AUTOMATIC DATACENTER STATE SUMMARIZATION
First Claim
1. A method comprising:
- receiving a context graph indicating a plurality of relationships among a plurality of nodes corresponding to components of a datacenter, each node comprising properties corresponding to a particular component of the datacenter;
for each subgraph identified as a relevant region in the context graph corresponding to a relevance condition and lacking an annotation describing the relevance condition, determining a plurality of context hashes based on selected properties;
comparing the plurality of context hashes to a plurality of subgraph hashes derived from a library of subgraphs to determine a set of subgraph hashes that are similar to the plurality of context hashes derived for each relevant region;
identifying annotations corresponding to the set of subgraph hashes;
combining the annotations in accordance with an importance into an annotation for each relevant region; and
annotating the context graph with the combined annotations, the combined annotations describing the datacenter as a whole with a textual description.
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Abstract
In a datacenter setting, annotations or descriptions of relevant parts or subgraphs corresponding to components in the datacenter are predicted. Given a set of training data (library of subgraphs seen in the past labeled with a textual description explaining why were they considered relevant enough to be placed in the historical database), the recurrent neural network (RNN) learns how to combine the different textual annotations coming from each relevant region into a single annotation that describes the whole system. Accordingly, given a set of input or test data (datacenter state modeled a context graph that is not annotated), the system determines which regions of the input graph are more relevant, and for each of these regions, the RNN predicts an annotation even in a previously unseen or different datacenter infrastructure.
8 Citations
20 Claims
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1. A method comprising:
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receiving a context graph indicating a plurality of relationships among a plurality of nodes corresponding to components of a datacenter, each node comprising properties corresponding to a particular component of the datacenter; for each subgraph identified as a relevant region in the context graph corresponding to a relevance condition and lacking an annotation describing the relevance condition, determining a plurality of context hashes based on selected properties; comparing the plurality of context hashes to a plurality of subgraph hashes derived from a library of subgraphs to determine a set of subgraph hashes that are similar to the plurality of context hashes derived for each relevant region; identifying annotations corresponding to the set of subgraph hashes; combining the annotations in accordance with an importance into an annotation for each relevant region; and annotating the context graph with the combined annotations, the combined annotations describing the datacenter as a whole with a textual description. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. A method comprising:
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receiving historical metrics from a plurality of historical nodes for relevance conditions seen by historical datacenters; aggregating the historical metrics into historical vector representations for the plurality of historical nodes in the historical datacenter, the historical vector representations including information derived from the historical metrics of neighbors of the historical nodes and having annotations describing relevance conditions seen by the historical datacenters; and training a classifier with the historical vector representations and annotations to predict an annotation for a datacenter depicted by a context graph indicating a plurality of relationships among a plurality of nodes corresponding to components of the datacenter, the context graph having a subgraph identified as a relevant region corresponding to a relevance condition not having an annotation describing the relevance condition with a textual description. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19)
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20. A computerized system:
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a processor; and a non-transitory computer storage medium storing computer-useable instructions that, when used by the processor, cause the processor to; receive a context graph indicating a plurality of relationships among a plurality of nodes corresponding to components of a datacenter, each node comprising properties corresponding to a particular component of the datacenter; for each relevant region of the context graph corresponding to a relevance condition and lacking an annotation describing the relevance condition, determine a plurality of context hashes based on selected properties of the node; compare the plurality of context hashes to a plurality of subgraph hashes derived from a library of subgraphs to determine a set of subgraph hashes that are similar to the plurality of context hashes corresponding to each relevant region; identify annotations corresponding to the set of subgraph hashes for each relevant region; and annotate the node with the combined annotations, the combined annotations describing the relevance conditions of the datacenter at a particular state with a textual description.
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Specification