AiVibeMicroservices Architecture
Microservices architecture is a software design approach that builds an application from small, independently deployable services, each responsible for one business capability and communicating with others over APIs or events.
Microservices architecture structures an application as a set of small, independently deployable services, each owning a specific business capability and usually its own data store. Services communicate over the network through APIs, such as HTTP/REST or gRPC, or asynchronously through message queues and event streams. Each service can be developed, deployed and scaled by a separate team without redeploying the whole application, in contrast to a monolith that is built and released as a single unit.
Organisations adopt microservices to release changes faster, scale busy components independently and use different technologies where they fit. The style is common in cloud-native platforms, e-commerce, banking and industrial software, where separate services may handle device data ingestion, analytics, alerting and user interfaces. Containers and Kubernetes are the usual runtime.
Distribution brings costs: network latency, partial failures, data consistency across services, versioned APIs and more complex testing and monitoring. Patterns such as API gateways, circuit breakers, distributed tracing and event-driven communication address these issues. Many teams start with a well-structured monolith and extract services only when team size or scaling needs justify the overhead.
Key points
- Each service owns one capability and ideally its own data store
- Services communicate via APIs such as REST or gRPC, or through events and queues
- Enables independent deployment and scaling of individual components
- Adds network latency, partial failures and harder testing compared with a monolith
Where AiVibe comes in
AiVibe Software Services delivers cloud solutions on AWS, Microsoft Azure, Google Cloud or on-premise, together with cloud security, legacy modernisation, data analytics and AI and machine learning services.
Related terms
- API GatewayCloud & AI Infrastructure
- Service MeshCloud & AI Infrastructure
- Software ContainerCloud & AI Infrastructure
- KubernetesCloud & AI Infrastructure
- Event StreamingCloud & AI Infrastructure
- ObservabilityCloud & AI Infrastructure