Microservice design patterns

Category : Microservices | Sub Category : Microservices | By Prasad Bonam Last updated: 2023-07-15 14:54:07 Viewed : 338


Microservice design patterns:

Microservice architecture is a design approach that structures an application as a collection of loosely coupled and independently deployable services. It promotes scalability, agility, and fault tolerance. When designing microservices, various design patterns can be used to address common challenges and ensure the effectiveness of the architecture. Here are some commonly used microservice design patterns:

  1. Service Registry and Discovery: Services register themselves with a central registry, allowing other services to discover and communicate with them. This pattern enables dynamic service discovery and supports load balancing and failover.

    In a microservices architecture, Service Registry and Discovery are important components that help manage the dynamic nature of the system. They facilitate the location and communication with services in the network. Here are examples of Service Registry and Discovery patterns using popular tools:

    1. Netflix Eureka:

      • Service Registry: Eureka is a service registry server where microservices can register themselves.
      • Service Discovery: Microservices can query the Eureka server to discover the location (IP address and port) of other microservices.

      Example of registering a service in Eureka (using Spring Cloud):

      java
      @SpringBootApplication @EnableEurekaClient public class MyMicroserviceApplication { public static void main(String[] args) { SpringApplication.run(MyMicroserviceApplication.class, args); } }
    2. Consul:

      • Service Registry: Consul is a tool for service discovery and key-value storage. Microservices register with Consul.
      • Service Discovery: Microservices query Consul to discover the location of other services.

      Example of registering a service in Consul:

      bash
      $ consul agent -dev -node=your-node-name -config-dir=/etc/consul.d
    3. Zookeeper:

      • Service Registry: Zookeeper can be used for service registry by creating a znode for each microservice.
      • Service Discovery: Microservices watch the relevant znodes to discover other services.

      Example of registering a service in Zookeeper (using Curator, a Zookeeper client library for Java):

      java
      CuratorFramework client = CuratorFrameworkFactory.newClient("zookeeper-server:2181", new RetryNTimes(3, 1000)); client.start(); client.create().creatingParentsIfNeeded().forPath("/services/my-service", "127.0.0.1:8080".getBytes());
    4. HashiCorp Consul with Spring Cloud:

      • Service Registry and Discovery: Using Spring Cloud with Consul, you can integrate Consul for service registry and discovery seamlessly with Spring Boot.

      Example of using Consul with Spring Cloud:

      java
      @SpringBootApplication @EnableDiscoveryClient public class MyMicroserviceApplication { public static void main(String[] args) { SpringApplication.run(MyMicroserviceApplication.class, args); } }

    These examples illustrate how microservices can register themselves with a service registry and query it for the locations of other services. The choice of tool depends on your specific requirements and the existing technology stack in your microservices architecture.


  2. API Gateway: An API gateway provides a single entry point for clients to access multiple microservices. It handles requests, performs authentication, routing, rate limiting, and other cross-cutting concerns.

  3. Circuit Breaker: The circuit breaker pattern is used to prevent cascading failures in a distributed system. It monitors the availability of a service and, if it fails repeatedly, opens the circuit to prevent further requests, returning a fallback response instead.

  4. Bulkhead: The bulkhead pattern isolates different parts of a system to prevent failures in one component from affecting others. It involves separating services into different pools or thread groups to limit resource contention.

  5. Event-driven Architecture: In an event-driven architecture, services communicate asynchronously through events. Events are published and subscribed to by interested services, allowing loose coupling and scalability.

  6. Saga: A saga is a sequence of local transactions that together form a complex business transaction. Each step of the saga emits events, and these events trigger subsequent steps or compensating actions if an error occurs.

  7. Database per Service: Each microservice has its own dedicated database, ensuring loose coupling and allowing teams to choose the most suitable database for their services requirements.

  8. Command and Query Responsibility Segregation (CQRS): CQRS separates the read and write models of an application, allowing different models to be optimized for their specific needs. It enables efficient querying and scaling of the read side while maintaining separate write models.

  9. Fault Tolerance and Retry: Services can employ fault tolerance mechanisms such as retries, timeouts, and circuit breakers to handle transient failures and improve system reliability.

  10. Shared Data Management: Microservices may share data through event sourcing, where all changes are stored as a sequence of events, or through a shared database, caching, or message queues.

These are just a few examples of microservice design patterns. The choice of patterns depends on the specific requirements and constraints of your application. Its important to consider factors such as scalability, fault tolerance, data consistency, and operational simplicity when designing a microservice architecture.

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