Copan Systems Inc.

Other

Storage Technology Corporation

Aumni Data, Inc.

Copan System, Inc.

Schneider Electric It Corporation

Alumni Data Inc.

Aloke Guha

Chris T Santilli

Gary McMillian

Joan Wrabetz

Christopher T Santilli

Will Hays Layton

Kim Bang Le

Michael T Rowan

Michael Anthony

Bahareh Ghaffari

James Boyd Lenehan

Kelly E Long

Shumin Wu

Jeffrey Cousins

Gary B McMillian

Christopher Rocca

Shridhar Venkatraman

Adam Matusiak

Michael D Anthony

Venky Madireddi

Michael Henriksen

William White

Steve Fredrick Hartung

A computerized method for optimizing cloud application performance, including the step of monitoring of a cloud application. The method includes the step of building a full-stack view of the cloud application. The method includes the step of providing an application model. The method includes the step of mapping one or more cloud application performance needs to a set of cloud-resources based on the application model. The method includes the step of detecting a performance problem with the cloud application. The method includes the step of dynamically adjusting a specified layer of the cloud application to meet an application performance SLO. The method includes the step of, as cloud resources are consumed, determining a real-time aggregate cost for a specified application operation.

Methods and systems for cloud application optimization

In one aspect, a computerized method for managing autonomous cloud application operations includes the step of providing a cloud-based application. The method includes the step of implementing a discovery phase on the cloud-based application. The discovery phase comprises ingesting data from the cloud-based application and building an application graph of the cloud-based application. The application graph represents a structural topology and a set of directional dependencies within and across the layers of the cloud-based application. The method includes the step of, with the application graph, implementing anomaly detection on the cloud-based application by building a set of predictive behavior models from a predictive understanding of the complete application using a priori curated knowledge and one or more machine learning (ML) models. The set of predictive behavior models fingerprints a behavior of the cloud-based application behavior. The method predicts expected values of key indicators. The method detects one or more anomalies in the cloud-based application. The method includes the step of implementing causal analysis of the one or more detected anomalies. The causal analysis includes receiving a set of relevant labels and a set of metadata related to the one or more detected anomalies, and the structure of the application graph. The method generates a causal analysis information. The method includes the step of implementing problem classification by classifying the one or more anomalies and causal analysis information into a taxonomy. The taxonomy includes a set of details on the nature of the problem and a set of remediation actions.

Methods and systems for autonomous cloud application operations

Techniques for power analysis for data centers are disclosed. In one particular exemplary embodiment, the techniques may be realized as a method for power analysis for a plurality of computing platform components comprising receiving information associated with a component, retrieving, using a computer processor, electronically stored data associated with the component, estimating power usage of the component based at least in part on the stored data, and outputting an indicator of power usage.

Techniques for power analysis

Various embodiments of the present invention disclose a method for Business Intelligence (BI) metrics on unstructured data. Unstructured data is collected from numerous data sources that include unstructured data as ingested data. The ingested data is indexed and represents hyperlink and extracted data and metadata for each document. Thereafter, the ingested data is automatically classified into one or more relevance classes. Further, numerous analytics are performed on the classified data to generate business intelligence metrics that may be presented on an access device operated by a user.

Method and system for business intelligence analytics on unstructured data

A method and system for adaptive classification during information retrieval from unstructured data are provided. The method includes receiving input from a user defining a classification. A sample set of unstructured data based on the user defined classification defined is determined. The sample set of unstructured data is analyzed to determine a classification mapping that maps attributes of the sample set of unstructured data to class labels for the classification. The attributes of a set of data objects in a second set of unstructured data are indexed and one or more data objects in the set of data objects are mapped to the class label based on the classification mapping. Feedback based on the user's response to an interaction with results is determined using the class label. Finally, adaptive classification mapping is performed based on analysis of feedback by adjusting the sample set of data objects.

Adaptive data classification for data mining

In one embodiment, input is received from a user defining a classification and an analytic for the classification. Multiple classifications and analytics may be defined by a user. A definition of relevance parameters is determined that characterize the classification and a set of analytics measures associated with the analytic. The definition may be for the classification. Unstructured data and structured data are analyzed based on the definition of the relevance parameters to determine relevant data in the unstructured data and the structured data. The relevant data being data that is determined to be relevant to the classification defined by the user. An index of the terms from the relevant data is determined. The index is useable by an analytics tool to provide results for queries of the unstructured data and structured data. The query may be used within the classification such that targeted results are provided using the index and the relevant data to the classification. Thus, queries from different classifications may be performed efficiently using data determined to be relevant to the classification.

Adaptive archive data management

A system and method for coupling a host to a drive in a high-capacity data storage system are disclosed. The data storage system comprises a number of drives arranged in a hierarchical manner. A control system is provided for controlling input/output of data and managing control signals. The control system comprises a hierarchy of controllers and switches. The control system receives a request for a drive from a host and couples the host to the requested drive through the hierarchy of controllers.

High-density storage systems using hierarchical interconnect

An apparatus and a method for improving the fault tolerance of storage systems by replacing disk drives, which are about to fail, are disclosed. The set of disk drives in a storage system are monitored to identify failing disk drives. A processing unit identifies the failing disk drive and selects a spare disk drive to replace the failing disk drive. The selected spare disk drive is powered on, and data from the failing disk drive is copied to the selected spare disk drive. A memory unit stores attributes and sensor data for the disk drives in the storage system. The attributes and sensor data are used by the processing unit to identify a failing disk drive. Attributes for disk drives are obtained by using SMART, and sensor data is obtained from environmental sensors such as temperature and vibration sensors.

Method and apparatus for efficient fault-tolerant disk drive replacement in raid storage systems

Spare disk drive management in a storage system. The storage system comprises disk drives and spare disk drives. Spare disk drives are initially kept in power-off state. The storage system detects the failure of a disk drive and selects a spare disk drive to replace the failed disk drive. The spare disk drive is selected on the basis of spare selection criteria. The selected spare disk drive is powered-on and replaces the failed disk drive. Data on the failed disk drive can be reconstructed on the spare disk drive by using RAID parity techniques.

Method and apparatus for just in time RAID spare drive pool management

A method for processing data on a particular storage device in a plurality of storage devices is disclosed. A system and a computer program product for processing data on a particular storage device in a plurality of storage devices are also disclosed. All the storage devices from among the plurality of storage devices are not powered-on at the same time. A storage device, which is powered-off is selected for background processing. Further, a data-enhancing operation is selected. The selected storage device is powered on and the selected data-enhancing operation is processed on the storage device.

Background processing of data in a storage system

Methods for preventing the failure of disk drives in storage systems are disclosed. A system and a computer program product for preventing the failure are also disclosed. Factors relating to the aging or early onset of errors in a disk drive are monitored. These factors are then compared to thresholds. In case the thresholds are exceeded, an indication for the replacement of the disk drive is given. Sudden rises in the factors are also used to indicate the impeding failure of disk drives.

Method and system for proactive drive replacement for high availability storage systems

An interconnecting unit and method for data communication between a plurality of computer hosts and a plurality of storage devices. The interconnecting unit couples the hosts to the storage devices and enables the data communication. The interconnection includes a plurality device control units. Each of the device control unit allows multiple commands to be distributed to multiple storage devices. The communication through the interconnecting unit is strong enough to tolerate failure across one connection path between the hosts and the storage devices.

Method and apparatus for storage command and data router

A method for preparing data units for access in a data storage system is disclosed. The data storage system includes multiple storage devices having data units. All the storage devices of the data storage system are not powered on at the same time. The method includes preparing and storing the auxiliary data. The auxiliary data is prepared for a data unit on a storage device that will be powered off during an access request of the data unit. The auxiliary data is stored on the storage devices so that the auxiliary data is likely to be available on a powered-on storage device when the data unit is the subject of an access request.

Growing community of inventors

Louisville, CO, United States of America

Aloke Guha