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Representational State Transfer (REST)

This chapter introduces and elaborates the Representational State Transfer (REST) architectural style for distributed hypermedia systems, describing the software engineering principles guiding REST and the interaction constraints chosen to retain those principles, while contrasting them to the constraints of other architectural styles. REST is a hybrid style derived from several of the network-based architectural styles described in Chapter 3 and combined with additional constraints that define a uniform connector interface. The software architecture framework of Chapter 1 is used to define the architectural elements of REST and examine sample process, connector, and data views of prototypical architectures.

5.1 Deriving REST

The design rationale behind the Web architecture can be described by an architectural style consisting of the set of constraints applied to elements within the architecture. By examining the impact of each constraint as it is added to the evolving style, we can identify the properties induced by the Web's constraints. Additional constraints can then be applied to form a new architectural style that better reflects the desired properties of a modern Web architecture. This section provides a general overview of REST by walking through the process of deriving it as an architectural style. Later sections will describe in more detail the specific constraints that compose the REST style.

5.1.1 Starting with the Null Style

There are two common perspectives on the process of architectural design, whether it be for buildings or for software. The first is that a designer starts with nothing--a blank slate, whiteboard, or drawing board--and builds-up an architecture from familiar components until it satisfies the needs of the intended system. The second is that a designer starts with the system needs as a whole, without constraints, and then incrementally identifies and applies constraints to elements of the system in order to differentiate the design space and allow the forces that influence system behavior to flow naturally, in harmony with the system. Where the first emphasizes creativity and unbounded vision, the second emphasizes restraint and understanding of the system context. REST has been developed using the latter process. Figures 5-1 through 5-8 depict this graphically in terms of how the applied constraints would differentiate the process view of an architecture as the incremental set of constraints is applied.

The Null style ( Figure 5-1 ) is simply an empty set of constraints. From an architectural perspective, the null style describes a system in which there are no distinguished boundaries between components. It is the starting point for our description of REST.

5.1.2 Client-Server

The first constraints added to our hybrid style are those of the client-server architectural style ( Figure 5-2 ), described in Section 3.4.1 . Separation of concerns is the principle behind the client-server constraints. 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.

5.1.3 Stateless

We next add a constraint to the client-server interaction: communication must be stateless in nature, as in the client-stateless-server (CSS) style of Section 3.4.3 ( Figure 5-3 ), 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 [ 133 ]. 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.

5.1.4 Cache

In order to improve network efficiency, we add cache constraints to form the client-cache-stateless-server style of Section 3.4.4 ( Figure 5-4 ). Cache constraints require that the data within a response to a request 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.

The early Web architecture, as portrayed by the diagram in Figure 5-5 [ 11 ], was defined by the client-cache-stateless-server set of constraints. That is, the design rationale presented for the Web architecture prior to 1994 focused on stateless client-server interaction for the exchange of static documents over the Internet. The protocols for communicating interactions had rudimentary support for non-shared caches, but did not constrain the interface to a consistent set of semantics for all resources. Instead, the Web relied on the use of a common client-server implementation library (CERN libwww) to maintain consistency across Web applications.

Developers of Web implementations had already exceeded the early design. In addition to static documents, requests could identify services that dynamically generated responses, such as image-maps [Kevin Hughes] and server-side scripts [Rob McCool]. Work had also begun on intermediary components, in the form of proxies [ 79 ] and shared caches [ 59 ], but extensions to the protocols were needed in order for them to communicate reliably. The following sections describe the constraints added to the Web's architectural style in order to guide the extensions that form the modern Web architecture.

5.1.5 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 ( Figure 5-6 ). 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. These constraints will be discussed in Section 5.2 .

5.1.6 Layered System

In order to further improve behavior for Internet-scale requirements, we add layered system constraints ( Figure 5-7 ). As described in Section 3.4.2 , 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 [ 32 ]. 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 [ 136 ]. Such layers also allow security policies to be enforced on data crossing the organizational boundary, as is required by firewalls [ 79 ].

The combination of layered system and uniform interface constraints induces architectural properties similar to those of the uniform pipe-and-filter style ( Section 3.2.2 ). 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 [ 26 ]. Within REST, intermediary components can actively transform the content of messages because the messages are self-descriptive and their semantics are visible to intermediaries.

5.1.7 Code-On-Demand

The final addition to our constraint set for REST comes from the code-on-demand style of Section 3.5.3 ( Figure 5-8 ). 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 [ 45 ], 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.

5.1.8 Style Derivation Summary

REST consists of a set of architectural constraints chosen for the properties they induce on candidate architectures. Although each of these constraints can be considered in isolation, describing them in terms of their derivation from common architectural styles makes it easier to understand the rationale behind their selection. Figure 5-9 depicts the derivation of REST's constraints graphically in terms of the network-based architectural styles examined in Chapter 3.

5.2 REST Architectural Elements

The Representational State Transfer (REST) style is an abstraction of the architectural elements within a distributed hypermedia system. REST ignores the details of component implementation and protocol syntax in order to focus on the roles of components, the constraints upon their interaction with other components, and their interpretation of significant data elements. It encompasses the fundamental constraints upon components, connectors, and data that define the basis of the Web architecture, and thus the essence of its behavior as a network-based application.

5.2.1 Data Elements

Unlike the distributed object style [ 31 ], where all data is encapsulated within and hidden by the processing components, the nature and state of an architecture's data elements is a key aspect of REST. The rationale for this design can be seen in the nature of distributed hypermedia. When a link is selected, information needs to be moved from the location where it is stored to the location where it will be used by, in most cases, a human reader. This is unlike many other distributed processing paradigms [ 6 , 50 ], where it is possible, and usually more efficient, to move the "processing agent" (e.g., mobile code, stored procedure, search expression, etc.) to the data rather than move the data to the processor.

A distributed hypermedia architect has only three fundamental options: 1) render the data where it is located and send a fixed-format image to the recipient; 2) encapsulate the data with a rendering engine and send both to the recipient; or, 3) send the raw data to the recipient along with metadata that describes the data type, so that the recipient can choose their own rendering engine.

Each option has its advantages and disadvantages. Option 1, the traditional client-server style [ 31 ], allows all information about the true nature of the data to remain hidden within the sender, preventing assumptions from being made about the data structure and making client implementation easier. However, it also severely restricts the functionality of the recipient and places most of the processing load on the sender, leading to scalability problems. Option 2, the mobile object style [ 50 ], provides information hiding while enabling specialized processing of the data via its unique rendering engine, but limits the functionality of the recipient to what is anticipated within that engine and may vastly increase the amount of data transferred. Option 3 allows the sender to remain simple and scalable while minimizing the bytes transferred, but loses the advantages of information hiding and requires that both sender and recipient understand the same data types.

REST provides a hybrid of all three options by focusing on a shared understanding of data types with metadata, but limiting the scope of what is revealed to a standardized interface. REST components communicate by transferring a representation of a resource in a format matching one of an evolving set of standard data types, selected dynamically based on the capabilities or desires of the recipient and the nature of the resource. Whether the representation is in the same format as the raw source, or is derived from the source, remains hidden behind the interface. The benefits of the mobile object style are approximated by sending a representation that consists of instructions in the standard data format of an encapsulated rendering engine (e.g., Java [ 45 ]). REST therefore gains the separation of concerns of the client-server style without the server scalability problem, allows information hiding through a generic interface to enable encapsulation and evolution of services, and provides for a diverse set of functionality through downloadable feature-engines.

REST's data elements are summarized in Table 5-1 . Resources and Resource Identifiers

The key abstraction of information in REST is a resource . Any information that can be named can be a resource: a document or image, a temporal service (e.g. "today's weather in Los Angeles"), a collection of other resources, a non-virtual object (e.g. a person), and so on. In other words, any concept that might be the target of an author's hypertext reference must fit within the definition of a resource. A resource is a conceptual mapping to a set of entities, not the entity that corresponds to the mapping at any particular point in time.

More precisely, a resource R is a temporally varying membership function M R (t) , which for time t maps to a set of entities, or values, which are equivalent. The values in the set may be resource representations and/or resource identifiers . A resource can map to the empty set, which allows references to be made to a concept before any realization of that concept exists -- a notion that was foreign to most hypertext systems prior to the Web [ 61 ]. Some resources are static in the sense that, when examined at any time after their creation, they always correspond to the same value set. Others have a high degree of variance in their value over time. The only thing that is required to be static for a resource is the semantics of the mapping, since the semantics is what distinguishes one resource from another.

For example, the "authors' preferred version" of an academic paper is a mapping whose value changes over time, whereas a mapping to "the paper published in the proceedings of conference X" is static. These are two distinct resources, even if they both map to the same value at some point in time. The distinction is necessary so that both resources can be identified and referenced independently. A similar example from software engineering is the separate identification of a version-controlled source code file when referring to the "latest revision", "revision number 1.2.7", or "revision included with the Orange release."

This abstract definition of a resource enables key features of the Web architecture. First, it provides generality by encompassing many sources of information without artificially distinguishing them by type or implementation. Second, it allows late binding of the reference to a representation, enabling content negotiation to take place based on characteristics of the request. Finally, it allows an author to reference the concept rather than some singular representation of that concept, thus removing the need to change all existing links whenever the representation changes (assuming the author used the right identifier).

REST uses a resource identifier to identify the particular resource involved in an interaction between components. REST connectors provide a generic interface for accessing and manipulating the value set of a resource, regardless of how the membership function is defined or the type of software that is handling the request. The naming authority that assigned the resource identifier, making it possible to reference the resource, is responsible for maintaining the semantic validity of the mapping over time (i.e., ensuring that the membership function does not change).

Traditional hypertext systems [ 61 ], which typically operate in a closed or local environment, use unique node or document identifiers that change every time the information changes, relying on link servers to maintain references separately from the content [ 135 ]. Since centralized link servers are an anathema to the immense scale and multi-organizational domain requirements of the Web, REST relies instead on the author choosing a resource identifier that best fits the nature of the concept being identified. Naturally, the quality of an identifier is often proportional to the amount of money spent to retain its validity, which leads to broken links as ephemeral (or poorly supported) information moves or disappears over time. Representations

REST components perform actions on a resource by using a representation to capture the current or intended state of that resource and transferring that representation between components. A representation is a sequence of bytes, plus representation metadata to describe those bytes. Other commonly used but less precise names for a representation include: document, file, and HTTP message entity, instance, or variant.

A representation consists of data, metadata describing the data, and, on occasion, metadata to describe the metadata (usually for the purpose of verifying message integrity). Metadata is in the form of name-value pairs, where the name corresponds to a standard that defines the value's structure and semantics. Response messages may include both representation metadata and resource metadata: information about the resource that is not specific to the supplied representation.

Control data defines the purpose of a message between components, such as the action being requested or the meaning of a response. It is also used to parameterize requests and override the default behavior of some connecting elements. For example, cache behavior can be modified by control data included in the request or response message.

Depending on the message control data, a given representation may indicate the current state of the requested resource, the desired state for the requested resource, or the value of some other resource, such as a representation of the input data within a client's query form, or a representation of some error condition for a response. For example, remote authoring of a resource requires that the author send a representation to the server, thus establishing a value for that resource that can be retrieved by later requests. If the value set of a resource at a given time consists of multiple representations, content negotiation may be used to select the best representation for inclusion in a given message.

The data format of a representation is known as a media type [ 48 ]. A representation can be included in a message and processed by the recipient according to the control data of the message and the nature of the media type. Some media types are intended for automated processing, some are intended to be rendered for viewing by a user, and a few are capable of both. Composite media types can be used to enclose multiple representations in a single message.

The design of a media type can directly impact the user-perceived performance of a distributed hypermedia system. Any data that must be received before the recipient can begin rendering the representation adds to the latency of an interaction. A data format that places the most important rendering information up front, such that the initial information can be incrementally rendered while the rest of the information is being received, results in much better user-perceived performance than a data format that must be entirely received before rendering can begin.

For example, a Web browser that can incrementally render a large HTML document while it is being received provides significantly better user-perceived performance than one that waits until the entire document is completely received prior to rendering, even though the network performance is the same. Note that the rendering ability of a representation can also be impacted by the choice of content. If the dimensions of dynamically-sized tables and embedded objects must be determined before they can be rendered, their occurrence within the viewing area of a hypermedia page will increase its latency.

5.2.2 Connectors

REST uses various connector types, summarized in Table 5-2 , to encapsulate the activities of accessing resources and transferring resource representations. The connectors present an abstract interface for component communication, enhancing simplicity by providing a clean separation of concerns and hiding the underlying implementation of resources and communication mechanisms. The generality of the interface also enables substitutability: if the users' only access to the system is via an abstract interface, the implementation can be replaced without impacting the users. Since a connector manages network communication for a component, information can be shared across multiple interactions in order to improve efficiency and responsiveness.

All REST interactions are stateless. That is, each request contains all of the information necessary for a connector to understand the request, independent of any requests that may have preceded it. This restriction accomplishes four functions: 1) it removes any need for the connectors to retain application state between requests, thus reducing consumption of physical resources and improving scalability; 2) it allows interactions to be processed in parallel without requiring that the processing mechanism understand the interaction semantics; 3) it allows an intermediary to view and understand a request in isolation, which may be necessary when services are dynamically rearranged; and, 4) it forces all of the information that might factor into the reusability of a cached response to be present in each request.

The connector interface is similar to procedural invocation, but with important differences in the passing of parameters and results. The in-parameters consist of request control data, a resource identifier indicating the target of the request, and an optional representation. The out-parameters consist of response control data, optional resource metadata, and an optional representation. From an abstract viewpoint the invocation is synchronous, but both in and out-parameters can be passed as data streams. In other words, processing can be invoked before the value of the parameters is completely known, thus avoiding the latency of batch processing large data transfers.

The primary connector types are client and server. The essential difference between the two is that a client initiates communication by making a request, whereas a server listens for connections and responds to requests in order to supply access to its services. A component may include both client and server connectors.

A third connector type, the cache connector, can be located on the interface to a client or server connector in order to save cacheable responses to current interactions so that they can be reused for later requested interactions. A cache may be used by a client to avoid repetition of network communication, or by a server to avoid repeating the process of generating a response, with both cases serving to reduce interaction latency. A cache is typically implemented within the address space of the connector that uses it.

Some cache connectors are shared, meaning that its cached responses may be used in answer to a client other than the one for which the response was originally obtained. Shared caching can be effective at reducing the impact of "flash crowds" on the load of a popular server, particularly when the caching is arranged hierarchically to cover large groups of users, such as those within a company's intranet, the customers of an Internet service provider, or Universities sharing a national network backbone. However, shared caching can also lead to errors if the cached response does not match what would have been obtained by a new request. REST attempts to balance the desire for transparency in cache behavior with the desire for efficient use of the network, rather than assuming that absolute transparency is always required.

A cache is able to determine the cacheability of a response because the interface is generic rather than specific to each resource. By default, the response to a retrieval request is cacheable and the responses to other requests are non-cacheable. If some form of user authentication is part of the request, or if the response indicates that it should not be shared, then the response is only cacheable by a non-shared cache. A component can override these defaults by including control data that marks the interaction as cacheable, non-cacheable or cacheable for only a limited time.

A resolver translates partial or complete resource identifiers into the network address information needed to establish an inter-component connection. For example, most URI include a DNS hostname as the mechanism for identifying the naming authority for the resource. In order to initiate a request, a Web browser will extract the hostname from the URI and make use of a DNS resolver to obtain the Internet Protocol address for that authority. Another example is that some identification schemes (e.g., URN [ 124 ]) require an intermediary to translate a permanent identifier to a more transient address in order to access the identified resource. Use of one or more intermediate resolvers can improve the longevity of resource references through indirection, though doing so adds to the request latency.

The final form of connector type is a tunnel, which simply relays communication across a connection boundary, such as a firewall or lower-level network gateway. The only reason it is modeled as part of REST and not abstracted away as part of the network infrastructure is that some REST components may dynamically switch from active component behavior to that of a tunnel. The primary example is an HTTP proxy that switches to a tunnel in response to a CONNECT method request [ 71 ], thus allowing its client to directly communicate with a remote server using a different protocol, such as TLS, that doesn't allow proxies. The tunnel disappears when both ends terminate their communication.

5.2.3 Components

REST components, summarized in Table 5-3 , are typed by their roles in an overall application action.

A user agent uses a client connector to initiate a request and becomes the ultimate recipient of the response. The most common example is a Web browser, which provides access to information services and renders service responses according to the application needs.

An origin server uses a server connector to govern the namespace for a requested resource. It is the definitive source for representations of its resources and must be the ultimate recipient of any request that intends to modify the value of its resources. Each origin server provides a generic interface to its services as a resource hierarchy. The resource implementation details are hidden behind the interface.

Intermediary components act as both a client and a server in order to forward, with possible translation, requests and responses. A proxy component is an intermediary selected by a client to provide interface encapsulation of other services, data translation, performance enhancement, or security protection. A gateway (a.k.a., reverse proxy) component is an intermediary imposed by the network or origin server to provide an interface encapsulation of other services, for data translation, performance enhancement, or security enforcement. Note that the difference between a proxy and a gateway is that a client determines when it will use a proxy.

5.3 REST Architectural Views

Now that we have an understanding of the REST architectural elements in isolation, we can use architectural views [ 105 ] to describe how the elements work together to form an architecture. Three types of view--process, connector, and data--are useful for illuminating the design principles of REST.

5.3.1 Process View

A process view of an architecture is primarily effective at eliciting the interaction relationships among components by revealing the path of data as it flows through the system. Unfortunately, the interaction of a real system usually involves an extensive number of components, resulting in an overall view that is obscured by the details. Figure 5-10 provides a sample of the process view from a REST-based architecture at a particular instance during the processing of three parallel requests.

REST's client-server separation of concerns simplifies component implementation, reduces the complexity of connector semantics, improves the effectiveness of performance tuning, and increases the scalability of pure server components. Layered system constraints allow intermediaries--proxies, gateways, and firewalls--to be introduced at various points in the communication without changing the interfaces between components, thus allowing them to assist in communication translation or improve performance via large-scale, shared caching. REST enables intermediate processing by constraining messages to be self-descriptive: interaction is stateless between requests, standard methods and media types are used to indicate semantics and exchange information, and responses explicitly indicate cacheability.

Since the components are connected dynamically, their arrangement and function for a particular application action has characteristics similar to a pipe-and-filter style. Although REST components communicate via bidirectional streams, the processing of each direction is independent and therefore susceptible to stream transducers (filters). The generic connector interface allows components to be placed on the stream based on the properties of each request or response.

Services may be implemented using a complex hierarchy of intermediaries and multiple distributed origin servers. The stateless nature of REST allows each interaction to be independent of the others, removing the need for an awareness of the overall component topology, an impossible task for an Internet-scale architecture, and allowing components to act as either destinations or intermediaries, determined dynamically by the target of each request. Connectors need only be aware of each other's existence during the scope of their communication, though they may cache the existence and capabilities of other components for performance reasons.

5.3.2 Connector View

A connector view of an architecture concentrates on the mechanics of the communication between components. For a REST-based architecture, we are particularly interested in the constraints that define the generic resource interface.

Client connectors examine the resource identifier in order to select an appropriate communication mechanism for each request. For example, a client may be configured to connect to a specific proxy component, perhaps one acting as an annotation filter, when the identifier indicates that it is a local resource. Likewise, a client can be configured to reject requests for some subset of identifiers.

REST does not restrict communication to a particular protocol, but it does constrain the interface between components, and hence the scope of interaction and implementation assumptions that might otherwise be made between components. For example, the Web's primary transfer protocol is HTTP, but the architecture also includes seamless access to resources that originate on pre-existing network servers, including FTP [ 107 ], Gopher [ 7 ], and WAIS [ 36 ]. Interaction with those services is restricted to the semantics of a REST connector. This constraint sacrifices some of the advantages of other architectures, such as the stateful interaction of a relevance feedback protocol like WAIS, in order to retain the advantages of a single, generic interface for connector semantics. In return, the generic interface makes it possible to access a multitude of services through a single proxy. If an application needs the additional capabilities of another architecture, it can implement and invoke those capabilities as a separate system running in parallel, similar to how the Web architecture interfaces with "telnet" and "mailto" resources.

5.3.3 Data View

A data view of an architecture reveals the application state as information flows through the components. Since REST is specifically targeted at distributed information systems, it views an application as a cohesive structure of information and control alternatives through which a user can perform a desired task. For example, looking-up a word in an on-line dictionary is one application, as is touring through a virtual museum, or reviewing a set of class notes to study for an exam. Each application defines goals for the underlying system, against which the system's performance can be measured.

Component interactions occur in the form of dynamically sized messages. Small or medium-grain messages are used for control semantics, but the bulk of application work is accomplished via large-grain messages containing a complete resource representation. The most frequent form of request semantics is that of retrieving a representation of a resource (e.g., the "GET" method in HTTP), which can often be cached for later reuse.

REST concentrates all of the control state into the representations received in response to interactions. The goal is to improve server scalability by eliminating any need for the server to maintain an awareness of the client state beyond the current request. An application's state is therefore defined by its pending requests, the topology of connected components (some of which may be filtering buffered data), the active requests on those connectors, the data flow of representations in response to those requests, and the processing of those representations as they are received by the user agent.

An application reaches a steady-state whenever it has no outstanding requests; i.e., it has no pending requests and all of the responses to its current set of requests have been completely received or received to the point where they can be treated as a representation data stream. For a browser application, this state corresponds to a "web page," including the primary representation and ancillary representations, such as in-line images, embedded applets, and style sheets. The significance of application steady-states is seen in their impact on both user-perceived performance and the burstiness of network request traffic.

The user-perceived performance of a browser application is determined by the latency between steady-states: the period of time between the selection of a hypermedia link on one web page and the point when usable information has been rendered for the next web page. The optimization of browser performance is therefore centered around reducing this communication latency.

Since REST-based architectures communicate primarily through the transfer of representations of resources, latency can be impacted by both the design of the communication protocols and the design of the representation data formats. The ability to incrementally render the response data as it is received is determined by the design of the media type and the availability of layout information (visual dimensions of in-line objects) within each representation.

An interesting observation is that the most efficient network request is one that doesn't use the network. In other words, the ability to reuse a cached response results in a considerable improvement in application performance. Although use of a cache adds some latency to each individual request due to lookup overhead, the average request latency is significantly reduced when even a small percentage of requests result in usable cache hits.

The next control state of an application resides in the representation of the first requested resource, so obtaining that first representation is a priority. REST interaction is therefore improved by protocols that "respond first and think later." In other words, a protocol that requires multiple interactions per user action, in order to do things like negotiate feature capabilities prior to sending a content response, will be perceptively slower than a protocol that sends whatever is most likely to be optimal first and then provides a list of alternatives for the client to retrieve if the first response is unsatisfactory.

The application state is controlled and stored by the user agent and can be composed of representations from multiple servers. In addition to freeing the server from the scalability problems of storing state, this allows the user to directly manipulate the state (e.g., a Web browser's history), anticipate changes to that state (e.g., link maps and prefetching of representations), and jump from one application to another (e.g., bookmarks and URI-entry dialogs).

The model application is therefore an engine that moves from one state to the next by examining and choosing from among the alternative state transitions in the current set of representations. Not surprisingly, this exactly matches the user interface of a hypermedia browser. However, the style does not assume that all applications are browsers. In fact, the application details are hidden from the server by the generic connector interface, and thus a user agent could equally be an automated robot performing information retrieval for an indexing service, a personal agent looking for data that matches certain criteria, or a maintenance spider busy patrolling the information for broken references or modified content [ 39 ].

5.4 Related Work

Bass, et al. [ 9 ] devote a chapter on architecture for the World Wide Web, but their description only encompasses the implementation architecture within the CERN/W3C developed libwww (client and server libraries) and Jigsaw software. Although those implementations reflect many of the design constraints of REST, having been developed by people familiar with the Web's architectural design and rationale, the real WWW architecture is independent of any single implementation. The modern Web is defined by its standard interfaces and protocols, not how those interfaces and protocols are implemented in a given piece of software.

The REST style draws from many preexisting distributed process paradigms [ 6 , 50 ], communication protocols, and software fields. REST component interactions are structured in a layered client-server style, but the added constraints of the generic resource interface create the opportunity for substitutability and inspection by intermediaries. Requests and responses have the appearance of a remote invocation style, but REST messages are targeted at a conceptual resource rather than an implementation identifier.

Several attempts have been made to model the Web architecture as a form of distributed file system (e.g., WebNFS) or as a distributed object system [ 83 ]. However, they exclude various Web resource types or implementation strategies as being "not interesting," when in fact their presence invalidates the assumptions that underlie such models. REST works well because it does not limit the implementation of resources to certain predefined models, allowing each application to choose an implementation that best matches its own needs and enabling the replacement of implementations without impacting the user.

The interaction method of sending representations of resources to consuming components has some parallels with event-based integration (EBI) styles. The key difference is that EBI styles are push-based. The component containing the state (equivalent to an origin server in REST) issues an event whenever the state changes, whether or not any component is actually interested in or listening for such an event. In the REST style, consuming components usually pull representations. Although this is less efficient when viewed as a single client wishing to monitor a single resource, the scale of the Web makes an unregulated push model infeasible.

The principled use of the REST style in the Web, with its clear notion of components, connectors, and representations, relates closely to the C2 architectural style [ 128 ]. The C2 style supports the development of distributed, dynamic applications by focusing on structured use of connectors to obtain substrate independence. C2 applications rely on asynchronous notification of state changes and request messages. As with other event-based schemes, C2 is nominally push-based, though a C2 architecture could operate in REST's pull style by only emitting a notification upon receipt of a request. However, the C2 style lacks the intermediary-friendly constraints of REST, such as the generic resource interface, guaranteed stateless interactions, and intrinsic support for caching.

5.5 Summary

This chapter introduced the Representational State Transfer (REST) architectural style for distributed hypermedia systems. REST provides a set of architectural constraints that, when applied as a whole, emphasizes scalability of component interactions, generality of interfaces, independent deployment of components, and intermediary components to reduce interaction latency, enforce security, and encapsulate legacy systems. I described the software engineering principles guiding REST and the interaction constraints chosen to retain those principles, while contrasting them to the constraints of other architectural styles.

The next chapter presents an evaluation of the REST architecture through the experience and lessons learned from applying REST to the design, specification, and deployment of the modern Web architecture. This work included authoring the current Internet standards-track specifications of the Hypertext Transfer Protocol (HTTP/1.1) and Uniform Resource Identifiers (URI), and implementing the architecture through the libwww-perl client protocol library and Apache HTTP server.

Ole Begemann

Roy fielding’s rest dissertation.

I recently read Roy Fielding’s 2000 PhD thesis, Architectural Styles and the Design of Network-based Software Architectures , in which he introduced and described REST . Here’s what I learned.

REST is almost as old as the web. I first heard of REST around 2005 while working with Rails . As mentioned, Fielding’s dissertation is from 2000, but he began developing the ideas that later became REST as early as 1994.

REST didn’t come out of nowhere. Roy Fielding wasn’t some random PhD student who sat in his ivory tower and came up with a bright idea. He was deeply involved in the web’s early development and standardization. Starting in 1994, Fielding began working at and for the World Wide Web Consortium and co-authored the HTTP 1.0 specification. In the second half of the 1990s, Fielding was the main author behind the HTTP 1.1 and URI specs. He also co-founded the Apache web server project.

REST is the web’s architecture. REST isn’t specifically about web services (i.e. machine-readable APIs that return JSON or XML). In fact, Fielding doesn’t really mention web APIs in his dissertation.

Rather, REST is first and foremost a description of the web’s architecture. The entire web is supposed to be RESTful. Specifying the web (as defined in the HTTP 1.1 spec ) is the original purpose for which REST was developed.

Since 1994, the REST architectural style has been used to guide the design and development of the architecture for the modern Web. This work was done in conjunction with my authoring of the Internet standards for the Hypertext Transfer Protocol (HTTP) and Uniform Resource Identifiers (URI), the two specifications that define the generic interface used by all component interactions on the Web. — Roy Fielding, Architectural Styles and the Design of Network-based Software Architectures, p. 107.

The original name for REST was the “HTTP object model”:

REST was originally referred to as the “HTTP object model,” but that name would often lead to misinterpretation of it as the implementation model of an HTTP server. The name “Representational State Transfer” is intended to evoke an image of how a well-designed Web application behaves: a network of web pages (a virtual state-machine), where the user progresses through the application by selecting links (state transitions), resulting in the next page (representing the next state of the application) being transferred to the user and rendered for their use. — ibid., p. 109.

Architectural constraints

REST is defined through constraints. Any communication architecture that wants to call itself RESTful must abide by these constraints. You can read the full list on the Wikipedia page . Here, I’ll just list the ones I find most important.


Each request must contain all of the information necessary for the server to understand the request, and cannot take advantage of any stored context on the server. Session state is kept entirely on the client. Statelessness makes a service more reliable and easier to scale.

Fielding notes that cookies violate REST. To him, the presence of cookies is an unfortunate mismatch between the ideals of REST and the reality of HTTP:

An example of where an inappropriate extension has been made to the protocol [HTTP] to support features that contradict the desired properties of the generic interface is the introduction of site-wide state information in the form of HTTP cookies. Cookie interaction fails to match REST’s model of application state, often resulting in confusion for the typical browser application. — ibid., p. 130.


Requests and responses must include information about their cacheability. If a response is marked as cacheable, the client (or any node sitting between server and client) is allowed to reuse the data for later requests.

Fielding’s focus in the dissertation is markedly different from how developers discuss REST today. He spends a lot of time discussing web characteristics like cacheability, scalability, and the transparency of messages to intermediaries (proxies), whereas the finer points of POST vs. PUT vs. PATCH play no role in the thesis. In fact, he doesn’t mention the different HTTP methods at all.

Resources and representations

Identification of resources. Resources are the key abstraction of REST. This is in constrast to earlier specifications of the web, which used the term document for an individual “unit of content”. Resources are a more generic concept than documents. For example, having the URI to a document implies that the document exists, while a resource identifier can be valid before the resource exists (e.g. a client could pass a URI of a non-existent resource to create it).

A resource is a conceptual mapping to a set of concrete entities. For example, “today’s weather” is a valid resource, even though the concrete piece of information it maps to changes every day. Each resource has a unique identifier (usually a URI ).

Manipulation of resources through representations. Since resources can be abstract concepts, a resource itself is never directly manipulated or sent over the network. Instead, server and client exchange representations of resources. The server can (and should) offer multiple representations (e.g. JSON and XML) of the same resource. Clients tell the server which representation formats they understand.

REST components communicate by transferring a representation of a resource in a format matching one of an evolving set of standard data types , selected dynamically based on the capabilities or desires of the recipient and the nature of the resource. Whether the representation is in the same format as the raw source, or is derived from the source, remains hidden behind the interface. — ibid., p. 87.

Self-descriptive messages

Messages include enough information to describe how their payload is to be processed (e.g. media type information must be part of each message). Also, each message completely identifies the resource it concerns (this wasn’t the case in the early days of HTTP when the HTTP header didn’t contain the hostname because it was assumed that there was a 1:1 mapping between IP addresses and hostnames).

Hypermedia as the engine of application state

The central idea behind HATEOAS is that RESTful servers and clients shouldn’t rely on a hardcoded interface (that they agreed upon through a separate channel). Instead, the server is supposed to send the set of URIs representing possible state transitions with each response, from which the client can select the one it wants to transition to. This is exactly how web browsers work:

The model application is therefore an engine that moves from one state to the next by examining and choosing from among the alternative state transitions in the current set of representations. Not surprisingly, this exactly matches the user interface of a hypermedia browser. — ibid. , p. 103.

For web services where two machines talk to each other without a human controlling the interaction, I have a harder time imagining how this is supposed to work. How can you develop a client for a specific API without hardcoding some knowledge about the expected resource types? Fielding doesn’t elaborate on this in his thesis.

However, he later clarified in a 2008 blog post that APIs must be hypertext-driven to legitimately call themselves RESTful:

A REST API should be entered with no prior knowledge beyond the initial URI and set of standardized media types. From that point on, all application state transitions must be driven by client selection of server-provided choices that are present in the received representations or implied by the user’s manipulation of those representations. The transitions may be determined (or limited by) the client’s knowledge of media types and resource communication mechanisms, both of which may be improved on-the-fly (e.g., code-on-demand).

I’m still not sure how anybody can develop e.g. a great mobile app under these constraints that provides a specialized user interface for one particular service. If you don’t have any out-of-band knowledge about the service you’re interacting with, you’re basically reimplementing a web browser.

PhotoKit’s data model

September 28, 2018

Splitting a Swift Sequence into head and tail

November 29, 2018

Roy T. Fielding: Understanding the REST Style

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Computing through the ages

rest dissertation roy fielding

Roy Fielding's Misappropriated REST Dissertation

28 Jun 2020

RESTful APIs are everywhere. This is funny, because how many people really know what “RESTful” is supposed to mean?

I think most of us can empathize with this Hacker News poster :

I’ve read several articles about REST, even a bit of the original paper. But I still have quite a vague idea about what it is. I’m beginning to think that nobody knows, that it’s simply a very poorly defined concept.

I had planned to write a blog post exploring how REST came to be such a dominant paradigm for communication across the internet. I started my research by reading Roy Fielding’s 2000 dissertation , which introduced REST to the world. After reading Fielding’s dissertation, I realized that the much more interesting story here is how Fielding’s ideas came to be so widely misunderstood.

Many more people know that Fielding’s dissertation is where REST came from than have read the dissertation (fair enough), so misconceptions about what the dissertation actually contains are pervasive.

The biggest of these misconceptions is that the dissertation directly addresses the problem of building APIs. I had always assumed, as I imagine many people do, that REST was intended from the get-go as an architectural model for web APIs built on top of HTTP. I thought perhaps that there had been some chaotic experimental period where people were building APIs on top of HTTP all wrong, and then Fielding came along and presented REST as the sane way to do things. But the timeline doesn’t make sense here: APIs for web services, in the sense that we know them today, weren’t a thing until a few years after Fielding published his dissertation.

Fielding’s dissertation (titled “Architectural Styles and the Design of Network-based Software Architectures”) is not about how to build APIs on top of HTTP but rather about HTTP itself. Fielding contributed to the HTTP/1.0 specification and co-authored the HTTP/1.1 specification, which was published in 1999. He was interested in the architectural lessons that could be drawn from the design of the HTTP protocol; his dissertation presents REST as a distillation of the architectural principles that guided the standardization process for HTTP/1.1. Fielding used these principles to make decisions about which proposals to incorporate into HTTP/1.1. For example, he rejected a proposal to batch requests using new MGET and MHEAD methods because he felt the proposal violated the constraints prescribed by REST, especially the constraint that messages in a REST system should be easy to proxy and cache. 1 So HTTP/1.1 was instead designed around persistent connections over which multiple HTTP requests can be sent. (Fielding also felt that cookies are not RESTful because they add state to what should be a stateless system, but their usage was already entrenched. 2 ) REST, for Fielding, was not a guide to building HTTP-based systems but a guide to extending HTTP.

This isn’t to say that Fielding doesn’t think REST could be used to build other systems. It’s just that he assumes these other systems will also be “distributed hypermedia systems.” This is another misconception people have about REST: that it is a general architecture you can use for any kind of networked application. But you could sum up the part of the dissertation where Fielding introduces REST as, essentially, “Listen, we just designed HTTP, so if you also find yourself designing a distributed hypermedia system you should use this cool architecture we worked out called REST to make things easier.” It’s not obvious why Fielding thinks anyone would ever attempt to build such a thing given that the web already exists; perhaps in 2000 it seemed like there was room for more than one distributed hypermedia system in the world. Anyway, Fielding makes clear that REST is intended as a solution for the scalability and consistency problems that arise when trying to connect hypermedia across the internet, not as an architectural model for distributed applications in general.

We remember Fielding’s dissertation now as the dissertation that introduced REST, but really the dissertation is about how much one-size-fits-all software architectures suck, and how you can better pick a software architecture appropriate for your needs. Only a single chapter of the dissertation is devoted to REST itself; much of the word count is spent on a taxonomy of alternative architectural styles 3 that one could use for networked applications. Among these is the Pipe-and-Filter (PF) style, inspired by Unix pipes, along with various refinements of the Client-Server style (CS), such as Layered-Client-Server (LCS), Client-Cache-Stateless-Server (C$SS), and Layered-Client-Cache-Stateless-Server (LC$SS). The acronyms get unwieldy but Fielding’s point is that you can mix and match constraints imposed by existing styles to derive new styles. REST gets derived this way and could instead have been called—but for obvious reasons was not—Uniform-Layered-Code-on-Demand-Client-Cache-Stateless-Server (ULCODC$SS). Fielding establishes this taxonomy to emphasize that different constraints are appropriate for different applications and that this last group of constraints were the ones he felt worked best for HTTP.

This is the deep, deep irony of REST’s ubiquity today. REST gets blindly used for all sorts of networked applications now, but Fielding originally offered REST as an illustration of how to derive a software architecture tailored to an individual application’s particular needs.

I struggle to understand how this happened, because Fielding is so explicit about the pitfalls of not letting form follow function. He warns, almost at the very beginning of the dissertation, that “design-by-buzzword is a common occurrence” brought on by a failure to properly appreciate software architecture. 4 He picks up this theme again several pages later:

Some architectural styles are often portrayed as “silver bullet” solutions for all forms of software. However, a good designer should select a style that matches the needs of a particular problem being solved. 5

REST itself is an especially poor “silver bullet” solution, because, as Fielding later points out, it incorporates trade-offs that may not be appropriate unless you are building a distributed hypermedia application:

REST 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. 6

Fielding came up with REST because the web posed a thorny problem of “anarchic scalability,” by which Fielding means the need to connect documents in a performant way across organizational and national boundaries. The constraints that REST imposes were carefully chosen to solve this anarchic scalability problem. Web service APIs that are public-facing have to deal with a similar problem, so one can see why REST is relevant there. Yet today it would not be at all surprising to find that an engineering team has built a backend using REST even though the backend only talks to clients that the engineering team has full control over. We have all become the architect in this Monty Python sketch , who designs an apartment building in the style of a slaughterhouse because slaughterhouses are the only thing he has experience building. (Fielding uses a line from this sketch as an epigraph for his dissertation: “Excuse me… did you say ‘knives’?”)

So, given that Fielding’s dissertation was all about avoiding silver bullet software architectures, how did REST become a de facto standard for web services of every kind?

My theory is that, in the mid-2000s, the people who were sick of SOAP and wanted to do something else needed their own four-letter acronym.

I’m only half-joking here. SOAP, or the Simple Object Access Protocol, is a verbose and complicated protocol that you cannot use without first understanding a bunch of interrelated XML specifications. Early web services offered APIs based on SOAP, but, as more and more APIs started being offered in the mid-2000s, software developers burned by SOAP’s complexity migrated away en masse.

Among this crowd, SOAP inspired contempt. Ruby-on-Rails dropped SOAP support in 2007, leading to this emblematic comment from Rails creator David Heinemeier Hansson: “We feel that SOAP is overly complicated. It’s been taken over by the enterprise people, and when that happens, usually nothing good comes of it.” 7 The “enterprise people” wanted everything to be formally specified, but the get-shit-done crowd saw that as a waste of time.

If the get-shit-done crowd wasn’t going to use SOAP, they still needed some standard way of doing things. Since everyone was using HTTP, and since everyone would keep using HTTP at least as a transport layer because of all the proxying and caching support, the simplest possible thing to do was just rely on HTTP’s existing semantics. So that’s what they did. They could have called their approach Fuck It, Overload HTTP (FIOH), and that would have been an accurate name, as anyone who has ever tried to decide what HTTP status code to return for a business logic error can attest. But that would have seemed recklessly blasé next to all the formal specification work that went into SOAP.

Luckily, there was this dissertation out there, written by a co-author of the HTTP/1.1 specification, that had something vaguely to do with extending HTTP and could offer FIOH a veneer of academic respectability. So REST was appropriated to give cover for what was really just FIOH.

I’m not saying that this is exactly how things happened, or that there was an actual conspiracy among irreverent startup types to misappropriate REST, but this story helps me understand how REST became a model for web service APIs when Fielding’s dissertation isn’t about web service APIs at all. Adopting REST’s constraints makes some sense, especially for public-facing APIs that do cross organizational boundaries and thus benefit from REST’s “uniform interface.” That link must have been the kernel of why REST first got mentioned in connection with building APIs on the web. But imagining a separate approach called “FIOH,” that borrowed the “REST” name partly just for marketing reasons, helps me account for the many disparities between what today we know as RESTful APIs and the REST architectural style that Fielding originally described.

REST purists often complain, for example, that so-called REST APIs aren’t actually REST APIs because they do not use Hypermedia as The Engine of Application State (HATEOAS). Fielding himself has made this criticism . According to him, a real REST API is supposed to allow you to navigate all its endpoints from a base endpoint by following links. If you think that people are actually out there trying to build REST APIs, then this is a glaring omission—HATEOAS really is fundamental to Fielding’s original conception of REST, especially considering that the “state transfer” in “Representational State Transfer” refers to navigating a state machine using hyperlinks between resources (and not, as many people seem to believe, to transferring resource state over the wire). 8 But if you imagine that everyone is just building FIOH APIs and advertising them, with a nudge and a wink, as REST APIs, or slightly more honestly as “RESTful” APIs, then of course HATEOAS is unimportant.

Similarly, you might be surprised to know that there is nothing in Fielding’s dissertation about which HTTP verb should map to which CRUD action, even though software developers like to argue endlessly about whether using PUT or PATCH to update a resource is more RESTful. Having a standard mapping of HTTP verbs to CRUD actions is a useful thing, but this standard mapping is part of FIOH and not part of REST.

This is why, rather than saying that nobody understands REST, we should just think of the term “REST” as having been misappropriated. The modern notion of a REST API has historical links to Fielding’s REST architecture, but really the two things are separate. The historical link is good to keep in mind as a guide for when to build a RESTful API. Does your API cross organizational and national boundaries the same way that HTTP needs to? Then building a RESTful API with a predictable, uniform interface might be the right approach. If not, it’s good to remember that Fielding favored having form follow function. Maybe something like GraphQL or even just JSON-RPC would be a better fit for what you are trying to accomplish.

If you enjoyed this post, more like it come out every four weeks! Follow @TwoBitHistory on Twitter or subscribe to the RSS feed to make sure you know when a new post is out.

Previously on TwoBitHistory…

New post is up! I wrote about how to solve differential equations using an analog computer from the '30s mostly made out of gears. As a bonus there's even some stuff in here about how to aim very large artillery pieces. https://t.co/fwswXymgZa — TwoBitHistory (@TwoBitHistory) April 6, 2020

Roy Fielding. “Architectural Styles and the Design of Network-based Software Architectures,” 128. 2000. University of California, Irvine, PhD Dissertation, accessed June 28, 2020, https://www.ics.uci.edu/~fielding/pubs/dissertation/fielding_dissertation_2up.pdf .  ↩

Fielding, 130.  ↩

Fielding distinguishes between software architectures and software architecture “styles.” REST is an architectural style that has an instantiation in the architecture of HTTP.  ↩

Fielding, 2.  ↩

Fielding, 15.  ↩

Fielding, 82.  ↩

Paul Krill. “Ruby on Rails 2.0 released for Web Apps,” InfoWorld. Dec 7, 2007, accessed June 28, 2020, https://www.infoworld.com/article/2648925/ruby-on-rails-2-0-released-for-web-apps.html   ↩

Fielding, 109.  ↩

Fundamentals of RESTful APIs

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APIs are not new. They’ve served as interfaces that enable applications to communicate with each other for decades. But the role of APIs has changed dramatically in the last few years. Innovative companies have discovered that APIs can be used as an interface to the business, allowing them to monetize digital assets, extend their value proposition with partner-delivered capabilities, and connect to customers across channels and devices. When you create an API, you are allowing others within or outside of your organization to make use of your service or product to create new applications, attract customers, or expand their business. Internal APIs enhance the productivity of development teams by maximizing reusability and enforcing consistency in new applications. Public APIs can add value to your business by allowing third-party developers to enhance your services or bring their customers to you. As developers find new applications for your services and data, a network effect occurs, delivering significant bottom-line business impact. For example, Expedia opened up their travel booking services to partners through an API to launch the Expedia Affiliate Network, building a new revenue stream that now contributes $2B in annual revenue. Salesforce released APIs to enable partners to extend the capabilities of their platform and now generates half of their annual revenue through those APIs, which could be SOAP based (JAX-WS) and, more recently, RESTful (JAX-RS), Spring Boot, and now Micronaut.

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Stavropol Krai is a federal subject of Russia located in the central part of Ciscaucasia and on the northern slope of the Greater Caucasus in the North-Caucasian Federal District. Stavropol is the capital city of the region.

The population of Stavropol Krai is about 2,780,200 (2022), the area - 66,160 sq. km.

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11 January, 2021   / The Kochubeevskaya wind farm with an installed capacity of 210 MW, the largest in Russia, has been commissioned in Stavropol Krai. With a total area of about 200 hectares, it includes 84 wind turbines, each 150 meters high, the length of the blades - 50 meters.

History of Stavropol Krai

The most ancient archaeological finds date back to the 4th millennium BC. The territory of the present Stavropol region was successively part of the state of the Scythians (the 7th - 5th centuries BC), Sarmatians (the 3rd century BC - the 3rd century AD), Huns (the 4th - 5th centuries AD).

Later, from 620 to 969, this territory was part of the ancient state called the Khazar Khaganate. Approximately in the 8th century, with the weakening of the Khazar Kaganate, the medieval state of the Alans appeared here. In 1238-1239, a significant part of the plain Alania was captured by the Mongols, and this state as a political entity ceased to exist.

In 1556, the Russian troops took Astrakhan and opened the way to the North Caucasus and the Caspian Sea. In Ciscaucasia, the interests of Russia, the Ottoman Empire, the Crimean Khanate, and Iran collided.

In 1777, according to the decree of Catherine II, the Azov-Mozdok defensive line was founded, which gave rise to colonization of the Ciscaucasia and the North Caucasus. The territory of the Stavropol region became part of Astrakhan oblast. In November 1777, the fortress called Stavropolskaya was founded. In 1782, about 500 retired soldiers lived there.

More historical facts…

In 1785, in connection with the development of Ciscaucasia, the Caucasian guberniya (province) was created that included the Caucasian and Astrakhan regions. Since that time, Stavropol officially became one of the six county-level towns of the Caucasus region.

With the development of the Ciscaucasia, Stavropol was gaining an increasing importance as an important trade and transit center. It became a kind of the main gate of the Caucasus. In 1822, the Caucasian province was transformed into an oblast and Stavropol became its center. After the defeat of the Decembrist uprising, a lot of its participants were sent here. In 1837 - 1841, Mikhail Lermontov, exiled to the Caucasus, visited Stavropol several times.

In 1847, the Caucasian oblast was reformed into Stavropol gubernia. With the formation of the Kuban and Terek Cossack regions and the end of the Caucasian War, the military-political and economic importance of Stavropol significantly reduced.

In 1919, the Stavropol province was occupied by the Bolsheviks and included in the territory of the North Caucasian Soviet Republic. As a result of the Second Kuban campaign the region went under the control of the Volunteer Army.

In October 1924, the North Caucasian region was formed and Stavropol gubernia was reformed into a district within the region. On January 10, 1934, the North Caucasian Krai was divided into the Azovo-Chernomorsky and North Caucasian. The town of Pyatigorsk became the center of North Caucasian Krai. In March 1936, North Caucasian Krai was reformed and, on its territory, Ordzhonikidze Krai with the center in Ordzhonikidze (Stavropol) was formed.

During the Second World War, from August 1942 to January 1943, the region was occupied by the German troops. In 1943, Ordzhonikidze Krai was renamed Stavropol Krai. In December 1956, the first part of the Stavropol-Moscow gas pipeline with a length of 1,300 km was commissioned (at that time, it was the longest gas pipeline in Europe).

During the 1970s-1980s, 56 new enterprises were opened in the region, among them the Prikumsky Plastics Plant - the largest chemical plant in the region, four power units at the Stavropol power station, and new capacities at the Nevinnomyssk enterprise “Azot”.

On July 3, 1991, Karachay-Cherkess Autonomous Region withdrew from Stavropol Krai and became the Karachay-Cherkess Soviet Socialist Republic. On April 21, 1992, it became the Republic of Karachay-Cherkessia of the Russian Federation.

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Stavropol Krai stretches for 285 km from north to south and 370 km from west to east. The climate is temperate continental. The average temperature in January is minus 5 degrees Celsius (in mountains - down to -10), in July - plus 22-25 degrees Celsius (in mountains - +14).

The main natural resources are natural gas, oil, polymetals containing uranium, building materials. Mineral medicinal waters are a special riches of the region.

The Caucasian Mineral Waters is Russia’s largest resort region, which has no analogues in the whole of Eurasia for the richness and diversity of mineral waters and therapeutic mud. The healing properties of “narzan”, one of the popular local mineral waters, are known throughout Russia. The name can be translated into Russian as “Hercules’ beverage”, “Water of Hercules”.

The largest cities and towns are Stavropol (458,200), Pyatigorsk (145,500), Kislovodsk (127,300), Nevinnomyssk (114,400), Yessentuki (117,200), Mikhailovsk (94,500), Mineralnye Vody (72,400), Georgievsk (64,400), Budennovsk (59,600).

Stavropol Krai - Economy

The main industries of Stavropol Krai are engineering, production and processing of oil and natural gas, electric power industry, food (winemaking, butter, sugar), chemical (mineral fertilizers in Nevinnomyssk), building materials (glass in Mineralnye Vody), light (wool in Nevinnomyssk, leather in Budennovsk).

Agriculture specializes in growing grain and sunflower, the leading role in livestock breeding belongs to cattle breeding, fine-wool sheep breeding. Horticulture, viticulture, poultry farming, pig breeding, beekeeping are widespread. Agriculture is one of the most important sectors of the local economy, which employs more than 156 thousand people.

The main highway M29 “Caucasus” passes through Nevinnomyssk, Mineralnye Vody and Pyatigorsk. There are international airports in Stavropol (Shpakovskoye) and Mineralnye Vody. This region has a very dense and extensive network of pipelines.

Attractions of Stavropol Krai

A large number of various interesting places are concentrated on the territory of the Stavropol region. Here are just a few of the most famous sights:

  • Proval - a lake and a natural cave on the southern slope of Mount Mashuk in Pyatigorsk. The cave is a cone-shaped funnel with a height of 41 m, at the bottom of which there is a karst lake of mineral water of pure blue color;
  • Monument to Lermontov in Pyatigorsk at the place where the poet was fatally wounded during the duel;
  • Lake Tambukan (Black Lake), located near Pyatigorsk, is known for its unique healing mud;
  • Therapeutic park, mineral springs, Balneary mud baths named after Semashko in the resort city of Yessentuki;
  • Resort park in Kislovodsk is very popular with tourists. The territory of the park is huge. Here you can find a drinking gallery, ponds, grottoes, and the famous valley of roses. Plants growing in the park make the air unusually clean and healthy;
  • Koltso (Ring) Mount near Kislovodsk. Under the influence of natural factors, a ring with a diameter of 8 meters was formed in the center of the rock;
  • Pushkin Gallery (1901), the Emir of Bukhara Palace, the Cave of Permafrost, Zheleznaya Mount in the resort town of Zheleznovodsk.

Stavropol krai of Russia photos

Stavropol Krai scenery

Paved road in Stavropol Krai

Paved road in Stavropol Krai

Author: A.Kostin

Winter in Stavropol Krai

Winter in Stavropol Krai

Author: Kabatov V.

Small river in the Stavropol region

Small river in the Stavropol region

Author: Alex Stanin

Pictures of Stavropol Krai

Beautiful nature of Stavropol Krai

Beautiful nature of Stavropol Krai

Author: Sergey Shevchenko

Stavropol Krai scenery

Author: V.Buturlia

Cathedral in Stavropol Krai

Cathedral in Stavropol Krai

Author: Bulgakov Pyotr

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Sustainability from the Local Perspective: The Evidence from Zlatibor Tourist Center (Republic of Serbia)


Other Interests

I like playing games -- especially non-betting card games (Bridge, Hearts, etc.) and obscure board games (british rails, naval war, etc.). I also like playing basketball, softball, football and going fishing. Mind you, I haven't had time to do any of these things since I started messing with the Web.

What is life? It is the flash of a firefly in the night. It is the breath of a buffalo in the wintertime. It is the little shadow which runs across the grass and loses itself in the sunset. --- Crowfoot's last words (1890), Blackfoot warrior and orator.
To most readers it will be easy, after reading this tale, to accept Rover's theory that Man is set up deliberately as the antithesis of everything the Dogs stand for, a sort of mythical straw-man, a sociological fable. This is underlined by the recurring evidence of Man's aimlessness, his constant running hither and yon, his grasping at a way of life which constantly eludes him, possibly because he never knows exactly what he wants. --- Clifford D. Simak, "City" [Notes on the Fifth Tale], 1952.
Life is a distributed object system. However, communication among humans is a distributed hypermedia system, where the mind's intellect, voice+gestures, eyes+ears, and imagination are all components. --- Roy T. Fielding, 1998.


  1. Roy T. Fielding: Understanding the REST Style

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  2. Introduction to REST API

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  3. Roy Fielding's REST dissertation

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  4. REST in AEM by Roy Fielding

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  5. Rest fielding dissertation

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  6. A little REST and Relaxation

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  1. Fielding Dissertation: CHAPTER 5: Representational State Transfer (REST)

    CHAPTER 5. This chapter introduces and elaborates the Representational State Transfer (REST) architectural style for distributed hypermedia systems, describing the software engineering principles guiding REST and the interaction constraints chosen to retain those principles, while contrasting them to the constraints of other architectural styles.

  2. Roy Fielding's REST dissertation

    As mentioned, Fielding's dissertation is from 2000, but he began developing the ideas that later became REST as early as 1994. REST didn't come out of nowhere. Roy Fielding wasn't some random PhD student who sat in his ivory tower and came up with a bright idea. He was deeply involved in the web's early development and standardization.

  3. Roy T. Fielding: Understanding the REST Style

    Roy T. Fielding talks with Charles Severance about his PhD dissertation, which defined the Representational State Transfer architectural style. From Computer...

  4. PDF Reflections on the REST Architectural Style and ``Principled Design of

    2.1 Formulation in Dissertation (2000) Fielding's dissertation [16] is the original and most widely cited description of REST. As an architectural style for network-based applications, its def-inition is presented in the dissertation incrementally, as an accu-mulation of design constraints that derive from nine pre-existing

  5. Roy T. Fielding: Understanding the REST Style

    Roy T. Fielding reminisces about his PhD dissertation, which defined the Representational State Transfer architectural style. The first Web extra at http://yout

  6. Roy T. Fielding: Understanding the REST Style

    In this Episode. Roy T. Fielding reminisces about his PhD dissertation, which defined the Representational State Transfer architectural style. From Computer's Issue 6, Vol 48 - June 2015. Roy T. Fielding: Understanding the REST Style.

  7. Introduction to REST

    REST stands for REpresentational State Transfer and is an architectural style for designing distributed network applications. Roy Fielding coined the term REST in his PhD dissertation Footnote 1 and proposed the following six constraints or principles as its basis:. Client-server—Concerns should be separated between clients and servers.

  8. Roy T. Fielding: Understanding the REST Style

    A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.

  9. Roy Fielding

    Roy Thomas Fielding (born 1965) is an American computer scientist, one of the principal authors of the HTTP specification and the originator of the Representational State Transfer (REST) architectural style. He is an authority on computer network architecture and co-founded the Apache HTTP Server project.. Fielding works as a Senior Principal Scientist at Adobe Systems in San Jose, California.

  10. Roy Fielding's Misappropriated REST Dissertation

    He was interested in the architectural lessons that could be drawn from the design of the HTTP protocol; his dissertation presents REST as a distillation of the architectural principles that guided the standardization process for HTTP/1.1. Fielding used these principles to make decisions about which proposals to incorporate into HTTP/1.1.

  11. Fundamentals of RESTful APIs

    This section has further introductory details about REST concepts. "REST" was coined by Roy Fielding in his Ph.D. dissertation to describe a design pattern for implementing networked systems. REST is Representational State Transfer, an architectural style for designing distributed systems. It's not a standard, but rather a set of constraints.

  12. PDF Roy Fielding's PHD Dissertation

    Roy Fielding's PHD Dissertation Chapter's 5 & 6 (REST) Architectural Styles and the Design of Network-based Software Architectures Roy Fielding University of California - Irvine 2000. Chapter 5 Representational State Transfer (REST) Deriving REST

  13. ‪Roy T. Fielding‬

    Roy T. Fielding. Senior Principal Scientist, Adobe. Verified email at gbiv.com - Homepage. Software Architecture Software Engineering Computer Supported Collaborative Work Human-Computer Interaction Networking. Title. Sort. Sort by citations Sort by year Sort by title. Cited by.

  14. REST APIs must be hypertext-driven » Untangled

    A REST API should not be dependent on any single communication protocol, though its successful mapping to a given protocol may be dependent on the availability of metadata, choice of methods, etc. In general, any protocol element that uses a URI for identification must allow any URI scheme to be used for the sake of that identification.

  15. Stavropol Krai

    Stavropol Krai, also known as Stavropolye, is a federal subject of Russia. It is geographically located in the North Caucasus region in Southern Russia, and is administratively part of the North Caucasian Federal District. Stavropol Krai has a population of 2,907,593, according to the 2021 Census.

  16. Stavropol Krai, Russia guide

    Stavropol Krai - Overview. Stavropol Krai is a federal subject of Russia located in the central part of Ciscaucasia and on the northern slope of the Greater Caucasus in the North-Caucasian Federal District. Stavropol is the capital city of the region. The population of Stavropol Krai is about 2,780,200 (2022), the area - 66,160 sq. km.

  17. MilSim West

    Now, after a particularly warm winter, Russian forces have begun to push south with one goal: to SEIZE STAVROPOL. MilSim West Presents SEIZE STAVROPOL May 27-29 in Centerville, WA on 3300 acres of land in one of the largest AOs ever used for war gaming. Registration opens Thursday, March 10 at $150. March 10-March 24 - $150.

  18. Sustainability from the Local Perspective: The Evidence from Zlatibor

    Tourism sustainability is a ubiquitous topic of scientific circles. To this day, there is controversy about the environmental, economic and socio-cultural sustainability of this global industry.

  19. Roy T. Fielding

    My dissertation, Architectural Styles and the Design of Network-based Software Architectures, ... Most of the rest can be seen in my vita. I was a Visiting Scholar at MIT/LCS during the summer of 1995, ... --- Roy T. Fielding, 1998.