The most critical microservices patterns you must know
The most important microservices patterns you must know.
1 - Event Sourcing: This involves capturing all changes to the state of a system as a series of events. These events can be used to reconstruct the current state of the system at any point in time. This pattern is useful for systems with complex business logic that require auditability, traceability, or compliance.
2 - Event-Driven Architecture Pattern: Leverages events to trigger actions in your services, promoting loose coupling between services and enabling real-time responsiveness.
3 - Strangler Pattern: Facilitates the gradual replacement of a monolithic system with microservices, ensuring a smooth and risk-free transition.
4 - Bulkhead Pattern: Isolates microservices into separate partitions, preventing failures in one partition from affecting the entire system and enhancing system resilience.
5 - Circuit Breaker Pattern: Implements a fault-tolerant mechanism for microservices, preventing cascading failures by automatically detecting and isolating faulty services.?It monitors the availability of a service and, if it detects a failure, it can quickly isolate the problematic service and prevent other services from being affected.
6 - Retry Pattern: Enhances microservices' resilience by automatically retrying failed operations, increasing the chances of successful execution and minimizing transient issues.
7 - Saga Pattern: Manages long-running transactions that involve multiple microservices. It ensures that all services involved in a transaction are completed successfully or rolled back in case of failures, ensuring data consistency while maintaining the autonomy of your services.
8 - Saga Choreography: This pattern is similar to the Saga pattern, but instead of having a central orchestrator, each microservice involved in the transaction communicates directly with other services to coordinate the transaction.
9 - Sidecar Pattern: Involves deploying a separate process alongside a microservice, which handles certain tasks such as service discovery, load balancing, or communication with other services. This allows the microservice to focus on its core functionality, while the sidecar handles cross-cutting concerns.
10 - Service Discovery Pattern: Enables microservices to dynamically discover and communicate with each other, simplifying service orchestration and enhancing system scalability. (End-to-end process of registering services to a central place and reaching out to target service using service registry)
11 - Service Registry: Involves managing the locations of services in a distributed system. It maintains a list of all available services and their locations, which can be queried by other services to find and communicate with them.
12 - CQRS (Command Query Responsibility Segregation) Pattern: separates the read and write operations of a system. It uses separate models for reads and writes, which allows for the optimization and scalability of each. This pattern is particularly useful for systems with high read-and-write workloads. Read more ...
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13 - Service Mesh: provides a dedicated infrastructure layer for managing communication between microservices. It adds features such as load balancing, service discovery, and security to the network layer, which can be used by any microservice in the system.
14 - Anti-corruption layer: implements a fa?ade between new and legacy applications, to ensure that the design of a new application is not limited by dependencies on legacy systems.
15 - Database per Service: Involves using a separate database for each microservice. This ensures that each microservice has its own data store, which can be optimized for its specific needs. It also helps to prevent coupling between services.
16 - Load Balancing Pattern: Distributes incoming traffic among multiple instances of a microservice, improving system performance, resilience, and resource utilization.
17 - API Gateway Pattern: provides a single entry point to a microservices-based system. It acts as a reverse proxy and routes incoming requests to the appropriate microservice. It can also perform authentication, rate limiting, and other security-related tasks.
18 - Backends for Frontends Pattern (BFF): Creates dedicated backend services for each frontend, optimizing performance and user experience tailored to each platform.
19 - Aggregator Pattern: Aggregates requests to multiple individual microservices into a single request, reducing chattiness between consumers and services.
20 - Externalized Configuration: Allows storing configuration data outside of the application code, making it easier to manage configuration changes.
21 - The materialized view pattern: is generate prepopulated views over the data in one or more data stores when the data isn't ideally formatted for required query operations. helps support efficient querying and data extraction, and improves application performance. Read more ...
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