Microservices Design Patterns
Microservices Design Patterns with real world use cases
1. API Gateway Pattern
Summary: Acts as a single entry point for clients to access multiple microservices, managing request routing, composition, and protocol translation.
Pros:
Simplifies client interactions.
Centralizes security and request logging.
Cons:
Can become a bottleneck if overloaded.
Single point of failure.
Use Cases:
E-commerce Platforms: Consolidate different services (product, order, payment) into one API for easier client access.
Mobile Applications: Use an API Gateway to provide a consistent interface to various backend services.
2. Circuit Breaker Pattern
Summary: Prevents calls to a failing service to allow it time to recover, reducing cascading failures across the system.
Pros:
Increases system resilience.
Helps manage temporary service failures.
Cons:
Requires careful configuration of thresholds.
May mask deeper underlying issues.
Use Cases:
Streaming Services (e.g., Netflix): Manage API calls to third-party services to prevent user experience degradation during outages.
Payment Processing: Stop attempts to communicate with a failing payment service during peak traffic.
3. Service Discovery Pattern
Summary: Automatically detects available services within the microservices architecture, enabling dynamic service interaction.
Pros:
Simplifies service-to-service communication.
Facilitates dynamic scaling of services.
Cons:
Adds complexity in architecture management.
Requires a reliable registry mechanism.
Use Cases:
Cloud-Native Applications: Use tools like Eureka or Consul for service registration and discovery in dynamic environments.
Microservices for IoT: Enable devices to find and interact with services without hardcoded addresses.
4. Saga Pattern
Summary: Manages distributed transactions through a sequence of local transactions, where each service executes its transaction and publishes an event.
Pros:
Ensures data consistency without centralizing transaction management.
Supports long-running processes.
Cons:
Complexity in orchestrating and managing transactions.
Requires robust error handling mechanisms.
Use Cases:
Online Booking Systems: Manage complex transactions across services like flights, hotels, and car rentals.
E-commerce Checkout Processes: Handle the complete transaction lifecycle, from cart updates to payment and inventory adjustments.
5. Strangler Fig Pattern
Summary: Gradually replaces a monolithic application by routing some requests to new microservices while maintaining the old system.
Pros:
Reduces risk during migration.
Allows for incremental testing and rollout.
Cons:
Requires careful management to avoid confusion.
Possible architectural complexity during the transition.
Use Cases:
Financial Institutions: Transition from legacy systems to microservices to improve agility while ensuring service continuity.
Retail Companies: Gradually move from a monolithic inventory management system to microservices.
6. Event Sourcing Pattern
Summary: Captures all changes as events, allowing the system to reconstruct the current state from the event log.
Pros:
Provides a full audit trail of changes.
Facilitates eventual consistency and traceability.
Cons:
Can complicate data retrieval and management.
Requires careful management of event schemas.
Use Cases:
Retail Applications: Track inventory changes in real-time to ensure accurate stock levels and order processing.
Financial Transactions: Maintain a comprehensive log of all transactions for auditing purposes.
7. Database per Service Pattern
Summary: Each microservice manages its own database, promoting loose coupling and service independence.
Pros:
Enhances flexibility and scalability of services.
Reduces the risk of one service affecting another's data.
Cons:
Increased complexity in data management and consistency.
Requires coordination for data across services.
Use Cases:
Social Media Platforms: Different services (user profiles, posts, messaging) can manage their own data stores based on specific needs.
Insurance Companies: Separate databases for claims processing, customer data, and policy management.
8. Bulkhead Pattern
Summary: Isolates different parts of an application to prevent a failure in one part from affecting others.
Pros:
Improves resilience and stability of the application.
Cons:
May lead to resource underutilization.
Increased complexity in managing separate pools.
Use Cases:
Travel Booking Systems: Ensure that failures in flight booking do not impact hotel or car rental services.
Healthcare Applications: Isolate patient record services from appointment scheduling to maintain availability.
9. CQRS (Command Query Responsibility Segregation) Pattern
Summary: Separates read and write operations into different models to optimize performance and scalability.
Pros:
Improves performance by optimizing read and write operations.
Enhances security by separating read and write access.
Cons:
Increased complexity in managing two models.
Potential for data inconsistency if not managed correctly.
Use Cases:
E-commerce Platforms: Separate commands for placing orders and queries for retrieving product details.
Banking Systems: Use CQRS to handle transaction requests and balance inquiries efficiently.
10. Sidecar Pattern
Summary: Deploys a helper application alongside a main service to handle cross-cutting concerns such as logging, monitoring, or configuration.
Pros:
Promotes separation of concerns, simplifying service management.
Cons:
Increases deployment complexity and resource usage.
Use Cases:
Microservices in Kubernetes: Use a sidecar container for service mesh implementations, managing traffic and service discovery.
Logging and Monitoring: Attach a sidecar to manage logging for a microservice without modifying its core logic.