Cisco Technology, Inc.

Zizhen Gao

Carlos M Pignataro

David C White, Jr

Chidambaram Arunachalam

David John Zacks

Enzo Fenoglio

Dmitry Goloubev

Methods are provided in which a cloud portal, serving as an orchestrator device, obtains a request for diagnostics data to monitor performance of a cloud-based service executing in a provider cloud network and accessed by a client device in an enterprise network and obtains service information about a plurality of assets involved in providing the cloud-based service. The plurality of assets are managed by at least a first cloud-based management entity and a second cloud-based management entity. The methods further include collecting the diagnostics data about the plurality of assets based on the service information, aggregating the diagnostics data to form a multi-cloud diagnostics data, and determining the performance of the cloud-based service based on the multi-cloud diagnostics data.

Case deflection using visibility into multi-product clouds

Methods are provided in which a computing device obtains telemetry data associated with a network technology used in an enterprise network and an enterprise network profile that includes information about the complexity of the enterprise network. The network technology is deployed at one or more devices of the enterprise network. The methods further include the computing device determining, based on the telemetry data, for each deployment of the network technology, a current stage from a plurality of stages of an adoption lifecycle to which the network technology progressed, determining a time estimate for completing the current stage of the adoption lifecycle, based on the enterprise network profile and an adoption benchmark generated from a plurality of activities performed for progressing along the adoption lifecycle, and evaluating an adoption of the network technology, using the time estimate, to progress the network technology along the lifecycle.

System for lifecycle progression leveraging adoption journey of networking and computing equipment

A method, computer system, and computer program product are provided for detecting drift in predictive models for network devices and traffic. A plurality of streams of time-series telemetry data are obtained, the time-series telemetry data generated by network devices of a data network. The plurality of streams are analyzed to identify a subset of streams, wherein each stream of the subset of streams includes telemetry data that is substantially empirically distributed. The subset of streams of time-series data are analyzed to identify a change point. In response to identifying the change point, additional time-series data is obtained from one or more streams of the plurality of streams of time-series telemetry data. A predictive model is trained using the additional time-series data to update the predictive model and provide a trained predictive model.

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San Ramon, CA, United States of America

Zizhen Gao