Abstract: A system comprehensively tests each feasible path in a policy-based Extensible Markup Language (XML) workflow. The system may receive an input workflow and parse workflow (or proxy code of the workflow) to construct a policy control flow graph. The system may identify paths in the policy control flow graph, such as each feasible path in the policy control flow graph. The system may determine path constraints for the identified paths, where the path constraints identify path conditions for traversing the identified path in the policy control flow graph. Then, the system may generate a set of test inputs for the workflow using the path constraints that, when input into the policy-based XML workflow, cause the workflow to traverse the identified paths.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes (e.g., consolidation strategies) usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform off-line modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.

Abstract: According to an example, an adaptive fault diagnosis system may include a memory storing machine readable instructions to receive metrics and events from an enterprise system, and use a substitution graph to determine if a received metric or a received event belongs to a cluster that includes one or more correlated metrics and/or events grouped based on similarity. If the received metric or the received event belongs to the cluster, the memory may further store machine readable instructions to use a detection graph to determine if the received metric or the received event is identifiable to form a fault pattern by traversing a fault path of the detection graph. Further, the memory may further store machine readable instructions to diagnose a fault based on the traversal of the fault path of the detection graph. The system may include a processor to implement the machine readable instructions.

Abstract: API analytics systems and methods are provided. Frequently occurring API usage patterns may be determined from API call data collected from across an API ecosystem. Alternatively or in addition, a classification structure, such as a decision tree, may be generated from the API usage patterns. A type of activity that resulted in a set of API calls being invoked may be determined from the classification structure. A similarity or difference between the set of API calls and the frequently occurring API usage patterns may also be determined and/or identified.

Abstract: The differentiated service-based graceful degradation layer (DSGDL) allows cloud-based architectures to operate through and recover from periods of limited capability. The DSGDL protects and continues serving higher priority requests with the best possible response even as the underlying cloud-based services deteriorate. The DSGDL offloads lower priority requests to lower-grade secondary capability that can be dynamically provisioned in order to reserve the best capability for maintaining high priority service (e.g., by re-directing lower priority requests to a slightly out-of-date cached dataset, and reserve the primary consistent database for higher priority requests). The DSGDL 1) implements an overlay network over existing cloud services to route and enforce priority requests, and 2) provisions on-demand computing nodes and sites to provide secondary capability for service requests as needed.

Abstract: API analytics systems and methods are provided. Frequently occurring API usage patterns may be determined from API call data collected from across an API ecosystem. Alternatively or in addition, a classification structure, such as a decision tree, may be generated from the API usage patterns. A type of activity that resulted in a set of API calls being invoked may be determined from the classification structure. A similarity or difference between the set of API calls and the frequently occurring API usage patterns may also be determined and/or identified.

Abstract: The differentiated service-based graceful degradation layer (DSGDL) allows cloud-based architectures to operate through and recover from periods of limited capability. The DSGDL protects and continues serving higher priority requests with the best possible response even as the underlying cloud-based services deteriorate. The DSGDL offloads lower priority requests to lower-grade secondary capability that can be dynamically provisioned in order to reserve the best capability for maintaining high priority service (e.g., by re-directing lower priority requests to a slightly out-of-date cached dataset, and reserve the primary consistent database for higher priority requests). The DSGDL 1) implements an overlay network over existing cloud services to route and enforce priority requests, and 2) provisions on-demand computing nodes and sites to provide secondary capability for service requests as needed.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes (e.g., consolidation strategies) usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform off-line modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.

Abstract: The distributed computing backup and recovery (DCBR) system and method provide backup and recovery for distributed computing models (e.g., NoSQL) The DCBR system extends the protections from server node-level failure and introduces persistence in time so that the evolving data set may be stored and recovered to a past point in time. The DCBR system, instead of performing backup and recovery for an entire dataset, may be configured to apply to a subset of data. Instead of keeping or recovering snapshots of the entire dataset which requires the entire cluster, the DCBR system identifies the particular nodes and/or archive files where the dataset resides so that backup or recovery may be done with a much smaller number of nodes.

Abstract: API analytics systems and methods are provided. Frequently occurring API usage patterns may be determined from API call data collected from across an API ecosystem. Alternatively or in addition, a classification structure, such as a decision tree, may be generated from the API usage patterns. A type of activity that resulted in a set of API calls being invoked may be determined from the classification structure. A similarity or difference between the set of API calls and the frequently occurring API usage patterns may also be determined and/or identified.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.

Abstract: Embodiments of the claimed subject matter provide a process and system for designing composite application systems. One embodiment of the claimed subject matter is a process of designing a composite application system to meet an application requirement. The process includes defining a use case scenario performed by a composite application system to meet the application requirement, integrating the use case scenario with an execution tool, and specifying an underlying infrastructure for the system design, wherein, the entire process is performed within an integrated software application.

Abstract: A system comprehensively tests each feasible path in a policy-based Extensible Markup Language (XML) workflow. The system may receive an input workflow and parse workflow (or proxy code of the workflow) to construct a policy control flow graph. The system may identify paths in the policy control flow graph, such as each feasible path in the policy control flow graph. The system may determine path constraints for the identified paths, where the path constraints identify path conditions for traversing the identified path in the policy control flow graph. Then, the system may generate a set of test inputs for the workflow using the path constraints that, when input into the policy-based XML workflow, cause the workflow to traverse the identified paths.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.

Abstract: The distributed computing backup and recovery (DCBR) system and method provide backup and recovery for distributed computing models (e.g., NoSQL). The DCBR system extends the protections from server node-level failure and introduces persistence in time so that the evolving data set may be stored and recovered to a past point in time. The DCBR system, instead of performing backup and recovery for an entire dataset, may be configured to apply to a subset of data. Instead of keeping or recovering snapshots of the entire dataset which requires the entire cluster, the DCBR system identifies the particular nodes and/or archive files where the dataset resides so that backup or recovery may be done with a much smaller number of nodes.

Abstract: According to an example, an adaptive fault diagnosis system may include a memory storing machine readable instructions to receive metrics and events from an enterprise system, and use a substitution graph to determine if a received metric or a received event belongs to a cluster that includes one or more correlated metrics and/or events grouped based on similarity. If the received metric or the received event belongs to the cluster, the memory may further store machine readable instructions to use a detection graph to determine if the received metric or the received event is identifiable to form a fault pattern by traversing a fault path of the detection graph. Further, the memory may further store machine readable instructions to diagnose a fault based on the traversal of the fault path of the detection graph. The system may include a processor to implement the machine readable instructions.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform off-line modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.

Abstract: A cloud services monitoring system (CSMS) helps a consumer of cloud computing resources determine the state of the cloud computing resources available to the consumer. The CSMS is particularly effective for cloud models where the consumer of the cloud computing resources is not the same as the provider of the cloud resource. The CSMS also provides mechanisms for adjusting operations actions to preserve service guarantees for the consumer. In that regard, the CSMS dynamically adjusts operations actions in response to the state of the cloud, rather than executing fixed pre-determined operations actions that are not tailored to the monitored conditions.

Abstract: A cloud services monitoring system (CSMS) helps a consumer of cloud computing resources determine the state of the cloud computing resources available to the consumer. The CSMS is particularly effective for cloud models where the consumer of the cloud computing resources is not the same as the provider of the cloud resource. The CSMS 102 also provides mechanisms for adjusting operations actions to preserve service guarantees for the consumer. In that regard, the CSMS dynamically adjusts operations actions in response to the state of the cloud, rather than executing fixed pre-determined operations actions that are not tailored to the monitored conditions.

Abstract: Embodiments of the claimed subject matter provide a process and system for designing composite application systems. One embodiment of the claimed subject matter is a process of designing a composite application system to meet an application requirement. The process includes defining a use case scenario performed by a composite application system to meet the application requirement, integrating the use case scenario with an execution tool, and specifying an underlying infrastructure for the system design, wherein, the entire process is performed within an integrated software application.