You Think You Have Microservices? You Probably Have a Distributed Monolith!

Introduction

Many teams proudly claim they use a microservices architecture, but in reality, they have built a distributed monolith. This misunderstanding leads to deployment nightmares, inter-service dependencies, and fragile systems that collapse when a single component fails. In this article, we’ll break down the difference between microservices and a distributed monolith, highlight real-world examples, and discuss whether a distributed monolith is always bad.

What Are Microservices?

Microservices are an architectural style where applications are composed of independent, loosely coupled services that:

• Can be deployed independently
• Have separate databases and state management
• Communicate in an asynchronous, event-driven manner
• Are resilient and do not depend on a single service to function

Real-World Microservices Examples:

✅ Netflix – Fully event-driven architecture, independent deployments, chaos engineering

✅ Amazon – Polyglot services with individual ownership, fully decoupled scaling

✅ Uber – Transitioned from a monolith to a microservices-based event-driven system

Pros and Cons of Microservices

✅ Advantages of Microservices

1. Scalability – Each service can be scaled independently based on demand.
2. Faster Development and Deployment – Teams can develop, test, and deploy services independently.
3. Improved Fault Isolation – A failure in one service does not bring down the entire system.
4. Technology Flexibility – Each service can use the best programming language or database for its needs.
5. Better Team Autonomy – Teams can own specific services without interfering with others.

❌ Disadvantages of Microservices

1. Increased Complexity – Managing multiple services requires advanced DevOps practices.
2. Data Consistency Challenges – Transactions across multiple services require event-driven patterns.
3. Deployment Overhead – More CI/CD pipelines, service discovery, and orchestration.
4. Latency Overhead – Inter-service communication introduces network delays.
5. Monitoring and Debugging Complexity – Logs, tracing, and observability become more challenging.

What Is a Distributed Monolith?

A distributed monolith is an application that looks like a microservices system on the surface but has the worst aspects of both monolithic and microservices architectures. It typically has:

• Services that cannot be deployed independently
• Tightly coupled inter-service communication
• A single point of failure (e.g., a User Service that all other services depend on)
• Synchronous request-response messaging instead of event-driven communication

Real-World Example of a Distributed Monolith

In one of my past projects, the company claimed to use microservices, but in reality, it was a distributed monolith:

• Each service had its own database and CI/CD pipeline ✅
• Services communicated via a message broker ✅
• BUT:
• The message broker was used in a synchronous manner rather than event-driven ❌
• Services depended on request-response messaging, creating strong interdependencies ❌
• Certain core services became bottlenecks and single points of failure ❌
• Releasing a new version of any service often required coordinated updates across multiple services ❌

This meant the system was not truly microservices because it lacked independent deployments and was not resilient to failures.

Pros and Cons of a Distributed Monolith

Although a distributed monolith is often seen as a failure state, it does have some benefits in certain cases.

✅ Advantages of a Distributed Monolith

1. Easier Debugging – Logs and execution flow are more centralized.
2. Stronger Data Consistency – Unlike microservices, there’s less need for eventual consistency and distributed transactions.
3. Simpler Local Development – Running all services together is easier compared to managing microservices locally.
4. Faster Initial Development – No need for complex API versioning or strict service boundaries.
5. Less DevOps Complexity – Fewer Kubernetes, service discovery, and deployment challenges.

❌ Disadvantages of a Distributed Monolith

1. Tightly Coupled Services – Changes in one service often require updates in others.
2. Difficult to Scale – Cannot scale individual services independently.
3. Single Points of Failure – A failure in one key service (e.g., User Service) can bring down the entire system.
4. Deployment Bottlenecks – Releasing one service often requires coordinated updates to others.
5. Increased Operational Complexity – Microservices-like overhead without the benefits of true microservices.

How to Transition from a Distributed Monolith to True Microservices

If your system suffers from tight coupling, deployment difficulties, and interdependent services, it may be time to transition towards true microservices.

Can We Ever Achieve “Perfect” Microservices?

In theory, yes. In practice, it’s extremely difficult. Some trade-offs are always necessary depending on the business needs. The key is to minimize coupling as much as possible and ensure that failure in one service doesn’t break the entire system.

How to Move Toward True Microservices?

✅ 1. Move to Asynchronous, Event-Driven Communication

• Instead of request-reply messaging, adopt event-driven patterns (e.g., Kafka, SNS/SQS, event sourcing).

✅ 2. Reduce Service Dependencies

• Identify and refactor services that act as critical bottlenecks (e.g., User Service should not be a dependency for everything).

✅ 3. Enable Truly Independent Deployments

• Use API versioning and backward compatibility to allow services to evolve independently.

✅ 4. Separate Databases Properly

• Each service should own its own data and communicate via events or APIs, not shared databases.

✅ 5. Implement Proper Service Boundaries

• Define services based on business capabilities, not just technical layers.

Conclusion

A distributed monolith isn’t always bad, but it removes the key benefits of microservices while adding unnecessary complexity. If your system suffers from interdependent deployments, tight service coupling, and single points of failure, you may be dealing with a distributed monolith rather than true microservices.

To transition towards real microservices, teams should prioritize decoupling, asynchronous communication, and independent deployments. While achieving a perfect microservices architecture is difficult, companies like Netflix, Amazon, and Uber prove that it’s possible with the right approach.

What’s your experience with microservices? Have you ever worked on a system that turned out to be a distributed monolith? Let’s discuss in the comments!