In 2025, the development world is ready to move from traditional architecture to a more advanced application development approach. Unified models like monolithic architecture are history, and Microservices today are the testament to modern-day software architecture. And why not? They represent a more flexible and scalable approach to developing large, complicated applications with easier management solutions.
If you are wondering what these microservices design patterns and how using these patterns can ensure a higher level of accuracy in writing code. In this article, we will discuss the top 10 microservices design patterns, their benefits, and how you can choose the best for specific issues.
Designing successful microservices may require much more effort. Including choosing a design pattern, which is one of the most critical components of designing successful microservices.
| OTT giant Netflix experienced increasing difficulties in 2009 due to the growing demand for expanding video streaming services. It could not exceed the capacity of its infrastructure, so it decided to switch from a monolithic to a microservices architecture for its IT infrastructure and move it from its private data centers to a public cloud. The problem was that the term “microservices” was not known widely, nor was the architecture. Netflix also became the first widely known company to successfully migrate from a monolith to a cloud-based microservices architecture. It was one of the reasons why it received the 2015 JAX Special Jury award for this new architecture that incorporated DevOps. Although Netflix’s programmers release code very frequently, sometimes thousands of times, the company now has thousands of microservices that oversee and support distinct platform components. |
Top 10 Design Patterns in Microservices Architecture
Leading organizations are well aware of the benefits that come with shifting to microservices architecture and the modern-day approach. They use Microservices to enable themselves to mitigate inherent challenges around scalability, performance, and deployment, that application designers, architects, and developers face. Some of the popular Microservices design patterns are:
API Gateway Pattern
The API Gateway aka “backend for frontend” (BFF) is a crucial architectural tool built to serve the needs of clients. Acting as a central hub they enhance communication between microservices and clients.
It is a reverse proxy that routes client requests to the correct microservices. It integrates several microservices behind a single entry point and can handle cross-cutting concerns like authentication, logging, and rate limiting.
Example: A mobile app might talk to an API Gateway, which then routes the request to the appropriate backend services (user management, orders, payments, etc.)
Service Discovery Pattern
In microservices architectures, services are usually dynamic and can scale in or out based on load. It helps the client to know where the service instance is located. The Service Discovery pattern allows services to register themselves and discover each other at runtime, while acting as a registry in which the addresses of all instances are tracked, ensuring smooth communication between services.
In service discovery, there are two types of patterns.
- Client Side Service Discovery
- Server Side Service Discovery
Example: Consul or Eureka can be used for service registration and discovery in Java-based microservices.
Circuit Breaker Pattern
The Circuit Breaker pattern acts as an electrical circuit breaker (safety switch) that gracefully prevents failure by preventing one service from propagating or repeatedly trying to execute an operation that is likely to fail and could worsen things.
It tracks requests and “opens” the circuit when a service is not healthy, avoiding additional load and allowing the system to recover. Further, it enhances fault tolerance by isolating and managing failures in individual services. Example: Netflix’s Hystrix is a very popular library to implement this pattern in Java.
Event-Driven Architecture Pattern
This pattern uses events to trigger communication between microservices, thus encouraging loose coupling. Services publish events when a state change occurs, and other services subscribe to those events.
Example: Kafka is one of the most popular event streaming platforms, usually used with Java-based microservices.
Saga Pattern
Saga pattern handles long-running business transactions with the consistency of data across multiple services. It breaks down into small, independent transactions with compensating actions in case of failure of one.
Example: In an e-commerce application, the payment service could trigger a sequence of steps (order creation, payment, inventory update) with compensating transactions in case of failure.
Database per Service Pattern
Each microservice manages its database, which ensures the independence of services. This pattern promotes decentralized data management by assigning dedicated databases to each service. It allows services to choose data bases that fit right and help avoid tight coupling between services and databases.
Example: A Java microservice handling customer data might have its own PostgreSQL database, while an order service uses MySQL.
Strangler Fig Pattern
The Strangler Pattern is a design approach for incrementally modernizing a monolithic application. It involves replacing parts of the application with microservices, often by wrapping the monolithic system with a facade and gradually transitioning functionality to new microservices.
Using the Strangler Fig pattern you can incrementally rewrite your codebase, and strangle your old codebase after a few months or years, so it can be completely wiped clean. This is called
Example: Migrating legacy systems to microservices without disrupting ongoing operations.
Client-Side Load Balancing Pattern
In these cases, instead of having a central load balancer, the client can distribute the load by choosing which server to request from, using metadata such as service endpoints or status information.
The logic of the Load Balancer is part of the client itself. It carries the list of servers and, based on an algorithm, determines which server a particular request must be directed to.
Example: Client-side load balancing in Java using Ribbon
Shared Nothing Pattern
Here, each microservice operates independently without dependence on shared resources. It leads to scalability and robustness. It offers a decentralized design with unique nuances, offering compelling benefits for specific use cases.
Unique Nuances
1. No Single Point of Contention
2. Fault Isolation
3. Scale Out, Not Up
4. Data Partitioning
Example: Running each service with its database instance rather than sharing one database.
CQRS Pattern
CQRS segregates the read and write operations of a service into different models, which will make the performance and scalability better. It allows handling queries and commands in microservices separately and makes the best use of each one.
Example: The user service might use different models to query a user’s data and update information about the user.
Benefits of Using Microservices Design Patterns
Microservices design patterns are critical as they solve common issues related to architectural problems in distributed systems, such as communication, data management, and service scalability, helping developers build scalable, flexible, and easier-to-maintain systems.
Some advantages of microservices developers should know are:
- Modularity and Scalability
Microservices allow you to break down a complex application into smaller, independently deployable services. Design patterns like the API Gateway or Service Discovery allow seamless integration and management of these services.
- Resilience and Fault Tolerance
Some design patterns help ensure that your system continues to function even when services fail. Patterns such as “Circuit Breaker” and “Retry” improve the fault tolerance of your microservices-based system.
- Separation of Concerns
Microservices design patterns enforce the separation of concerns, which allows services to focus on their specific functionality without interfering with others. This improves maintainability and readability.
- Decoupling of Dependencies
Microservices can communicate with each other without being tightly coupled by using patterns like “Event-Driven Architecture” or “Saga.” This makes it easier to scale and modify individual components without the system breaking down.
- Flexibility and Technology Agnostic
Different services can be developed in different programming languages and technologies because of microservice design patterns. Unlike monolithic applications, the microservices architecture enables teams to develop new features and make changes fast without having to rewrite large portions of existing code. This gives the developers more flexibility and the liberty to use the right tool for the job.
How to Choose Microservices Design Patterns
Many factors may influence your selection approaches, however, choosing the best microservices design pattern can be summarised by considering these common points. First the size and complexity of the system, second the problem you want to solve, and third, trade-offs you can make.
Here’s a step-by-step approach.
- Identify the issues at hand: big data processing, transactions across services, fault tolerance, and more.
- Evaluation of the Needs for Each Microservice: Some microservices may need high availability, while others may need high throughput. Consider how each pattern will meet your service’s specific needs.
- Consider Integration Needs: If your microservices must communicate with each other, then Service Discovery or Event-Driven Architecture might be helpful.
- Supported Technology Stack: Some patterns, like API Gateway or Circuit Breaker, require specific tools or libraries. Ensure that your technology stack supports the patterns you choose.
- Scalability and Flexibility: Consider how easily your architecture can scale. Patterns like Database per Service and Client-Side Load Balancing offer increased scalability.
- Assess Trade-offs: Some patterns introduce complexity or require additional resources (e.g., event-driven systems may require message brokers). Consider the trade-offs before committing to a pattern.
Wrap up
A microservices architecture is designed by taking into account the patterns that best address your system’s needs. The following microservices design patterns will help programmers improve scalability, resilience, and maintainability.
When choosing a pattern, consider the requirements of your application, the scalability needs, and the technologies involved. By carefully choosing the right patterns, you can build a robust, fault-tolerant, and easily manageable microservices architecture.
