In Cloud Native architecture, which approach enables independent development, deployment, and scaling of components?

In Cloud Native architecture, which approach enables independent development, deployment, and scaling of components?

• A. Monolithic architecture with tightly coupled components
• B. Microservices
• C. Batch processing systems
• D. Mainframe-style tightly integrated applications

Answer: (B)

Breaking an application into small, independently deployable services is the hallmark of microservices in Cloud Native. Each service handles a focused capability, owns its own data, and has its own lifecycle, so teams can develop, test, deploy, and scale it without coordinating with the rest of the system. This enables true independence in development and deployment, and allows horizontal scaling to be applied to only the parts that need it, improving agility and resilience. Cloud Native tooling, such as containers and Kubernetes, supports this by giving each service its own runtime environment and declarative deployment, while services communicate through lightweight APIs or events. Monolithic architecture bundles everything into a single deployable unit, making changes and scaling a whole application rather than individual components. Batch processing systems are geared toward processing large data jobs rather than enabling independent, continuously deployed services. Mainframe-style tightly integrated applications are also monolithic, lacking the modular independence that microservices provide.

Breaking an application into small, independently deployable services is the hallmark of microservices in Cloud Native. Each service handles a focused capability, owns its own data, and has its own lifecycle, so teams can develop, test, deploy, and scale it without coordinating with the rest of the system. This enables true independence in development and deployment, and allows horizontal scaling to be applied to only the parts that need it, improving agility and resilience. Cloud Native tooling, such as containers and Kubernetes, supports this by giving each service its own runtime environment and declarative deployment, while services communicate through lightweight APIs or events.

Monolithic architecture bundles everything into a single deployable unit, making changes and scaling a whole application rather than individual components. Batch processing systems are geared toward processing large data jobs rather than enabling independent, continuously deployed services. Mainframe-style tightly integrated applications are also monolithic, lacking the modular independence that microservices provide.