Microservice

Technical terms
About 1 min read

A cloud-native architecture that builds and deploys an application as a collection of independent, small-scale services centered around business capabilities.

Also known as
MicroserviceMSAMicroservice Architecture

Detailed explanation

Microservices is a method of designing a large application as a collection of small, loosely coupled services. Each service has its own database and business logic, communicating primarily via REST APIs or gRPC. Unlike monolithic architectures, specific features can be updated or scaled independently, resulting in excellent development agility and fault isolation. Recently, the 'Model-as-a-Service' pattern, which separates the inference environment of AI models into separate microservices for efficient resource deployment, has been spreading, and operational complexity is being addressed through service meshes and serverless technologies.

Why it matters in tool selection

When adopting AI tools or platforms, support for microservice architecture is directly linked to scalability. Because AI models consume higher computational resources than general business logic, they must be separated from the overall system and scaled independently to enable cost-efficient operation. Furthermore, allowing diverse technology stacks makes it easy to integrate the latest AI frameworks into existing systems.

Key checkpoints for tool adoption

  • Does it communicate flexibly with existing systems through standard APIs (REST, gRPC)?
  • Does it support independent deployment in container environments like Docker/Kubernetes?
  • Does it provide observability tools to monitor status across distributed services?
  • Does it have circuit breaker capabilities to prevent failures in a specific service from cascading to the entire system?

AI system application examples

In an e-commerce service, 'product search' is handled by a standard database, while 'image-based similar product recommendation' is structured as a separate microservice with allocated GPU resources. When user traffic spikes, scaling up only the recommendation engine service keeps the entire system stable.

Commonly confused terms

Monolithic

A structure where all features are bundled into a single codebase and process, meaning deployment and scaling must be done as a whole.

Modular Monolith

An intermediate step where deployment is done as a single unit but the internal code is strictly separated by service, avoiding the complexity of microservices while gaining structural benefits.

Related terms

Serverless