Overview
Direct Answer
Microservices is an architectural pattern that decomposes an application into small, independently deployable services, each owning a specific business capability and communicating via lightweight protocols. This approach contrasts with monolithic architectures by enabling teams to develop, deploy, and scale individual services without affecting others.
How It Works
Each service runs in its own process and communicates with others through well-defined APIs, typically REST or message brokers. Services maintain their own data stores and are organised around business domains rather than technical layers, allowing teams to select appropriate technologies and deployment strategies per service. Orchestration platforms manage service discovery, load balancing, and inter-service networking.
Why It Matters
Organisations adopt this pattern to accelerate feature delivery, improve system resilience, and enable independent team ownership. Services can be updated and deployed without full application redeployment, reducing release cycles and blast radius of failures, whilst supporting polyglot technology choices across the system.
Common Applications
E-commerce platforms use separate services for inventory, payments, and shipping. Streaming platforms decompose recommendation engines, content delivery, and user authentication as distinct services. Financial institutions employ this pattern for transaction processing, regulatory compliance, and customer-facing applications.
Key Considerations
Distributed complexity increases operational overhead, including network latency, eventual consistency challenges, and debugging difficulty. Teams require mature DevOps practices, monitoring infrastructure, and organisational alignment to manage the coordination burden effectively.
Cited Across coldai.org2 pages mention Microservices
Industry pages, services, technologies, capabilities, case studies and insights on coldai.org that reference Microservices — providing applied context for how the concept is used in client engagements.
Referenced By3 terms mention Microservices
Other entries in the wiki whose definition references Microservices — useful for understanding how this concept connects across Cloud Computing and adjacent domains.
More in Cloud Computing
AI Infrastructure
Service ModelsThe specialised hardware, software, and networking stack required to train and serve AI models at scale, including GPU clusters, high-bandwidth interconnects, and model serving frameworks.
Serverless Computing
Service ModelsA cloud execution model where the provider dynamically allocates resources, charging only for actual compute time used.
Auto-Scaling
InfrastructureAutomatically adjusting compute resources based on current demand to maintain performance and optimise costs.
Cloud Orchestration
Service ModelsThe automated arrangement, coordination, and management of complex cloud computing systems and services.
Region
InfrastructureA geographic area containing one or more data centres where cloud services are hosted.
GPU Cloud Computing
Service ModelsCloud infrastructure providing on-demand access to graphics processing units optimised for AI training and inference, enabling organisations to scale compute without capital investment.
Identity and Access Management
Strategy & EconomicsA framework for managing digital identities and controlling user access to resources and systems.
Container Orchestration
InfrastructureThe automated management of containerised application deployment, scaling, networking, and availability across clusters of machines, with Kubernetes as the dominant platform.