Abstract: A computer-implemented method according to one aspect includes identifying environmental information for a hyper-converged infrastructure (HCI) system; and adjusting one or more resources allocated to one or more applications within the HCI system, based on the environmental information.

Abstract: Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalities across software products.

Abstract: Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalties across software products.

Abstract: Product data pertaining to a plurality of products is gathered from a plurality of sources. Dependency information for the plurality of products is extracted from the product data. The dependency information is analyzed to determine dependencies for each product of the plurality of products. The dependencies for each product of the plurality of products are displayed to a user.

Abstract: The present invention provides technology neutral process integration (Cloud Resource Planning), and optimization methodology leveraging a business meta-schema format Cloud Data Interchange (CDI) to integrate, enable, and invoke Cloud services. One example is that the present invention provides a management layer at the process level. There can be multiple Cloud implementations/types within a govern enterprise—perhaps utilizing different infrastructure (e.g., hardware of one supplier versus that of another) or different areas of functionality (computing services, storage services, etc). This disclosure provides an abstraction or ‘resource planning’ layer above these core services such that a customer does not have to have knowledge or choose different Cloud types and/or understand or choose each underlying service. As such, it provides a ‘one stop’ portal.

Abstract: Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalities across software products.

Abstract: Methods and arrangements for automatically finding the dependency of a software product on other software products or components. From an install image or directory, a signature is found by deriving the same from a directory structure of the software. Further, a directory tree structure is built and an approximate sub-tree matching algorithm is applied to find commonalties across software products.

Abstract: A system for managing a capacity extreme at a first entity in a supply chain includes a planning application that receives status data for at least the first entity reflecting the capacity extreme at the first entity and generates a plan according to the status data. A manager application receives the plan and, according to the plan, automatically initiates at least one service in an attempt to resolve at least a portion of the capacity extreme through interaction with one or more other entities. The manager application selects the service from among a plurality of available services based on a monetary value to the first entity of a resolution expected to be available using the selected service relative to other services.

Abstract: The present invention provides technology neutral process integration (Cloud Resource Planning), and optimization methodology leveraging a business meta-schema format Cloud Data Interchange (CDI) to integrate, enable, and invoke Cloud services. One example is that the present invention provides a management layer at the process level. There can be multiple Cloud implementations/types within a govern enterprise—perhaps utilizing different infrastructure (e.g., hardware of one supplier versus that of another) or different areas of functionality (computing services, storage services, etc). This disclosure provides an abstraction or ‘resource planning’ layer above these core services such that a customer does not have to have knowledge or choose different Cloud types and/or understand or choose each underlying service. As such, it provides a ‘one stop’ portal.

Abstract: Product data pertaining to a plurality of products is gathered from a plurality of sources. Dependency information for the plurality of products is extracted from the product data. The dependency information is analyzed to determine dependencies for each product of the plurality of products. The dependencies for each product of the plurality of products are displayed to a user.

Abstract: A system (10) for managing a capacity extreme at a first entity (12) in a supply chain includes a planning application (36) that receives status data for at least the first entity (12) reflecting the capacity extreme at the first entity (12) and generates a plan (34) according to the status data. A manager application (44) receives the plan (34) and, according to the plan (34), automatically initiates at least one service in an attempt to resolve at least a portion of the capacity extreme through interaction with one or more other entities (12). The manager application (44) selects the service from among a plurality of available services based on a monetary value to the first entity (12) of a resolution expected to be available using the selected service relative to other services.

Abstract: A system (10) for managing a capacity extreme at a first entity (12) in a supply chain includes a planning application (36) that receives status data for at least the first entity (12) reflecting the capacity extreme at the first entity (12) and generates a plan (34) according to the status data. A manager application (44) receives the plan (34) and, according to the plan (34), automatically initiates at least one service in an attempt to resolve at least a portion of the capacity extreme through interaction with one or more other entities (12). The manager application (44) selects the service from among a plurality of available services based on a monetary value to the first entity (12) of a resolution expected to be available using the selected service relative to other services.

Abstract: A system (10) for managing a capacity extreme at a first entity (12) in a supply chain includes a planning application (36) that receives status data for at least the first entity (12) reflecting the capacity extreme at the first entity (12) and generates a plan (34) according to the status data. A manager application (44) receives the plan (34) and, according to the plan (34), automatically initiates at least one service in an attempt to resolve at least a portion of the capacity extreme through interaction with one or more other entities (12). The manager application (44) selects the service from among a plurality of available services based on a monetary value to the first entity (12) of a resolution expected to be available using the selected service relative to other services.

Abstract: A computer-implemented system for graphical design and automatic generation of supply chain collaboration services capable of understanding supply chain semantics includes a collaboration service designer and a collaboration service generator. The collaboration service designer provides a graphical user interface (GUI), solicits from a user, using the GUI, information regarding the design for the supply chain collaboration service in a sequence of design steps, receives from the user, using the GUI, the solicited information, and generates a file based on the received information that contains a meta-model for the supply chain collaboration service. The collaboration service generator accesses the file containing the meta-model for the supply chain collaboration service. The collaboration service generator, using the meta-model, automatically generates the supply chain collaboration service, which is capable of understanding of supply chain semantics for an underlying supply chain.