Here are some essential design patterns for Microservices:
Service Registry
A service registry functions akin to a navigational tool for your services, meticulously tracking all the services within your system, thus facilitating seamless discovery and interaction among them.
Upon initiation, every service within your system must register itself with the service registry, ensuring its presence is known. Conversely, upon cessation, services must be deregistered. Through this mechanism, other services can effortlessly query the service registry to pinpoint the services necessary for interaction. This dynamic capability fosters adaptability within your system, permitting services to enter and exit as needed without disrupting overall functionality.
Circuit Breaker
A circuit breaker serves as a sentinel against failures, encapsulating the logic to prevent recurrent failures. Various triggers, such as bugs within microservices, transient external system failures, or unforeseen operational anomalies, can trip the circuit breaker.
In the realm of microservices architecture, the circuit breaker pattern is deployed to monitor service interactions vigilantly. Should a service exhibit failure or sluggish response, the circuit breaker intervenes, halting further calls to the service to forestall system-wide failure. Upon service restoration, the circuit breaker resets, restoring normal operations.
API Gateway
Functioning as a singular entry point for all clients, an API gateway streamlines access into your system. Particularly advantageous in environments with multiple client apps (e.g., web and mobile), it consolidates disparate client APIs, simplifying client-side code.
The API gateway orchestrates requests in one of two manners: direct routing to pertinent services or composition, where data from multiple services is amalgamated and presented to the client. This approach not only streamlines client-side code but also enhances system efficiency and user experience.
Event-Driven Architecture
In an event-driven architecture, services emit events—records of actions—that other services can react to as needed. This decoupling of services fosters scalability and resilience.
This architecture cultivates systems resilient to failure as services operate autonomously. Should one service falter, others remain unaffected. Moreover, scalability is enhanced, enabling seamless integration of new services without disrupting existing ones.
Database per Service
Unlike traditional monolithic setups where a single database serves all services, microservices architecture advocates for each service having its own database.
This decentralized approach promotes service autonomy, shielding other services from the impact of failures. Additionally, it optimizes performance, as each database can be tailored to its service’s unique requirements.
Command Query Responsibility Segregation (CQRS)
CQRS delineates between read and write operations, advocating for separate data models. While implementation poses challenges, it significantly boosts system flexibility and performance when executed effectively.
Separating update and read operations enables tailored optimization, enhancing overall system efficiency.
Externalized Configuration
By separating configuration from code, the externalized configuration pattern enables dynamic adjustment of application behavior without necessitating code changes or system restarts.
In microservices architectures with multiple service instances running distinct configurations, this pattern streamlines management. However, robust configuration management systems are essential to prevent configuration drift.
Saga Pattern
The saga pattern ensures data consistency across diverse services in a microservices architecture by breaking transactions into localized transactions with compensating actions in case of failure.
This approach circumvents the limitations of traditional transaction management in loosely coupled, distributed systems.
Bulkhead Pattern
Inspired by ship design, the bulkhead pattern isolates application elements into compartments to prevent failure propagation.
By compartmentalizing components, this pattern fortifies system resilience, ensuring failures in one part do not disrupt other segments.
Backends for Frontends (BFF)
The BFF pattern advocates for tailored backend services for different client types, enhancing user experience and performance.
Effective implementation necessitates balancing customization and code reuse to mitigate code duplication.
About the Author
Photo Courtesy: Suresh Dodda
Result-oriented IT professional with over 20+ years of experience in designing and developing enterprise-level business applications for leading organizations, including ADP, National Grid, Mastercard, and Wipro Limited. Proven track record as a technical lead/manager (including project management) for global teams spread over multiple sites and locations in the USA and India with good interpersonal skills, an enthusiastic approach to problem-solving, and the ability to grasp new concepts quickly coupled with strong analytical and quantitative abilities make me an asset to any team.
Published by: Holy Minoza
