Abstract: An application performance analyzer adapted to analyze the performance of one or more applications running on IT infrastructure, comprises: a data collection engine collecting performance metrics for one or more applications running on the IT infrastructure; an anomaly detection engine analyzing the performance metrics and detecting anomalies, i.e. performance metrics whose values deviate from historic values with a deviation that exceeds a predefined threshold; a correlation engine detecting dependencies between plural anomalies, and generating anomaly clusters, each anomaly cluster consisting of anomalies that are correlated through one or more of the dependencies; a ranking engine ranking anomalies within an anomaly cluster; and a source detection engine pinpointing a problem source from the lowest ranked anomaly in an anomaly cluster.

Abstract: A method and computer device for storage and retrieval of a data object on a storage medium. The method includes steps of disassembling the data object into a predetermined number of redundant sub blocks, storing the redundant sub blocks on the storage medium, retrieving at least a predetermined multiple of a minimal spreading requirement of the redundant sub blocks from the storage medium, and assembling the data object from any combination of a particular number of the redundant sub blocks, the particular number corresponding to a predetermined multiple of a minimal spreading requirement. The computer device includes modules for performing the steps.

Abstract: An application performance analyzer adapted to analyze the performance of one or more applications running on IT infrastructure, comprises: a data collection engine collecting performance metrics for one or more applications running on the IT infrastructure; an anomaly detection engine analyzing the performance metrics and detecting anomalies, i.e. performance metrics whose values deviate from historic values with a deviation that exceeds a predefined threshold; a correlation engine detecting dependencies between plural anomalies, and generating anomaly clusters, each anomaly cluster consisting of anomalies that are correlated through one or more of the dependencies; a ranking engine ranking anomalies within an anomaly cluster; and a source detection engine pinpointing a problem source from the lowest ranked anomaly in an anomaly cluster.

Abstract: An application performance management system is provided, which is adapted to analyze the performance of one or more applications running on information technology (IT) infrastructure. The application performance management system includes a data collector, an anomaly detector, an anomaly correlator, an anomaly ranking unit, and a source problem detector. The data collector collects performance metrics for one or more applications running on the IT infrastructure. The anomaly detector analyzes the performance metrics and detects anomalies, which may include performance metrics whose values deviate from historic values with a deviation that exceeds a predefined threshold. The anomaly correlator detects dependencies between plural anomalies and generates anomaly clusters. Each anomaly cluster includes anomalies that are correlated through one or more of the dependencies. The anomaly ranking unit ranks anomalies within an anomaly cluster.

Abstract: A method and computer device for storage and retrieval of a data object on a storage medium. The method includes steps of disassembling the data object into a predetermined number of redundant sub blocks, storing the redundant sub blocks on the storage medium, retrieving at least a predetermined multiple of a minimal spreading requirement of the redundant sub blocks from the storage medium, and assembling the data object from any combination of a particular number of the redundant sub blocks, the particular number corresponding to a predetermined multiple of a minimal spreading requirement. The computer device includes modules for performing the steps.

Abstract: A method and computer device for storage and retrieval of a data object on a storage medium. The method includes steps of disassembling the data object into a predetermined number of redundant sub blocks, storing the redundant sub blocks on the storage medium, retrieving at least a predetermined multiple of a minimal spreading requirement of the redundant sub blocks from the storage medium, and assembling the data object from any combination of a particular number of the redundant sub blocks, the particular number corresponding to a predetermined multiple of a minimal spreading requirement. The computer device includes modules for performing the steps.

Abstract: An application performance analyzer adapted to analyze the performance of one or more applications running on IT infrastructure, comprises: a data collection engine collecting performance metrics for one or more applications running on the IT infrastructure; an anomaly detection engine analyzing the performance metrics and detecting anomalies, i.e. performance metrics whose values deviate from historic values with a deviation that exceeds a predefined threshold; a correlation engine detecting dependencies between plural anomalies, and generating anomaly clusters, each anomaly cluster consisting of anomalies that are correlated through one or more of the dependencies; a ranking engine ranking anomalies within an anomaly cluster; and a source detection engine pinpointing a problem source from the lowest ranked anomaly in an anomaly cluster.

Abstract: A method and computer device for storage and retrieval of a data object on a storage medium. The method includes steps of disassembling the data object into a predetermined number of redundant sub blocks, storing the redundant sub blocks on the storage medium, retrieving at least a predetermined multiple of a minimal spreading requirement of the redundant sub blocks from the storage medium, and assembling the data object from any combination of a particular number of the redundant sub blocks, the particular number corresponding to a predetermined multiple of a minimal spreading requirement. The computer device includes modules for performing the steps.

Abstract: A method and computer device for storage and retrieval of a data object on a storage medium. The method includes steps of disassembling the data object into a predetermined number of redundant sub blocks, storing the redundant sub blocks on the storage medium, retrieving at least a predetermined multiple of a minimal spreading requirement of the redundant sub blocks from the storage medium, and assembling the data object from any combination of a particular number of the redundant sub blocks, the particular number corresponding to a predetermined multiple of a minimal spreading requirement. The computer device includes modules for performing the steps.

Abstract: A distributed object storage system includes several performance optimizations with respect to storing very small data objects, very large data objects and CRC calculations.

Abstract: A method and computer device for storage and retrieval of a data object on a storage medium. The method includes steps of disassembling the data object into a predetermined number of redundant sub blocks, storing the redundant sub blocks on the storage medium, retrieving at least a predetermined multiple of a minimal spreading requirement of the redundant sub blocks from the storage medium, and assembling the data object from any combination of a particular number of the redundant sub blocks, the particular number corresponding to a predetermined multiple of a minimal spreading requirement. The computer device includes modules for performing the steps.

Abstract: A distributed object storage system includes several performance optimizations with respect to storing very small data objects, very large data objects and CRC calculations.