Why Distributed Monolith is a Bad Practice

Why Distributed Monolith is a Bad Practice

In software architecture, transitioning from monolithic applications to microservices is often seen as a step towards greater modularity, scalability, and resilience. However, this transition can sometimes result in a distributed monolith, which combines the drawbacks of both monolithic and microservices architectures without realizing the benefits of either. This article explores why a distributed monolith is considered a bad practice and the challenges it introduces.

Characteristics of a Distributed Monolith

Tight Coupling Between Services: Services are dependent on each other to such an extent that a change in one service often requires changes in others.

Synchronous Communication: Services frequently rely on synchronous communication (e.g., HTTP calls), creating tight runtime coupling.

Shared Databases: Multiple services access the same database, leading to data consistency issues and deployment complications.

Centralized Deployment: Despite being distributed, services may be deployed together, reducing the benefits of modularity.

Complex Inter-Service Communication: Overly intricate communication patterns between services.

Why Distributed Monolith is a Bad Practice

1. Scalability Challenges

Limited Independent Scaling: Due to interdependencies, scaling individual services independently becomes difficult. This can lead to inefficient resource utilization.

Performance Bottlenecks: Synchronous communication can create performance bottlenecks, as a slow response from one service can delay the entire process.

2. Deployment Complexities

Coordinated Deployments: Changes in one service often require synchronized deployments of multiple services, complicating the release process and increasing the risk of deployment failures.

Rollback Difficulties: Rolling back a single service can be challenging if other services depend on the updated version, leading to potential inconsistencies and downtime.

3. Maintenance and Development Difficulties

High Complexity: Tight coupling and shared dependencies increase the complexity of the system, making it harder to understand, maintain, and develop.

Slow Development Cycles: Changes require thorough testing across multiple services, slowing down the development process and reducing agility.

4. Resilience and Reliability Issues

Cascading Failures: Synchronous dependencies mean that a failure in one service can propagate and cause failures in other services, reducing overall system resilience.

Increased Latency: Synchronous calls between services can increase latency, impacting the user experience negatively.

5. Data Management Problems

Shared Databases: When services share a single database, it creates a strong coupling between them, leading to issues with data integrity and making it difficult to evolve the database schema independently for each service.

Transactional Complexity: Managing transactions across multiple services becomes complex and error-prone, often requiring distributed transaction mechanisms which add overhead and potential points of failure.

Mitigating the Risks of a Distributed Monolith

To avoid falling into the trap of a distributed monolith, consider the following strategies:

Decouple Services: Work towards reducing dependencies between services. Ensure that each service is as independent as possible, with well-defined APIs and clear separation of concerns.

Adopt Asynchronous Communication: Use messaging systems or event-driven architectures to reduce synchronous communication and improve system resilience.

Separate Databases: Each service should manage its own database to avoid shared dependencies and improve modularity.

Use API Gateways: Implement API gateways to manage and route requests between clients and services, improving scalability and security.

Monitor and Observe: Invest in centralized logging, monitoring, and tracing to understand service interactions and quickly identify and resolve issues.

Conclusion

A distributed monolith is a counterproductive architectural pattern that negates many of the advantages intended by adopting microservices. By maintaining tight coupling, synchronous dependencies, and shared databases, it introduces significant scalability, deployment, maintenance, and resilience challenges. To achieve the benefits of true microservices architecture, it's essential to decouple services, adopt asynchronous communication, separate databases, and implement robust CI/CD pipelines. By addressing these issues, organizations can realize the full potential of a microservices architecture and avoid the pitfalls of a distributed monolith.