How to Fail at Microservices: Anti-Patterns and Architecture Pitfalls to Avoid

By Teddy Morin

Microservices are designed to enhance agility, scalability, and maintainability in modern software architecture. But when implemented poorly, they can become a nightmare that drags down your entire project. In this article, we’ll explore some common microservices anti-patterns and bad architectural practices that you need to avoid at all costs.

Understanding the Core Principles of Microservices

Before diving into what makes microservices fail, it’s essential to understand what they are supposed to be. Based on expert resources like Building Microservices and Microservice Architecture, proper microservices should be:

• Small in size
• Messaging enabled
• Bounded by contexts
• Autonomously developed
• Independently deployable
• Decentralized
• Built and released with automated processes
• Loosely coupled
• Focused on a single responsibility

If your application architecture does not respect these foundational principles, you might not be building true microservices. Instead, you could be heading toward architectural failure — even if you think you’re following the microservices trend.

The Hidden Trap: Architecture Drift

One of the most dangerous issues is that bad architecture practices can sneak up on you. You may begin with solid intentions and structure in place, but over time, drift into poor architecture choices that stray from core microservices values.

This kind of slow deviation can lead to something that resembles a microservices setup but lacks the independence, flexibility, and decoupling essential to success.

Anti-Pattern: The Distributed Monolith

One of the most infamous microservices anti-patterns is the Distributed Monolith. It looks like a microservices architecture — with separated services, multiple deployments, and APIs — but in practice, it behaves like a monolith. Components are so tightly coupled that you can’t deploy or update services independently.

A distributed monolith has all the downsides of a monolith — tight dependencies, centralized decision-making, fragile deployments — without the simplicity or clarity of just having one codebase.

Why is the distributed monolith so dangerous?

• Lack of independent deployments increases downtime and failure risk.
• Tight coupling negates scalability and independence between teams.
• It requires microservices complexity without microservices benefits.

If your services can’t be deployed on their own, or if changing one service requires updates to several others, you’re probably dealing with a distributed monolith. Investing in clearer service boundaries and autonomy is critical to break this pattern.

Anti-Pattern: The Shared Database

Another fatal flaw in microservices architecture is the shared database across different services. This approach directly contradicts the principle of service independence and loose coupling.

In a shared database scenario, multiple services rely on and modify the same data source. This shared ownership leads to complex interdependencies, fragile deployments, and extremely limited flexibility. Not to mention the chaos during schema changes or database upgrades.

Top reasons why shared databases undermine microservices:

• Violation of service boundaries and autonomy
• Difficulty scaling independently
• Hard to implement domain-driven design
• Potential data integrity conflicts between services
• Challenging environment for automated testing and deployments

Microservices should own their own databases. Data needs to be encapsulated within the domain of each service, accessed only via APIs or events. If you must coordinate data, use messaging patterns, eventual consistency, or dedicated APIs—not a shared relational database.

Best Practices to Avoid Microservice Failures

Now that we’ve covered some critical anti-patterns, let’s consider practices that ensure your microservices architecture remains successful.

1. Autonomy First

Design services so they can be developed, tested, deployed, and scaled independently. This includes separate databases, dependency boundaries, and version control.

2. API-First Communication

Use well-defined and versioned APIs or asynchronous messaging for inter-service communication. Avoid direct dependencies or tight coupling.

3. Context Boundaries

Apply domain-driven design to define meaningful service boundaries based on business capabilities. Each service should encapsulate a domain and interact with others through contracts.

4. Continuous Delivery and DevOps

Microservices thrive when integrated with automated pipelines, CI/CD practices, containerization, and robust monitoring.

5. Monitor and Observe

Introduce logging, tracing, and monitoring tools early. Observability is crucial to understand behavior across a distributed system and preempt issues.

Validate Your Architecture Regularly

Even if you start on the right path, it’s easy to veer off. Regular architecture audits, team reviews, and cross-functional collaboration help keep your services loosely coupled and efficient.

Ask yourself frequently:

• Can this service be deployed independently?
• Do we share databases or configurations we shouldn’t?
• Are coupling and dependencies increasing over time?
• Are we following CI/CD best practices?

Final Thoughts

Failing with microservices doesn’t happen overnight. It occurs through a series of decisions that may seem practical in the short term but lead to long-term technical debt. The distributed monolith and shared database anti-patterns are common but avoidable with the right architectural mindset.

If your project displays any of the warning signs discussed above, it’s time to pause, reflect, and redirect your efforts toward building scalable, resilient services that align with the true principles of microservices architecture.