Dell Products Inc.

Sweta Kumari

Hung The Dinh

Seshadri Srinivasan

Shishir Kumar Parhi

Sashibhusan Panda

Shivangi Geetanjali

Antarlina Tripathy

Baishali Roy

Bijan Kumar Mohanty

Sambasivarao Gaddam

Shivangi Maharana

Harikrishna Reyyi

Sowmya Kumar

Panguluru Vijaya Sekhar

Satish Ranjan Das

Krishna Mohan Akkinapalli

Sourav Datta

Kiran Kumar Pidugu

Lakshman Kumar Tiwari

Bharath Alla

Shashikiran Rajagopal

Sowmya K

Yash Khare

A method comprises collecting data corresponding to a plurality of components in a system, wherein the data comprises information about at least one of respective protocols and respective interfaces associated with respective ones of the plurality of components. The data is analyzed to determine at least one of the respective protocols and the respective interfaces associated with the respective ones of the plurality of components. In the method, operations of one or more components of the plurality of components are tested based at least in part on the determination of the at least one of the respective protocols and the respective interfaces. The method further includes outputting respective statuses of the one or more components, wherein the respective statuses are derived at least in part from the testing.

Testing framework with load forecasting

A method comprises receiving a request for validation of software comprising one or more applications, analyzing the request and generating one or more validation steps based at least in part on the analysis. In the method, a time to complete the one or more validation steps is predicted. The predicting is performed using one or more machine learning models, and is based at least in part on a type and a number of the one or more applications.

Software validation framework

A method comprises collecting data corresponding to a plurality of components in a system, wherein the data comprises information about one or more issues with the plurality of components. The data is analyzed and categorized based at least in part on the analysis. In the method, one or more application programming interfaces (APIs) are selected to monitor respective statuses of the plurality of components, wherein the selection is based at least in part on the categorization of the data, and the data is pushed to the one or more APIs.

Component monitoring framework with predictive analytics

A method comprises managing multiple tasks of multiple entities associated with a deployment of a software program with a deployment framework comprising a machine learning module configured to assist with managing the multiple tasks of the multiple entities. The managing step comprises tracking a status of one or more of the multiple tasks, and predicting a time taken for a given one of the multiple entities to complete a given one of the multiple tasks.

Enterprise deployment framework with artificial intelligence/machine learning

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Bengaluru, India

Sweta Kumari