Microservices

Microservices architecture divides a system into multiple independent services, which are developed, deployed, and scaled independently. Each service has a clearly defined responsibility, often its own database, and communicates with other services over the network (API, messaging).

✅ When is it appropriate

Microservices make sense if most of the following apply:

you have a large team (10+ developers) or multiple teams
teams need to be autonomous and independent
the system has high domain complexity
you need independent deployment and scaling
you have strong DevOps and SRE (Site Reliability Engineering) capabilities
the project is long-term and business-critical

In these cases, microservices pay off over time: each team can develop, test, and deploy their service independently without waiting for others, specific services can be scaled up under load without scaling the entire system, and technology choices can be made per service rather than locked in globally.

❌ When is it NOT appropriate

Microservices are a poor choice if:

you have a small or medium-sized team
you are building an MVP or early-stage product
you need to iterate quickly and frequently change direction
you do not have automated CI/CD
monitoring, logging, and tracing are missing
the infrastructure needs to be simple and low-cost

Without the right foundation, microservices create more problems than they solve. Every service needs its own CI/CD pipeline, monitoring, logging, and distributed tracing. Without these, finding the source of a bug across 10 services becomes extremely difficult, and deployments turn into high-risk operations.

👍 Advantages

independent service deployment
autonomous teams without blocking each other
ability to scale only the critical parts of the system
better handling of large and complex domains
technological flexibility (each service can use a different programming language, framework, or database)

👎 Disadvantages

high architectural and operational complexity
network communication issues (latency, partial failures)
difficult testing of distributed systems
complex cross-service transactions
higher infrastructure and personnel costs
demanding monitoring and debugging

🛠️ Typical use cases

large SaaS platforms
high-traffic e-commerce systems
fintech and enterprise applications
global products with multiple teams
systems with high availability requirements

⚠️ Common mistakes (anti-patterns)

transitioning to microservices too early
splitting the system without clear domain boundaries
a shared database between services
overly synchronous communication between services
ignoring failure scenarios
microservices without autonomous teams

A very common outcome is a so-called distributed monolith: a system that is split into separate services but remains tightly coupled, so any change in one service requires coordinated changes in others. This combines the complexity of microservices with none of the benefits, you get the worst of both worlds.

💡 How to build on it wisely

Recommended approach:

Start with a simple monolith.
Evolve into a modular monolith.
Observe which modules change and scale the most.
Extract only the parts that truly need it.

This approach reduces risk, preserves development speed, and allows for gradual learning.

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