REST, acronym for REpresentational State Transfer, is one of the most common architectural pattern used in client-server applications. RESTful web services are meant to represent a resource in a way, that a client can consume and perform certain actions (like create or update a resource) on the resources. Although it is commonly implemented over HTTP, this is a protocol agnostic architecture.
Devised by Roy Fielding, REST has 6 guiding constrains that define a RESTful system and help achieve following properties from the system: performance, scalability, simplicity, modifiability, visibility, portability and reliability.
Constraints
1. Client-Server
It is based on the principle of Separation of concerns. By separating the user interface concerns from the data storage concerns, we improve the portability of the user interface across multiple platforms and improve scalability by simplifying the server components. Perhaps most significant to the Web, however, is that the separation allows the components to evolve independently, thus supporting the Internet-scale requirement of multiple organizational domains.
2. Stateless
Communication must be stateless in nature, such that each request from client to server must contain all of the information necessary to understand the request, and cannot take advantage of any stored context on the server. Session state is therefore kept entirely on the client.
This constraint induces the properties of visibility, reliability, and scalability. Visibility is improved because a monitoring system does not have to look beyond a single request datum in order to determine the full nature of the request. Reliability is improved because it eases the task of recovering from partial failures. Scalability is improved because not having to store state between requests allows the server component to quickly free resources, and further simplifies implementation because the server doesn’t have to manage resource usage across requests.
Like most architectural choices, the stateless constraint reflects a design trade-off. The disadvantage is that it may decrease network performance by increasing the repetitive data (per-interaction overhead) sent in a series of requests, since that data cannot be left on the server in a shared context. In addition, placing the application state on the client-side reduces the server’s control over consistent application behavior, since the application becomes dependent on the correct implementation of semantics across multiple client versions.
3. Cache
Cache constraint is required in order to improve network efficiency. The data within a response to a request can be implicitly or explicitly labeled as cacheable or non-cacheable. If a response is cacheable, then a client cache is given the right to reuse that response data for later, equivalent requests.
The advantage of adding cache constraints is that they have the potential to partially or completely eliminate some interactions, improving efficiency, scalability, and user-perceived performance by reducing the average latency of a series of interactions. The trade-off, however, is that a cache can decrease reliability if stale data within the cache differs significantly from the data that would have been obtained had the request been sent directly to the server.
4. Uniform Interface
The central feature that distinguishes the REST architectural style from other network-based styles is its emphasis on a uniform interface between components. By applying the software engineering principle of generality to the component interface, the overall system architecture is simplified and the visibility of interactions is improved. Implementations are decoupled from the services they provide, which encourages independent evolvability. The trade-off, though, is that a uniform interface degrades efficiency, since information is transferred in a standardized form rather than one which is specific to an application’s needs. The REST interface is designed to be efficient for large-grain hypermedia data transfer, optimizing for the common case of the Web, but resulting in an interface that is not optimal for other forms of architectural interaction.
In order to obtain a uniform interface, multiple architectural constraints are needed to guide the behavior of components. REST is defined by four interface constraints: identification of resources; manipulation of resources through representations; self-descriptive messages; and, hypermedia as the engine of application state.
5. Layered System
This constraint is added in order to further improve behavior for Internet-scale requirements. The layered system style allows an architecture to be composed of hierarchical layers by constraining component behavior such that each component cannot “see” beyond the immediate layer with which they are interacting. By restricting knowledge of the system to a single layer, we place a bound on the overall system complexity and promote substrate independence. Layers can be used to encapsulate legacy services and to protect new services from legacy clients, simplifying components by moving infrequently used functionality to a shared intermediary. Intermediaries can also be used to improve system scalability by enabling load balancing of services across multiple networks and processors.
The primary disadvantage of layered systems is that they add overhead and latency to the processing of data, reducing user-perceived performance. For a network-based system that supports cache constraints, this can be offset by the benefits of shared caching at intermediaries. Placing shared caches at the boundaries of an organizational domain can result in significant performance benefits. Such layers also allow security policies to be enforced on data crossing the organizational boundary, as is required by firewalls.
The combination of layered system and uniform interface constraints induces architectural properties similar to those of the uniform pipe-and-filter style. Although REST interaction is two-way, the large-grain data flows of hypermedia interaction can each be processed like a data-flow network, with filter components selectively applied to the data stream in order to transform the content as it passes. Within REST, intermediary components can actively transform the content of messages because the messages are self-descriptive and their semantics are visible to intermediaries.
6. Code-On-Demand
REST allows client functionality to be extended by downloading and executing code in the form of applets or scripts. This simplifies clients by reducing the number of features required to be pre-implemented. Allowing features to be downloaded after deployment improves system extensibility. However, it also reduces visibility, and thus is only an optional constraint within REST.
The notion of an optional constraint may seem like an oxymoron. However, it does have a purpose in the architectural design of a system that encompasses multiple organizational boundaries. It means that the architecture only gains the benefit (and suffers the disadvantages) of the optional constraints when they are known to be in effect for some realm of the overall system. For example, if all of the client software within an organization is known to support Java applets, then services within that organization can be constructed such that they gain the benefit of enhanced functionality via downloadable Java classes. At the same time, however, the organization’s firewall may prevent the transfer of Java applets from external sources, and thus to the rest of the Web it will appear as if those clients do not support code-on-demand. An optional constraint allows us to design an architecture that supports the desired behavior in the general case, but with the understanding that it may be disabled within some contexts.