Hewlett Packard Enterprise Development LP

Muthukumar Murugan

Douglas L Voigt

Suparna Bhattacharya

Kalapriya Kannan

Dinesh Venkatesh

Ancy Sarah Tom

Yan Burdett

Systems and methods are provided for computationally configuring computing devices and performing multi-layer cluster analysis. For example, the system can identify multiple layers of clusters of devices (e.g., shared hardware configuration, shared application configuration, number of applications, etc.) in a large scale infrastructure environment automatically. For each layer of the clusters of devices, parameters of these devices are provided to a machine learning model to produce an objective function (e.g., minimum number of devices, utilization under 80%, etc.), whose output can be provided to a datacenter operator or other user in the large scale infrastructure environment so they can make further configuration changes to the devices in each cluster.

Computational configuration and multi-layer cluster analysis

Some examples relate to associating an insight with data. In an example, data may be received. A determination may be made that data type of the data is same as compared to an earlier data. An insight generated from the earlier data may be identified, wherein the insight may represent intermediate or resultant data generated upon processing of the earlier data by an analytics function, and wherein during generation metadata is associated with the insight. An analytics function used for generating the insight may be identified.

Associating insights with data

Example implementations relate to performing computations using provenance data. An example implementation includes storing first lineage data of a first dataset and provenance data of an application operating on the first dataset in a storage system. A computing resource may determine whether second lineage data of a second dataset meets a similarity criterion with the first lineage data of the first dataset. A computation on the second dataset may be performed using the provenance data of the application, and an insight of the second dataset may be generated from the performed computation.

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Boulder, CO, United States of America

Muthukumar Murugan