Constraint aware flow based application discovery - improved machine learning algorithm for application discovery
AssigneeVMware, Inc.
InventorsMadan Singhal, Shubhrajyoti Mohapatra, Abhishek Shingane
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Abstract
A feature selection methodology is disclosed. In a computer-implemented method, components of a computing environment are automatically monitored, and have a feature selection analysis performed thereon. Provided the feature selection analysis determines that features of the components are well defined, a clustering of the features is performed. A constraint based semi supervised process is performed. Provided the feature selection analysis determines that features of the components are well defined, a similarity analysis of the sub-features of the feature is performed. Results of the feature selection methodology are generated.
Claims30
A computer-implemented method for automated application discovery in a virtual computing environment, said method comprising:
- automatically monitoring communications between a plurality of diverse components in said computing environment;
- generating network flow information in relation to said plurality of diverse components in said computing environment;
- utilizing said network flow information in a constraint based semi supervised process;
- providing a machine learning based discovery of a plurality of applications spanning across said plurality of diverse components in said computing environment;
- and
- creating a software defined network based upon the application boundary endpoints.
A computer-implemented method for automatically discovering applications in an agentless plurality of diverse components in a computing environment said method comprising:
- automatically generating component flow data;
- automatically enriching said flow data with workload information pertaining to said plurality of diverse components to generate a connectivity graph wherein said connectivity graph includes one or more weakly connected components;
- further using said flow data enriched with workload information pertaining to said plurality of diverse components to run a constraint based semi supervised process;
- generating applications spanning across said plurality of diverse components, providing said results for said automated analysis of said features of said components;
- and
- creating a software defined network based upon the application boundary endpoints.
Dependencies are inferred from the claim text.