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Distributed application development is the practice of designing, building, and operating an application whose independent components run across networked computing resources and communicate through defined interfaces. Those components can be separated by process or machine without being spread across geographic regions. Microservices are a common way to build distributed applications, but they are not required.
What makes an application distributed?
A distributed application divides functionality among separate components that cooperate over a network. The Cloud Native Computing Foundation (CNCF) glossary describes it as an application whose functionality is broken into smaller independent parts: CNCF glossary: distributed application. In practice, components might run as separate processes on one machine, on several machines in one data center, or across multiple locations.
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The defining feature is the components’ separation and network communication—not a particular programming language, cloud provider, container platform, or geographic footprint. AWS likewise describes distributed architecture in terms of independent components cooperating across computing resources through a network: AWS: What is a distributed system?
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“Distributed application” is the broader term. Microservices are one architectural approach: an application is divided into services organized around functional areas, with services that can be developed and deployed independently. ISO/IEC 23167:2026 defines a microservice as an independently deployable artefact that implements a specific functional part of an application; the standard’s terminology does not make microservices synonymous with all distributed applications. See ISO/IEC 23167:2026.
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Cloud-native systems commonly use distributed components, often packaged as containers and run on a cluster, but those are implementation choices rather than requirements. Services may communicate using protocols such as HTTP/HTTPS, gRPC, WebSockets, or AMQP. The right choices depend on the system’s needs; none alone makes an application distributed. Microsoft’s overview explains these cloud-native and microservices patterns: Microsoft: What is cloud-native?
What distribution can make possible—and what it costs
Separating components can let a team scale a busy function without scaling the entire application, deploy one component without releasing every other component, or reduce dependence on a single computer. These are opportunities, not automatic results: they depend on sound boundaries, redundancy, and the ability to operate the system.
Distribution also makes ordinary interactions depend on networks and independently operating parts. A slow or unavailable service can delay its callers; data owned by separate services can make queries and cross-component transactions harder; and the system needs deliberate handling of secrets. AWS reliability guidance emphasizes that distributed systems must account for network latency and data loss: AWS Well-Architected Reliability Pillar. Google Cloud’s guidance covers latency, redundancy, failover, and data consistency across environments: Google Cloud: Distributed patterns. More components also mean more work to secure, observe, deploy, and maintain, as the CNCF glossary notes.
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Before choosing a distributed design, consider these questions:
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- Boundaries: Does each component have a clear responsibility, or do routine changes span many components?
- Scaling and releases: Is there a real need to scale or deploy some parts independently?
- Failure behavior: What should happen when a network request is delayed, lost, or answered after a timeout?
- Data ownership: Which component owns each record, and what consistency or transaction behavior does the application require?
- Operations and security: Can the team securely handle secrets and reliably observe, deploy, and maintain every component?
When a distributed approach is appropriate
Distribution is worth considering when independent scaling, release cadence, or organizational ownership solves a concrete problem and the team can manage the added operational and coordination work. A single deployable application may be a better fit when those benefits do not justify the extra network calls, data coordination, and service management. Neither approach is inherently obsolete or superior; fit depends on the application’s requirements and the team’s capacity.
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