Abstract: The system and method for determining fuzzy cause and effect relationships in an intelligent workload management system described herein may combine potential causes and effects captured from various different sources associated with an information technology infrastructure with substantially instantaneous feedback mechanisms and other knowledge sources. As such, fuzzy correlation logic may then be applied to the combined information to determine potential cause and effect relationships and thereby diagnose problems and otherwise manage interactions that occur in the infrastructure. For example, information describing potential causes and potential effects associated with an operational state of the infrastructure may be captured and combined, and any patterns among the information that describes the multiple potential causes and effects may then be identified.

Abstract: Techniques for workload coordination are provided. An automated discovery service identifies resources with hardware and software specific dependencies for a workload. The dependencies are made generic and the workload and its configuration with the generic dependencies are packaged. At a target location, the packaged workload is presented and the generic dependencies automatically resolved with new hardware and software dependencies of the target location. The workload is then automatically populated in the target location.

Abstract: The system and method for determining fuzzy cause and effect relationships in an intelligent workload management system described herein may combine potential causes and effects captured from various different sources associated with an information technology infrastructure with substantially instantaneous feedback mechanisms and other knowledge sources. As such, fuzzy correlation logic may then be applied to the combined information to determine potential cause and effect relationships and thereby diagnose problems and otherwise manage interactions that occur in the infrastructure. For example, information describing potential causes and potential effects associated with an operational state of the infrastructure may be captured and combined, and any patterns among the information that describes the multiple potential causes and effects may then be identified.

Abstract: The system and method for determining fuzzy cause and effect relationships in an intelligent workload management system described herein may combine potential causes and effects captured from various different sources associated with an information technology infrastructure with substantially instantaneous feedback mechanisms and other knowledge sources. As such, fuzzy correlation logic may then be applied to the combined information to determine potential cause and effect relationships and thereby diagnose problems and otherwise manage interactions that occur in the infrastructure. For example, information describing potential causes and potential effects associated with an operational state of the infrastructure may be captured and combined, and any patterns among the information that describes the multiple potential causes and effects may then be identified.

Abstract: Techniques for auditing and controlling network services are provided. A proxy is interposed between a principal and a network service. Interactions between the principal and the service pass through the proxy. The proxy selectively raises events and evaluates policy based on the interactions for purposes of auditing and controlling the network service.

Abstract: Techniques for auditing and controlling network services are provided. A proxy is interposed between a principal and a network service. Interactions between the principal and the service pass through the proxy. The proxy selectively raises events and evaluates policy based on the interactions for purposes of auditing and controlling the network service.

Abstract: The system and method for determining fuzzy cause and effect relationships in an intelligent workload management system described herein may combine potential causes and effects captured from various different sources associated with an information technology infrastructure with substantially instantaneous feedback mechanisms and other knowledge sources. As such, fuzzy correlation logic may then be applied to the combined information to determine potential cause and effect relationships and thereby diagnose problems and otherwise manage interactions that occur in the infrastructure. For example, information describing potential causes and potential effects associated with an operational state of the infrastructure may be captured and combined, and any patterns among the information that describes the multiple potential causes and effects may then be identified.

Abstract: Techniques for workload coordination are provided. An automated discovery service identifies resources with hardware and software specific dependencies for a workload. The dependencies are made generic and the workload and its configuration with the generic dependencies are packaged. At a target location, the packaged workload is presented and the generic dependencies automatically resolved with new hardware and software dependencies of the target location. The workload is then automatically populated in the target location.

Abstract: The system and method for determining fuzzy cause and effect relationships in an intelligent workload management system described herein may combine potential causes and effects captured from various different sources associated with an information technology infrastructure with substantially instantaneous feedback mechanisms and other knowledge sources. As such, fuzzy correlation logic may then be applied to the combined information to determine potential cause and effect relationships and thereby diagnose problems and otherwise manage interactions that occur in the infrastructure. For example, information describing potential causes and potential effects associated with an operational state of the infrastructure may be captured and combined, and any patterns among the information that describes the multiple potential causes and effects may then be identified.

Abstract: Techniques for auditing and controlling network services are provided. A proxy is interposed between a principal and a network service. Interactions between the principal and the service pass through the proxy. The proxy selectively raises events and evaluates policy based on the interactions for purposes of auditing and controlling the network service.

Abstract: Techniques for workload coordination are provided. An automated discovery service identifies resources with hardware and software specific dependencies for a workload. The dependencies are made generic and the workload and its configuration with the generic dependencies are packaged. At a target location, the packaged workload is presented and the generic dependencies automatically resolved with new hardware and software dependencies of the target location. The workload is then automatically populated in the target location.

Abstract: Techniques for auditing and controlling network services are provided. A proxy is interposed between a principal and a network service. Interactions between the principal and the service pass through the proxy. The proxy selectively raises events and evaluates policy based on the interactions for purposes of auditing and controlling the network service.

Abstract: Techniques for workload coordination are provided. An automated discovery service identifies resources with hardware and software specific dependencies for a workload. The dependencies are made generic and the workload and its configuration with the generic dependencies are packaged. At a target location, the packaged workload is presented and the generic dependencies automatically resolved with new hardware and software dependencies of the target location. The workload is then automatically populated in the target location.

Abstract: The system and method for determining fuzzy cause and effect relationships in an intelligent workload management system described herein may combine potential causes and effects captured from various different sources associated with an information technology infrastructure with substantially instantaneous feedback mechanisms and other knowledge sources. As such, fuzzy correlation logic may then be applied to the combined information to determine potential cause and effect relationships and thereby diagnose problems and otherwise manage interactions that occur in the infrastructure. For example, information describing potential causes and potential effects associated with an operational state of the infrastructure may be captured and combined, and any patterns among the information that describes the multiple potential causes and effects may then be identified.