Accenture Global Services Gmbh

Sean David Peterson

Michael Gerald DeLuca

Patrick Francis Cimprich

Marshall J Wells

Jack Q W Cantwell

Jack Qw Cantwell

Michael Gerald Deluca

Jack QW Cantwell

A network component placement architecture addresses the difficult technical challenge of determining where specific technical components of an overall service may be provisioned. The architecture is particularly effective at determining where, among a myriad of possible service provides, platforms, and regions, the technical components can be placed and meet all of the applicable technical constraints on the placement of the technical components. In one implementation, the placement architecture includes a sequence of pipeline stages that define an analysis sequence leading to a set of possible placement options.

Network component placement architecture

Provisioning resources into the cloud is a constantly increasing technical challenge as more cloud service providers emerge, each offering disparate computing platforms, services, assets, supported technical components, and other features. A cloud computing provisioning architecture implements a sequence of complex technical analyses that successfully provisions complex cloud computing services. The provisioning architecture disaggregates resources into individual provisioning actions, and also selectively re-aggregates the resources into template blocks which a service provider accepts for native provisioning.

Multi-cloud provisioning architecture with template aggregation

Provisioning resources into the cloud is a constantly increasing technical challenge as more cloud service providers emerge, each offering disparate computing platforms, services, assets, supported technical components, and other features. A cloud computing provisioning architecture implements a sequence of complex technical analyzes that successfully provisions complex cloud computing services.

Cloud computing placement and provisioning architecture

A network component placement architecture addresses the difficult technical challenge of determining where specific technical components of an overall service may be provisioned. However, the placement decision can change over time in response to complex updates relating to service providers, the regions they support, the assets they support, and many other dynamic factors. Dynamic network component placement effectively determines updated possibilities for placing the technical components of a specified service, while meeting all of the applicable technical constraints on the placement of the technical components.

Dynamic network component placement

Cloud computing has emerged as an extremely popular implementation option for a wide range of computing services. However, provisioning services into the cloud is an extremely difficult technical challenge. This is due in part to the regular emergence of new cloud service providers, as well as the routine changing and reconfiguration of the disparate computing platforms, services, assets, supported technical components, and other features offered by the service providers. An analysis architecture determines how to map a particular technical component into the execution environment of any particular service provider with the aid of translation scripts.

Type-to-type analysis for cloud computing technical components with translation scripts

Cloud computing has emerged as an extremely popular implementation option for a wide range of computing services. However, provisioning services into the cloud is an extremely difficult technical challenge. This is due in part to the regular emergence of new cloud service providers, as well as the routine changing and reconfiguration of the disparate computing platforms, services, assets, supported technical components, and other features offered by the service providers. An analysis architecture determines how to map a particular technical component into the execution environment of any particular service provider, including translation through a reference type.

Type-to-type analysis for cloud computing technical components with translation through a reference type

Cloud computing has emerged as an extremely popular implementation option for a wide range of computing services. However, provisioning services into the cloud is an extremely difficult technical challenge. This is due in part to the regular emergence of new cloud service providers, as well as the routine changing and reconfiguration of the disparate computing platforms, services, assets, supported technical components, and other features offered by the service providers. An analysis architecture determines how to map a particular technical component into the execution environment of any particular service provider.

Type-to-type analysis for cloud computing technical components

Determining placement options for technical components of a specified service is a difficult technical challenge. A metadata architecture addresses, in part, the technical challenge by defining a complex metadata collection and attachment mechanism. In one implementation, the metadata architecture defines metadata domains and obtains descriptive metadata for those domains, e.g., metadata for the technical components from multiple disparate sources and across multiple different characteristics of the technical components. The metadata architecture is linked to the technical components and the metadata architecture injects specific metadata subsets into, e.g., a placement pipeline that determines where the technical components may be placed in the extensive provider/platform/service space.

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Sean David Peterson