What Is Microservices Architecture? A Guide to Moving Beyond a Monolith

In brief: Microservices split an application into small services that can be developed and deployed independently. They let teams work separately, scale components individually, and isolate failures. The trade-off is distributed-systems complexity: network latency, data consistency, observability, deployment, and operational overhead. For that reason, the right question for most projects is not “How do we move to microservices?” but “Do we actually need them?” It is often healthier to start with a well-structured modular monolith and split out components only when necessary.

Last updated: September 2026

What is microservices architecture?

In a monolithic application, all features—users, orders, payments, notifications, and more—live in one codebase and one deployment unit. In a microservices architecture, each business capability is a separate service with its own code, often its own database, and its own deployment process. Services communicate through APIs or messages.

Start with a monolith: common advice

The core idea in software architect Martin Fowler's “Monolith First” article is to begin a new project with a monolith rather than microservices. The reasons:

• Early on, speed and learning matter most. Microservices add what Fowler calls a “microservice premium” and can slow both down.
• Drawing service boundaries correctly takes experience. Moving functionality between services is much harder than moving it within a monolith.
• Fowler says most projects that start with microservices from scratch encounter serious problems. His 2015 article presents this as experience-based observation, not definitive research, but it remains a widely cited reference.

This does not mean microservices are bad; it means they should be adopted for the right reason and at the right time.

Example: Prime Video's monitoring service

In 2023, reports drew attention to the Prime Video team moving its audio/video quality-monitoring service from distributed microservices to a single application and reducing infrastructure costs by more than 90% (The Stack). The important detail is that this applied only to that monitoring service, not all of Prime Video. The bottleneck was data transfer between services and orchestration costs. The lesson: choose architecture for the workload; neither “microservices are always better” nor “monoliths are always better” is true.

When should you consider microservices?

Consider them when several of these signs are present:

1. Multiple teams are blocking one another in the same codebase, and releases have to queue up.
2. Parts of the application have very different scaling needs, such as image processing or search receiving far more load than other areas.
3. You have different technology or security requirements, for example payment processing needs separate isolation.
4. Failures spread: one module crashing can bring down the entire system.
5. Your organization is mature enough to operate services independently, with CI/CD, monitoring, and on-call processes.

It is sensible to wait when the team is small, product-market fit is unsettled, business boundaries are unclear, or operational experience is limited. In those cases, the cost of microservices can outweigh the benefit.

An alternative: the modular monolith

A modular monolith is a single deployment unit with clearly bounded modules such as orders, payments, and users. Modules do not reach directly into one another's database tables; they communicate through defined interfaces. It provides the most valuable microservices discipline—clear boundaries—with simpler operations, and makes it easier to extract a module later. For many teams, it is the most sensible middle ground.

Migration strategy: the strangler pattern

Rewriting an existing monolith overnight is risky. A common approach is the strangler pattern: place a routing layer (API gateway or reverse proxy) in front of the monolith, build new or extracted functionality as a separate service, direct the relevant traffic to it, and gradually shrink the monolith.

Steps:

1. Define boundaries. Start with business domains and ask, “Who owns this data?” Choose a low-dependency component with clear value.
2. Build observability first. Splitting a system without logs, metrics, and distributed tracing is flying blind.
3. Extract the first service. Start with an edge capability such as notifications, reporting, or search and learn from it.
4. Separate the data. Each service should own its data. Direct access to one shared database is a “distributed monolith” trap.
5. Shift routing gradually. Move traffic to the new service in increments and keep a rollback plan.
6. Remove the old code. Do not leave the extracted functionality in the monolith indefinitely.

Core components

• API gateway: One entry point for clients, handling authentication, rate limits, and routing.
• Service discovery: Lets services find each other dynamically; often built into platforms such as Kubernetes.
• Message queue/event stream (Kafka, RabbitMQ, and similar): Enables asynchronous, loosely coupled communication. Distributed workflows can use the saga pattern to define compensating actions.
• Resilience patterns: Timeouts, retries, and circuit breakers help prevent one slow service from causing cascading failures.
• Distributed tracing and centralized logs: Follow a request across services using tools such as OpenTelemetry and central log analysis.
• Containers and orchestration: Docker and Kubernetes, automatic CI/CD deployment, and blue-green or canary releases.

Pitfalls to watch for

1. Distributed monolith: Services are separate but tightly coupled, so changing one affects all the others. Splitting adds complexity without independence.
2. Too many tiny services: Making every function its own service increases communication overhead.
3. Shared database: Boundaries disappear if services write to the same tables.
4. Testing and environment complexity: End-to-end tests and local development become harder.
5. Ignoring network latency and failures: A local function call becomes a network call, so latency and error handling matter.
6. Cost: Infrastructure, observability tools, and operations staff add up.
7. Organizational mismatch: Speed does not improve when service and team boundaries do not align.

Decision checklist

• Is product-market fit established?
• Are several teams blocking one another in the same codebase?
• Do specific components need different scale, security, or technologies?
• Do you have CI/CD, monitoring, logs, and an on-call process?
• Can you define service ownership around business domains?
• Could a modular monolith be enough?

If most answers are “no,” stay with a monolith or modular monolith.

What Aktaş Digital can provide

For web applications, SaaS platforms, and enterprise systems, we choose architecture to fit the requirements. Most projects benefit from a modular, well-tested core first, with components that can be separated if needed. Our web application and SaaS platform development services include architecture consulting. Our SaaS guide covers the path from MVP to scale. Contact us about an existing system through our project inquiry form.

Frequently asked questions

Is microservices architecture better than a monolith?

No; they suit different situations. A monolith is often more efficient for a small team or an early-stage product. Microservices can help larger systems with multiple teams and different scaling needs.

How long does a migration take?

It depends on the size and dependencies of the system. Rather than a one-time rewrite, migration is usually a gradual process that can take months or years. The strangler pattern lets you move small parts at a time.

Should every service have its own database?

For service independence, each service should own its data. This creates additional design work for consistency and reporting.

Is Kubernetes required?

No. It is a common platform for deploying, scaling, and monitoring many services, but simpler options may work for a small number of services.

Can a modular monolith later become microservices?

Yes. Clear boundaries and interfaces between modules make future extraction considerably easier.

Conclusion

Microservices are a tool, not a goal. They work well for organizations with clear boundaries, independent teams, and mature operations; for others, a modular monolith is often faster, less expensive, and safer. When migration is necessary, move gradually and build observability first.