|By Thomas Erl||
|August 16, 2008 02:15 PM EDT||
Each SOA design pattern provides a design solution in support of successfully applying service orientation and establishing a quality service-oriented architecture. Therefore, to better understand how and to what extent individual SOA design patterns can be applied, SOA as an architectural model itself needs to be broken down into the following types, each of which represent a common "scope of implementation":
- Service Architecture: The architecture of a single service
- Service Composition Architecture: The architecture of a set of services assembled into a service composition
- Service Inventory Architecture: The architecture that supports a collection of related services that are independently standardized and governed
- Service-Oriented Enterprise Architecture: The architecture of the enterprise to whatever extent it is service-oriented
In a typical enterprise, these architecture types are very much interrelated, yet each requires individual design attention and documentation.
About the Patterns
This article is roughly organized according to these architecture types and related patterns.
SOA design patterns collectively form a master pattern language that allows patterns to be applied in different combinations and sequences. There are also compound patterns that are comprised of multiple individual design patterns. (For example, the Enterprise Service Bus and orchestration both represent compound design patterns.)
SOA design patterns are not specific to any particular vendor platform or business industry; they are simply design techniques that help overcome common obstacles to achieving the strategic goals and benefits associated with SOA and service-oriented computing.
The remainder of this article highlights key design patterns while referencing a cross-section of others. Not all mentioned patterns are explained, but descriptions are freely available at the SOA patterns community site (www.soapatterns.org).
Patterns for Collections of Services
A service inventory represents a collection of independently standardized and governed services. As shown in Figure 1, the services you deliver for a given service inventory are standardized and designed according to service orientation so that they become intrinsically interoperable. This then allows you to draw from this pool of services to assemble and augment service compositions repeatedly.
Inventory Boundary Patterns
One of the biggest decisions a project team faces when starting an SOA initiative is determining the appropriate scope of a service inventory. The Enterprise Inventory and Domain Inventory design patterns help address this decision point by providing alternative approaches.
The goal of the Enterprise Inventory pattern is to establish an enterprise-wide service inventory. The end result of achieving this pattern is considered desirable because it enables you to build all of your services according to the same design conventions to ensure consistent and widespread inter-service compatibility. It further guarantees that all of the services will be owned and evolved by the same group or department, which is the ultimate in centralized governance.
Although ideal, this approach is often not realistic, especially for larger organizations. It can raise various issues, including time and budget constraints, cultural and political concerns, and order of magnitude considerations (especially in relation to the long-term growth and governance of the inventory). These issues can introduce risks and problems that outweigh the benefit potential of applying this pattern.
This is the reason the Domain Inventory pattern has become so popular. It advocates an approach whereby the enterprise is divided into segments (domains), each of which represents a meaningful cross-silo scope. Often, the boundary of a domain inventory architecture is aligned with a business domain (such as accounting or claims). Services delivered into this architectural boundary are subject to the same design standards and governance practices, allowing them to be evolved independently from neighboring domain inventories in the same enterprise.
Although the use of this pattern can introduce the need for cross-domain data model and protocol conversion (as per the Schema Transformation and Protocol Bridging patterns), there are additional patterns (such as Cross-Domain Utility Layer, Dual Protocols, and Inventory Endpoint) that help reduce this impact.
Inventory Structure Patterns
Regardless of its scope, within the boundary of a service inventory, certain design patterns are applied to ensure a consistent structure in support of service orientation. For example, Logic Centralization positions reusable services as the sole or primary contact points for the logic they represent. This is further supported by the Service Normalization pattern that fosters service autonomy by reducing the amount of functional overlap between individual service boundaries to establish more of a "normalized" inventory.
The Service Layers pattern (and related, specialized layer patterns) can be used to further organize a service inventory into a set of logical layers, each of which is based on a different classification of service.
Note: Just a reminder that all of these structural patterns are only applied within the boundary of an inventory architecture. This means that, if you are working within the confines of a domain inventory, these patterns will not be applied on an enterprise-wide basis.
To support and extend the structure of a service inventory architecture, various other design patterns can be applied. Some (like Canonical Schema and Canonical Transport Protocol) help standardize the services within the inventory boundary to foster native interoperability and composability, while others (like Process Centralization and Rules Centralization) can be selectively used to leverage established product platforms that support the centralized management of business process logic and business rules, respectively.
Yet another dimension to inventory architecture design is the centralization of service contract-related logic. The creation of redundant schema and policy content can be addressed by the Schema Centralization and Policy Centralization patterns, each of which establishes a separate data representation layer (one layer for data models, the other for global and domain-level policies) that supports the primary service contract layer.
There are many more specialized patterns that are applied to an inventory architecture to solve common problems related to resource management, state management, quality of service, security, and communication.
Patterns for Service Design
Each service exists as a standalone software program, autonomous yet still fully geared to participate in larger service aggregations. When designing a service architecture, numerous challenges can arise, especially when shaping this architecture according to service-orientation design principles, such as Service Statelessness and Service Loose Coupling. Figure 2 provides an abstract glimpse of service architecture design patterns that are applied at the service architecture level.
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