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公开(公告)号：US20200287923A1
公开(公告)日：2020-09-10
申请号：US16297013
申请日：2019-03-08
摘要： Data associated with performances of microservices functioning in a distributed computing environment is clustered by executing an unsupervised machine learning algorithm. A representative data is selected from a cluster, selecting performed for a plurality of the clusters. Based on time series data of the representative data associated with the plurality of the clusters, causal extraction is performed. Based on the causal extraction and the plurality of the clusters, a causal graph is constructed. The causal graph is embedded into vector space. Based on the embedded vector space, an artificial neural network model can be trained for managing the distributed computing environment.
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公开(公告)号：US12034747B2
公开(公告)日：2024-07-09
申请号：US16297013
申请日：2019-03-08
CPC分类号： H04L63/1425 , G06N3/088 , G06N20/00
摘要： Data associated with performances of microservices functioning in a distributed computing environment is clustered by executing an unsupervised machine learning algorithm. A representative data is selected from a cluster, selecting performed for a plurality of the clusters. Based on time series data of the representative data associated with the plurality of the clusters, causal extraction is performed. Based on the causal extraction and the plurality of the clusters, a causal graph is constructed. The causal graph is embedded into vector space. Based on the embedded vector space, an artificial neural network model can be trained for managing the distributed computing environment.
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