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Distributed application development is the practice of building an application from independent components that run on networked computing resources and cooperate through defined interfaces. Those components may run in separate processes, on different machines, or in different locations. Microservices are one common way to build a distributed application, but they are not required.
What makes an application distributed?
A distributed application divides its functionality among parts that operate independently and communicate over a network. The Cloud Native Computing Foundation describes it as an application whose functionality is broken into “multiple smaller independent parts.” The key distinction is that components execute separately and must communicate—not that they use a particular programming language, cloud provider, container platform, or geographic layout.
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The parts may run on different computers in one data center; they do not have to be spread across regions. Conversely, using cloud infrastructure does not by itself make an application distributed. AWS describes distributed architecture in terms of independent components working together across multiple computing resources and communicating through a network.
How distributed applications relate to microservices
“Distributed application” is the broader term. Microservices are one architectural style for organizing such an application, typically by assigning services to specific functional areas and allowing them to be developed or deployed independently. ISO/IEC 23167:2026 defines a microservice as an independently deployable artefact that implements a specific functional part of an application.
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Microservices may communicate through protocols such as HTTP/HTTPS, gRPC, WebSockets, or AMQP. These are implementation options, not requirements for every distributed application. A distributed system can use other component boundaries and communication mechanisms, and it need not be cloud-native or containerized. Cloud-native applications commonly use distributed components, but distribution is not limited to cloud-native environments.
What distribution can make possible—and what it costs
Separating components can let teams scale or deploy a busy or frequently changing part without changing the whole application. Multiple components or resources can also reduce reliance on a single computer. These are potential advantages, not automatic outcomes: they depend on good boundaries, sufficient redundancy, and the ability to operate the system effectively.
The trade-off is that communication crosses networks, which introduces latency and failure modes that do not arise in the same way inside a single process. A slow or unavailable service can delay its callers; a request may be lost or receive a response after the caller has timed out. Redundancy and failover can help, but require deliberate design. Distribution also adds operational overhead: more components to secure, observe, deploy, and maintain.
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How to judge whether a distributed design fits
Compare the additional independence a design could provide with the complexity it introduces. These questions help make that trade-off concrete:
- Component boundaries: Do parts have clear responsibilities, or do routine changes require coordinated edits across many components?
- Scaling and deployment: Is there a real need to scale or release one part separately?
- Failure behavior: What happens when a network request is slow, lost, or times out? Can a component fail without taking down the rest, and how will the system recover?
- Data ownership: Which component is responsible for each record? Do cross-component queries or transactions need stronger coordination than the design can provide?
- Security and operations: Can the team protect secrets, observe the components, deploy them safely, and maintain them over time?
A monolithic application is not inherently obsolete or inferior. If separate scaling, deployment, or organizational ownership does not justify the network, data, security, and operating costs, a simpler design may be a better fit.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Further reading
For a deeper technical treatment, Designing Data-Intensive Applications, 2nd Edition by Martin Kleppmann and Chris Riccomini covers distributed systems, microservices, and cloud computing. O’Reilly lists it as an intermediate-to-advanced book published in February 2026.
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