Abstract: Methods and systems for managing data processing systems are disclosed. Data processing systems may be managed by monitoring for failure of a storage device. The storage device may be monitored by obtaining use data and diagnostic data for a storage device. The use data may be obtained to generate predicted future use data. The use data and the predicted future use data may be used to generate a use quantification. The use quantification and the diagnostic data may be ingested in a predictive algorithm to obtain a prediction of the operation of a storage device. The prediction may indicate the likelihood for failure of the storage device.

Abstract: A system, method, and computer-readable medium for performing a data center monitoring and management operation, The data center monitoring and management operation includes receiving data center asset data for a plurality of data center assets, the data center asset data comprising data center asset fan associated data; providing the data center asset fan associated data to a fan failure prediction model; and, training the fan failure prediction model using the data center asset fan associated data.

Abstract: A system, method, and computer-readable medium for performing a data center monitoring and management operation, The data center monitoring and management operation includes receiving data center asset data for a plurality of data center assets, the data center asset data comprising a data center asset telemetry dataset; storing the data center asset telemetry dataset in a telemetry dataset array, the telemetry dataset array comprising a plurality of telemetry dataset array rows; generating a dimensionally reduced telemetry dataset from the telemetry dataset array, the dimensionally reduced telemetry dataset having fewer rows than the telemetry dataset array; and, training a machine learning model using the dimensionally reduced telemetry dataset.

Abstract: A system, method, and computer-readable medium for performing a data center monitoring and management operation, The data center monitoring and management operation includes receiving data center data for a data center, the data center data comprising data center memory associated data; receiving data center asset data for a plurality of data center assets, the data center asset data comprising data center asset memory associated data; providing the data center memory associated data and the data center asset memory associated data to a memory failure prediction model; and, training the memory failure prediction model using the data center memory associated data and the data center asset memory associated data.

Abstract: Methods, apparatus, and processor-readable storage media for scalable capacity forecasting in storage systems using a machine learning model are provided herein.

Abstract: A system, method, and computer-readable medium for performing a data center monitoring and management operation, The data center monitoring and management operation includes receiving data center data for a data center, the data center data comprising data center memory associated data; receiving data center asset data for a plurality of data center assets, the data center asset data comprising data center asset memory associated data; providing the data center memory associated data and the data center asset memory associated data to a memory failure prediction model; and, training the memory failure prediction model using the data center memory associated data and the data center asset memory associated data.

Abstract: A system, method, and computer-readable medium for performing a data center monitoring and management operation, The data center monitoring and management operation includes receiving data center asset data for a plurality of data center assets, the data center asset data comprising data center asset fan associated data; providing the data center asset fan associated data to a fan failure prediction model; and, training the fan failure prediction model using the data center asset fan associated data.

Abstract: Methods, apparatus, and processor-readable storage media for automatically determining storage system data breaches using machine learning techniques are provided herein. An example computer-implemented method includes configuring a storage system by designating at least one storage object within the storage system for storing data identified as to be protected from breach; generating at least one multivariate data breach probability function using historical performance data of the designated storage object(s) and/or historical capacity data of the designated storage object(s); calculating at least one data breach score using the at least one multivariate data breach probability function, one or more machine learning techniques, and additional performance data of the designated storage object(s) and/or additional capacity data of the designated storage object(s); and performing one or more automated actions based at least in part on the at least one data breach score.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: monitoring a plurality of data center assets contained within a data center; receiving a data center asset data stream, the data center asset data stream comprising a plurality of data center events, at least some of the plurality of data center events having associated data center issues; capturing asset alert data from the plurality of data center events; and, performing a data center issue analysis operation, the data center issue analysis operation using the asset alert data from the plurality of data center events, the data center issue analysis operation identifying a data center asset from the plurality of data center assets affected by the particular data center issue.

Abstract: A denial-of-service detection system includes a denial-of-service detection subsystem coupled to a plurality of storage systems via a network. The denial-of-service detection subsystem receives current first storage system data for each of a plurality of different storage system operating metrics from a first storage system included in the plurality of storage systems.

Abstract: Systems and methods are provided for providing recommended resolutions to issues occurring during operation of an Information Handling System (IHS). Similar issues, each associated with resolution information specifying one or more recommended resolutions, are identified within an issue repository. Collaborative filtering is utilized on the similar issues and associated resolution information to generate a first ranked list. Collaborative filtering is also utilized on a subset of the similar issues and associated resolution information to generate a second ranked list of the subset of similar issues and associated resolution information, where the subset of similar issues are each selected based on being within a time proximity to the reported issue. A linear regression is utilized on the first ranked list and the second ranked list to generate a ranked list of recommended resolutions to the reported issue that is then provided to an administrator.

Abstract: Methods, apparatus, and processor-readable storage media for automatically processing storage system data and generating visualizations representing differential data comparisons are provided herein. An example computer-implemented method includes obtaining current data from a first storage system and historical data from the first storage system and/or one or more additional storage systems; determining, for the first storage system, at least one current state value for at least one storage system parameter by processing the current data using a first hashing algorithm; determining, for the first storage system with respect to the first storage system and/or the additional storage systems, at least one differential state value for the at least one storage system parameter by processing the current data and the historical data using a second hashing algorithm; and generating data visualizations based on the current state value(s) and/or the differential state value(s).

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: identifying a plurality of assets within a data center; monitoring usage of the plurality of assets within the data center; generating data center asset profile data based upon the monitoring; identifying a plurality of asset configurations related to the asset profile data; ranking the plurality of asset configurations based upon the data center asset profile data; and, generating a recommended asset configuration recommendation based upon the ranking.

Abstract: The disclosed systems and methods are directed to a computer-implemented method for use in designing a service. In at least one embodiment, a method includes designing a service with one or more generic virtual network functions (VNFs), where the generic VNFs are defined independent of vendor sourcing information. One or more trained machine learning (ML) models are used to identify VNFs available from VNF vendors that may source one or more VNFs similar to the generic VNFs. The service is implemented using VNFs provided by one or more VNF vendors, where the VNFs provided by the one or more VNF vendors have network functionality generating similar to the one or generic VNFs.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: identifying a plurality of assets within a data center; generating data center asset profile data for each of the plurality of assets within the data center; identifying a plurality of asset configurations related to the asset profile data; and, calculating costs associated with the plurality of asset configurations related to the asset profile data.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: identifying a plurality of assets within a data center; monitoring usage of the plurality of assets within the data center; generating data center asset profile data based upon the monitoring; identifying a plurality of asset configurations related to the asset profile data; ranking the plurality of asset configurations based upon the data center asset profile data; and, generating a recommended asset configuration recommendation based upon the ranking.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: collecting historical asset data; producing a prediction model associated with the historical asset data; identifying semantic changes in telemetry of the historical asset data; receiving a data center asset data stream, the data center asset data stream comprising a plurality of data center events, at least some of the plurality of data center events having associated data center issues; identifying telemetry changes and events of interest for the plurality of data center events; and, determining a context of changes for the plurality of data center events, the determining using the prediction model associated with the historical asset data.

Abstract: A system, method, and computer-readable medium are disclosed for performing a data center monitoring and management operation. The data center monitoring and management operation includes: monitoring a plurality of data center assets contained within a data center; receiving a data center asset data stream, the data center asset data stream comprising a plurality of data center events, at least some of the plurality of data center events having associated data center issues; capturing asset alert data from the plurality of data center events; and, performing a data center issue analysis operation, the data center issue analysis operation using the asset alert data from the plurality of data center events, the data center issue analysis operation identifying a data center asset from the plurality of data center assets affected by the particular data center issue.

Abstract: In some examples, before saving a file, a device analyzes contents (e.g., text and images) of the file to create a bag of words. The device performs Latent Dirichlet Allocation of the bag of words to determine topics included in the file and orders the topics in descending order of frequency. The device generates a particular name of the file based on the ordered topics and automatically save (or suggest saving) the file with the particular name. The device determines, based on the ordered topics, a folder name of a folder in which to store the file. If an existing folder has the folder name, then the device saves the file in the existing folder. If not, then the device creates a new folder with the folder name and saves the file in the new folder.

Abstract: Systems and methods are provided for providing recommended resolutions to issues occurring during operation of an Information Handling System (IHS). Similar issues, each associated with resolution information specifying one or more recommended resolutions, are identified within an issue repository. Collaborative filtering is utilized on the similar issues and associated resolution information to generate a first ranked list. Collaborative filtering is also utilized on a subset of the similar issues and associated resolution information to generate a second ranked list of the subset of similar issues and associated resolution information, where the subset of similar issues are each selected based on being within a time proximity to the reported issue. A linear regression is utilized on the first ranked list and the second ranked list to generate a ranked list of recommended resolutions to the reported issue that is then provided to an administrator.