Published by Sascha Neumeier
Last updated on July 24, 2026
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7 minute read
Representational State Transfer, or REST for short, gets thrown around in IT admin circles constantly. Ask five people to define it precisely though, and you'll probably get five slightly different answers. Here's the thing: REST is an architectural style. Not a protocol, not a piece of software, not something you install. Roy Fielding introduced it in his 2000 doctoral dissertation, where he laid out a set of constraints for building distributed hypermedia systems that could actually scale across the World Wide Web without collapsing under their own weight.
What Is REST, Exactly?
At its core, REST defines a set of constraints for creating web services, constraints that let computer systems talk to each other over the internet. Services following these rules are called RESTful web services, and they let client systems access and manipulate representations of web resources through a uniform, predefined set of operations. That's a mouthful. Let's break it down into something you can actually use on a Monday morning.
A REST API, also called a RESTful API, is simply a programming interface (an application programming interface) built on REST principles. String together a group of related RESTful web services and you've got yourself a RESTful API. REST doesn't bolt on an extra messaging layer the way SOAP does, and that's really the whole point: it's lighter, easier to reason about, less to go wrong.
The Constraints Behind REST
REST relies on client-server architecture. The client sends a request, the server sends a response, and the two sides stay cleanly separated. The server doesn't need to know anything about the user interface. The client doesn't care how data storage or business logic gets handled on the other end. This separation of concerns is a big reason REST APIs travel so well across different platforms and programming languages.
REST is stateless, too. Every single request has to carry all the information the server needs to process it. No session state gets stored on the server between calls. Sounds inconvenient at first, right? But that's actually where the scalability comes from. Since there's no session context sitting in memory, requests can get routed through a load balancer to whichever server happens to be free, and none of them need to know what happened on the last call. This same statelessness is part of why REST scales so well into microservices architectures, where you might have dozens of small services being swapped out, restarted, or replicated without anything breaking.
Caching is baked in as well. Responses get marked cacheable or non-cacheable through HTTP headers, so clients can reuse data instead of hammering the server with the same request over and over. Then there's the uniform interface, probably the constraint that defines REST more than any other. It covers four ideas: identification of resources through a uniform resource identifier (URI), manipulation of resources through representations (you're not touching the resource directly, you're sending a representation of it, usually JSON or XML), self-descriptive messages carrying enough metadata to stand on their own, and, where it's implemented, HATEOAS. Hypermedia as the engine of application state. The response itself can contain links telling you what to do next.
Two more constraints round the picture out. A layered system, meaning proxies, gateways, or load balancers can sit between client and server without either side even noticing. And the optional code on demand constraint, where a server can temporarily extend what the client can do, an idea that traces back to the old applets era of web development and barely shows up in modern REST APIs anymore.
HTTP Methods: How a REST Request Actually Works
Now for the part every IT administrator actually cares about day to day: how does a request work in practice? Requests typically travel over the Hypertext Transfer Protocol, combining a URI with one of the standard HTTP verbs. GET retrieves a resource representation without touching anything. POST creates a new subordinate resource. PUT updates an existing resource in full, start to finish. DELETE removes a resource. PATCH does a partial update, just the piece that changed. For anything beyond a plain GET, so POST, PUT, DELETE, and PATCH, authentication kicks in, usually via an API key sitting in the request headers.
If you're the one responsible for keeping dozens of endpoints, servers, and services talking to each other without downtime, you already know the theory only gets you so far. What actually matters is visibility into all that traffic. PRTG gives you exactly that: one dashboard showing the health of your entire infrastructure, from web servers to the APIs running on top of them. See it for yourself with a free 30 day trial:
REST vs. SOAP
REST versus SOAP is where things get genuinely practical. SOAP, Simple Object Access Protocol, is an XML based messaging protocol specification that leans on WSDL to describe how client and server talk to one another. REST, on the other hand, just uses JSON or XML to pass messages back and forth. SOAP invokes services through remote procedure calls. REST just sends a request to a URI, plain and simple. SOAP responses aren't exactly human readable; REST responses in JSON or XML usually are. SOAP can also travel over several protocols, including SMTP or FTP, while REST sticks to HTTP.
That narrower focus is exactly why REST tends to outperform SOAP. It's essentially HTTP without the extra baggage, so if your service already runs over HTTP anyway, there's not much left to trim. Encoding representations directly in JSON instead of XML shaves off extra bytes on every single call. Doesn't sound like much until you're dealing with thousands of endpoints and millions of requests a day, and suddenly it adds up fast.
REST, GraphQL and What Comes Next
Worth noting: REST isn't the only game in town anymore. GraphQL has picked up a real following for cases where clients want to request exactly the data they need in a single call, instead of pinging several fixed endpoints one after another. Both approaches care about interoperability at the end of the day. Picking one over the other usually comes down to how your data is shaped and how your teams actually like to query it.
None of this is theoretical if you're the one maintaining the web resources, endpoints, and hidden API traffic keeping a modern IT environment running. Before something breaks silently on you, you want a system watching every state transition across your network. Try PRTG free for 30 days and stop guessing what your infrastructure is actually doing.
How PRTG Uses REST Principles Too
Under the hood, PRTG Network Monitor runs its own HTTP API, so admins can pull monitoring data or automate routine tasks without opening the web interface every single time. If REST concepts like GET requests and JSON responses already feel familiar from reading this far, you'll feel right at home working with it.
The Bottom Line
REST has stuck around for more than two decades now, and that's not an accident. It solved a real problem: how to build interoperable, scalable web services without dragging along the overhead of older messaging protocols. Once you've got the six constraints down, statelessness, client-server architecture, cacheable responses, a uniform interface, a layered system, and optional code on demand, the rest of the terminology around REST APIs, endpoints, and HTTP verbs falls into place pretty quickly. Want to see what a well-documented REST API looks like in practice? The PRTG API v2 overview walks through real endpoints you can try yourself!
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