Performance modeling for cloud applications
AssigneeTelefonaktiebolaget LM Ericsson (publ)
InventorsMichel Gokan Khan, Wenfeng Hu, Carolyn Cartwright, Huiyuan Wang
Life of this patent
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Abstract
A method (1000) for performance modeling of a plurality of microservices (215) includes deploying the plurality of microservices (215) within a network (1260). The plurality of microservices (215) are communicatively coupled to generate at least one service chain (310) for providing at least one service. Based on a resource allocation configuration, an initial set of training data for the plurality of microservices within the network (1260) is determined. At least a portion of data is excluded from the initial set of training data to generate a subset of training data. A Quality of Service (QoS) behaviour model is generated based on the subset of the training data.
Claims19
A method for performance modeling of a plurality of microservices , the method comprising:
- deploying the plurality of microservices within a network, the plurality of microservices communicatively coupled to generate at least one service chain for providing at least one service;
- based on a resource allocation configuration, determining an initial set of training data for the plurality of microservices within the network;
- excluding at least a portion of data from the initial set of training data to generate a subset of training data;
- and
- generating a Quality of Service (QoS) behaviour model based on the subset of the training data, wherein selecting the QoS behaviour model based on the set of training data, comprises:
- testing a plurality of hypothesis functions for the plurality of microservices in a service chain;
- selecting one of a plurality of hypothesis functions that has a highest goodness of fit and cross-validation results to the set of training data;
- and
- training the QoS behaviour model to estimate at least one QoS metric.
A network node for performance modeling of a plurality of microservices, the network node comprising:
- processing circuitry configured to:
- deploy the plurality of microservices within a network, the plurality of microservices communicatively coupling to generate at least one service chain for providing at least one service;
- based on a resource allocation configuration, determine an initial set of training data for the plurality of microservices within the network;
- exclude at least a portion of data from the initial set of training data to generate a subset of training data;
- and
- generate a Quality of Service (QoS) behaviour model based on the subset of the training data, wherein when selecting the QoS behaviour model based on the set of training data the processing circuitry is configured to:
- test a plurality of hypothesis functions for the plurality of microservices in a service chain;
- select one of a plurality of hypothesis functions that has a highest goodness of fit and cross-validation results to the set of training data;
- and
- train the QoS behaviour model to estimate at least one QoS metric.
Dependencies are inferred from the claim text.