Scalable artificial intelligence driven configuration management

Techniques are described herein for scalable clustering of target resources by parameter set. In some embodiments, a plurality of parameter sets of varying length are received, where a parameter set identifies attributes of a target resource. A plurality of signature vectors are generated based on t...

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Bibliographische Detailangaben
Hauptverfasser: Ganesh, Amit, Garvey, Dustin, Frazier, Timothy Mark, Shaft, Uri, Ravuri, Prasad, Salunke, Sampanna Shahaji, Krishnan, Shriram, Gopalakrishnan, Sumathi
Format: Patent
Sprache:eng
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Zusammenfassung:Techniques are described herein for scalable clustering of target resources by parameter set. In some embodiments, a plurality of parameter sets of varying length are received, where a parameter set identifies attributes of a target resource. A plurality of signature vectors are generated based on the plurality of parameter sets such that the signature vectors have equal lengths. A signature vector may map to one or more parameter sets of the plurality of parameter sets. A plurality of clusters are generated based on the similarity between signature vectors. Operations may be performed on a target resource based on one or more nodes in the plurality of clusters.