significantly harder.

Let’s break down exactly why — with practical, developer-focused examples.

Complexity Shifts, Not Disappears

In a monolith, a database transaction is atomic. When you break apart services, that same transaction turns into a distributed operation across multiple services.

Example use case: user signup

• Create user record

• Create billing profile

• Send welcome email

In a monolith, this might be a simple transaction. In microservices, you now have three different services coordinating.

Example flow:

What happens if the billing service fails after the user record is created? You need a compensating transaction — there is no simple rollback.

Observability is Mandatory

With 20+ services, you cannot debug the old-fashioned way. You must invest in:

• Distributed tracing

• Correlated structured logs

• Metrics with alerting

Example with OpenTelemetry (Node.js):

import { NodeSDK } from '@opentelemetry/sdk-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';

const sdk = new NodeSDK({
  instrumentations: [getNodeAutoInstrumentations()]

This gives you traces so you can follow requests across services and spot latency or failures.

The Network is Your New Bottleneck

Moving from function calls to network calls introduces latency, retries, timeouts, and TLS handshakes.

Example deployment YAML snippet in Kubernetes with timeouts and retries defined:

That config ensures you retry billing calls safely rather than exploding on a transient network hiccup.

Organizational Coordination

Conway’s Law is real: if your team has unclear ownership, your services will mirror that confusion.

Practical DevOps step:
Define a team-per-domain mapping, then enforce service boundaries with clear API contracts.

For example, in a contracts repository:

Contract-first design gives you a shared definition, ideally in Protobuf, JSON Schema, or OpenAPI, so everyone speaks the same language.

Local Development is Painful

Spinning up 30 containers locally is no joke. Even docker-compose hits a wall.

What worked for us:

• Partial stack mocking

• API contract tests

• Lightweight test doubles with tools like WireMock

Sample WireMock stub example:

This lets you test locally against fake billing services without running the real thing.

Coordinated Deployment Is Hard

With a monolith, you ship one artifact. With microservices, you coordinate many.

Typical CI/CD resources to manage:

• Version tagging per service

• Shared libraries version control

• Infrastructure dependencies (databases, message queues)

• Deployment order

Example GitHub Actions snippet for independent service deploys with semantic versioning:

Versioning and tagging every deployment keeps things traceable and rollbacks predictable.

Real Production Use Case

Imagine you split a customer onboarding flow into three services:

• UserService (creates profile)

• BillingService (creates billing account)

• EmailService (sends welcome email)

Without careful orchestration, these can break apart:

1. UserService creates profile

2. BillingService fails to set up billing

3. EmailService sends welcome email anyway

What you really need is a coordination pattern, for example a saga orchestration to enforce consistency:

Saga orchestrator pseudo-code example:

That is the reality of microservices: you have to build these orchestration patterns yourself.

Final Thoughts

Microservices can be powerful — they scale, they decouple ownership, and they speed up delivery if you have:

• solid observability

• robust CI/CD

• clear domain contracts

• reliable coordination mechanisms

• well-defined team boundaries

Otherwise, you’re simply replacing monolith pain with a distributed headache.

In short, microservices are far harder than you think, and they deserve far more discipline than a quick architecture diagram in a slide deck.