Dell Products Inc.

Dell & Products L.p.

Vijayasimha Reddy Naga

Sudhir Vittal Shetty

Prakash Nara

Madhav Karri

Dahir Nur Herzi

Venkata Bala Koteswararao Donepudi

Kathleen A Hattaway

Michael Emery Brown

Thomas L Watson

Cyril Jose

Mukesh Sharma

Zoheb Khan

Nitesh Kumar Anand

Deepak Nagarajegowda

Muralidhar Kolli

Methods and systems for managing performance of workloads are disclosed. The performance of the workloads may be managed by choosing a data storage device for the performance of a workload. The data storage device may be chosen by selecting the data storage of data storage devices with a highest reliability prediction. The reliability prediction of the data storage device may be a likelihood of the data storage device of a data processing system to retain the data while performing the workload. The data processing system may be chosen by selecting the data processing system of data processing systems with the highest reliability prediction. The reliability prediction of the data processing system may be a weighted sum of reliability predictions and weights of the data storage devices.

Use of reliability predictions for selection of data storage devices

A system for continuous manageability of Kubernetes clusters is described. A system identifies a node, in a cluster of nodes, which failed to communicate with the cluster of nodes. The system identifies an application, which executed on the identified node, and which enabled continuous availability of cluster management for nodes in the cluster until when the identified node failed. The system identifies another node, which is already in the cluster of nodes, and which satisfies a prerequisite for executing the identified application, as a replacement node for the identified node that failed. The system installs the identified application on the replacement node in the cluster. The system enables, by the replacement node executing the identified application, continuous availability of cluster management for multiple nodes in the cluster.

Continuous manageability of Kubernetes clusters

An information handling system includes first and second memories, and a processor. The first memory stores user settings for performing a search in a system management console. The second memory stores data associated with components of the system management console. The processor receives multiple user defined weights, and each of the user defined weights is associated with a different search criterion of multiple search criteria. Based on the received user defined weights, the processor determines updated weights for each of the search criteria. The processor stores the updated weights for each of the search criteria in the user setting of the first memory. The processor receives a search query, and provides search results based on the search query and the updated weights for each of the search criteria. The search results include data from the second memory.

User-driven dynamic system management search

A system, method, and computer-readable medium for performing a telemetry aggregation operation. The telemetry aggregation operation includes: associating a data center asset from a plurality of data center assets with a data center asset group, the associating being based upon a telemetry information response time of the data center asset; identifying a telemetry aggregation cycle time for the data center asset group; collecting telemetry information from the data center asset of the plurality of data center assets; and, aggregating the telemetry information according to the telemetry aggregation cycle time.

Adaptive segmentation of data center asset telemetry information

A first information handling system may receive a telemetry metric report from a client information handling system. The first information handling system may determine that one or more characteristics of the telemetry metric report do not match one or more predetermined telemetry metric report characteristics. The first information handling system may perform one or more corrective actions based, at least in part, on the determination that the one or more characteristics of the telemetry metric report do not match one or more predetermined telemetry metric report characteristics.

In-flight detection of server telemetry report drift

A device management system that receives a first service request message for a remote device node, the request including an address identifier and a connection profile identifier. The system retrieves from a database protocol configuration information associated with the service request. The system connects to the remote device using the protocol configuration information and iterates through device packs and identifies a device type and support for in-band and out-of band application protocols for the remote device. The system retrieves and stores the retrieved device type and in-band and out-of band application protocols. The system further receives a second service request message that includes a device identifier of the remote device and iteratively connect to the remote device associated with the device identifier using each of the in-band and out-of band application protocols and retrieves an inventory of management operations associated with each application protocol.

Growing community of inventors

Georgetown, TX, United States of America

Vijayasimha Reddy Naga