How do you determine the appropriate granularity of a microservice?

Here's a concise checklist to determine if a microservice is too granular or too coarse: Responsibility: Handles more than one business capability? (Too coarse) Data Dependency: Requires frequent synchronous calls to other services for data? (Too granular) Deployment: Changes require coordinating deployments of other services? (Too coarse) Team: Single team cannot manage it effectively? (Too coarse) Reusability: Service logic duplicated across services? (Too granular) A service likely needs adjustment if it doesn't align well with these points.

The granularity of a service is often ambiguous and has different interpretation. But there is no doubt that the granularity affects the architecture of a system. As we come to service oriented development from object oriented and passing component oriented, the granularity is believed to increase. The services provide access to application where each application is composed of various component services. It is difficult to define granularity in terms of number because the concepts defining granularity are vague and subjective in nature. If we choose an activity supported by the service to determine its granularity then we cannot have one fixed value instead a hierarchical list of answers. My key believe is to focus on composability.

1: Apply Domain-Driven Design (DDD) principles. Ensure adherence to the Single Responsibility Principle (SRP). 2: Align microservices with specific business capabilities. 3: Consider trade-offs between fine-grained and coarse-grained microservices. 4: Evaluate communication overhead between microservices. 5: Assess deployment and scaling requirements. Continuously refine granularity based on feedback and evolving needs.

Domain-Driven Design (DDD): Identify bounded contexts to define microservice boundaries. Single Responsibility Principle (SRP): Ensure each microservice focuses on a single business function, promoting high cohesion and low coupling. Scalability: Design microservices for independent scaling based on demand. Team Structure: Align microservices with technological needs and team capabilities, allowing for technology diversity and team autonomy. Data Management: Each microservice should own its data to ensure independence . Performance: Balance granularity with network overhead to optimize system performance. Iterative Refinement: Adjust microservice boundaries based on real-world performance and evolving requirements.

Like engineering any complex system, designing microservices requires finding optimal modularization to balance opposing needs - a task akin to tuning a guitar to create beautiful music instead of awkward noise.

Applying domain driven design (DDD) is the key for microservice based architecture. This would define domain boundaries, based on business domain. In general services within a bounded context can be tightly coupled (eg: HTTP based services) and services interaction across domain boundaries can be loosly coupled (eg: Asynchronous services - pub/sub, point to point). This will ensure the different business functionalities are functionally and operationally separate and has less impact on each other's availability

Like constructing a building, microservices take shape optimally when founded on bedrock understanding of core domains rather than arbitrarily dividing functionality.

The first thing is to properly identifying the domain models. Once we identify the domain models half of the task is done. The next thing to be done is to divide the problem space into Bounded Contexts, which is specific to a problem. Each bounded context need to be defined with clear boundaries and responsibilities, and the communication between contexts should be well-defined.

Dise?ar microservicios con alta cohesión, bajo acoplamiento y baja complejidad implica considerar varios aspectos clave: Afinidad de Funcionalidades: Agrupa tareas relacionadas para cohesión y evita mezclar funciones no afines para reducir complejidad. Event-Driven Architecture (EDA): Implementa EDA para reaccionar a eventos sin conocer emisores, mejorando escalabilidad y reduciendo acoplamiento. Versionado y Evolución Independiente: Dise?a para permitir evolución independiente, facilitando actualizaciones sin afectar otros servicios. Buenas Prácticas: Aplica interfaz clara, división por capas, descomposición jerárquica, pruebas sólidas y documentación clara para lograr microservicios robustos y manejables.

Analysis Criteria: Cohesion: High cohesion ensures that a microservice encapsulates related and consistent functionality. Coupling: Low coupling indicates that microservices are independent and loosely connected, enabling easier maintenance and scalability. In our fraud detection system implementation, we aimed for low coupling between the microservices responsible for data ingestion, pattern recognition, and alert generation, allowing each component to evolve independently. Complexity: Microservices should have low complexity, focusing on simple and easy-to-understand functionality.

The level of granularity of a service in terms of dependencies and functionality is the decision variable for adopting microservices. The question needs to be, following DDD practices what level of functional granularity needs to be in a service. Based on the level ascertained in DDD microservices, modular monolith services or monolith services could be considered.

Desde mi experiencia, a?ado aspectos esenciales al determinar la granularidad de un microservicio: Evaluación Continua: Realiza revisiones periódicas para ajustar a las necesidades cambiantes del negocio y tecnológicas. Impacto en Escalabilidad: Considera cómo afectará la escalabilidad. Un dise?o equilibrado garantiza escalabilidad eficiente. Acoplamiento y Cohesión: Busca equilibrio entre acoplamiento y cohesión para evitar complejidades innecesarias. Ciclo de Vida Independiente: Asegura que cada microservicio tenga un ciclo de vida independiente para actualizaciones sin afectar otros. Requisitos de Negocio: Alínea la granularidad con requisitos del negocio, representando unidades coherentes y valiosas.