A design pattern in micro-service is a reusable solution to a common problem in micro-service architecture. These patterns can help to improve the design, implementation, and maintenance of micro-services-based applications.
Why Design Patterns are needed
There are many reasons why we need design patterns in micro-services. Here are a few of the most important ones:
To improve scalability
Micro-services are designed to be scalable, but they can still become difficult to manage as they grow in size and complexity. Design patterns can help to improve scalability by providing a way to organise micro-services and their dependencies in a way that is easy to understand and maintain.
To improve reliability
Micro-services are designed to be resilient to failures, but they can still be brought down by a single point of failure. Design patterns can help to improve reliability by providing a way to isolate micro-services from each other and to ensure that they can continue to function even if one micro-service fails.
To improve security
Micro-services are designed to be secure, but they can still be vulnerable to attack. Design patterns can help to improve security by providing a way to authenticate users, to encrypt data, and to protect micro-services from unauthorised access.
To improve maintainability
Micro-services are designed to be easy to maintain, but they can still become difficult to understand and change as they grow in size and complexity. Design patterns can help to improve maintainability by providing a way to document micro-services and their dependencies in a way that is easy to understand and update.
Overall, design patterns can be a valuable asset for any micro-services project. They can help to improve scalability, reliability, security, and maintainability, which can lead to a more successful and sustainable application.
— — — — — —
Classification of Design Patterns
There are numerous design patterns for micro-services, they are classified into few categories as below
- Patterns by Communication Mechanism
- Patterns by Mitigation Approach
- Patterns by Integrations
- Patterns by Persistent/Database
- Patterns by Deployments
- Patterns by Decomposition
Patterns by Communication Mechanism
API Gateway: An API gateway is a single point of entry for all requests to a micro-services-based application. This can help to improve security, performance, and scalability.
Service Registry: A central service registry helps micro-services discover and communicate with each other without hard-coded dependencies.
Service Discovery: micro-services dynamically find each other’s endpoints through the service registry, enabling effective communication.
Choreography: micro-services communicate and collaborate directly, often through events, without a centralised controller.
Orchestration: A central component coordinates the interactions and processes of multiple micro-services to fulfil a higher-level task.
Asynchronous Messaging: All services can communicate with each other but they do not have to communicate sequentially.
Patterns by Mitigation Approach
Circuit Breaker: A circuit breaker is a pattern that helps to protect micro-services from cascading failures. If one service fails, the circuit breaker will open and prevent requests from being sent to that service. This can help to prevent the failure of one service from bringing down the entire application.
Bulkhead: This pattern isolates micro-services from each other so that the failure of one micro-service does not affect the others.
Fallback: When a service is unavailable, a fallback mechanism provides an alternative response to maintain system functionality.
Patterns By Integrations
Sidecar: A sidecar is a small micro-service that is attached to another micro-service. It can provide additional functionality to the main micro-service, such as logging, monitoring, or load balancing.
Chained OR Chain of Responsibility: Chained micro-services are micro-services that are connected in a sequence. A request is sent to the first micro-service in the chain, and the response from the first micro-service is then sent to the second micro-service, and so on. This pattern can be used to implement complex business logic.
Aggregator Pattern: Collect related items of data and display them, works in DRY principle.
Branch micro-services: Branch micro-services are micro-services that are created to support a particular feature or use case. This pattern can be used to improve scalability and agility, as well as to isolate changes to different features.
Patterns by Persistent/Database
Database per Service: This pattern has each micro-service have its own database. This can help to improve performance and scalability, as well as simplify data access.
Shared Database: Certain data is shared among micro-services, enabling efficient data access, but also requiring careful management to avoid tight coupling.
Saga: Manages distributed transactions across multiple micro-services, ensuring consistency in a decentralised environment.
Polyglot Persistence: Uses the most appropriate database technology for each micro-service’s data storage needs.
Command Query Responsibility Segregation (CQRS): This pattern separates commands (operations that change data) from queries (operations that read data). This can help to improve performance and scalability, as well as simplify the design of micro-services.
Event Sourcing: This pattern stores all changes to data as events. This can help to improve scalability and reliability, as well as simplify the development of micro-services.
Patterns by Deployments
Independent Deployability: Each micro-service can be developed, tested, and deployed independently, facilitating rapid iteration.
Continuous Delivery Patterns: These patterns are used to automate the deployment of micro-services. This can help to improve agility and scalability, as well as simplify the deployment process.
Canary Deployment Pattern: Canary deployment pattern is a deployment strategy that is commonly used in micro-services architecture. It involves gradually rolling out a new version of a micro-service to a small percentage of users, and then gradually increasing the percentage of users over time. This allows developers to test the new version of the micro-service in production with real users, and to identify and fix any problems before the new version is rolled out to all users.
Blue-Green Deployment Pattern: Blue-Green deployment pattern is a deployment strategy that is commonly used in micro-services architecture. It involves deploying two identical versions of a micro-service in production, one called “blue” and the other called “green”. The blue version is the live version that is serving traffic, and the green version is the new version that is being tested.
Patterns by Decomposition
Strangler pattern: This pattern helps to migrate an existing monolithic application to a micro-services architecture gradually.
Domain Driven Design (Business Capabilities): Designing the services by segregating based on the business functionalities.
