Vmware, Inc.

Naveen Mudnal

Chandrashekhar Jha

Kumar Gaurav

Yash Bhatnagar

Jobin Raju George

Dattathreya Sathyamurthy

Rajat Garg

Jusvinder Singh

Swarnalatha Pasupuleti

Santoshkumar Kavadimatti

Gerin Jacob

Methods, apparatus, systems and articles of manufacture are disclosed to detect drift in a hybrid cloud environment. An example apparatus to detect drift in a hybrid cloud environment includes a configuration model determiner to, after deployment of a blueprint in the hybrid cloud environment, generate a first model including first relationships of a first plurality of resources corresponding to the blueprint, the blueprint including a plurality of properties in which at least one of the plurality of properties is agnostic of type of cloud, an inventor model determiner to generate a second model including second relationships of a second plurality of resources as deployed in the hybrid cloud environment based on the blueprint, and a drift determiner to determine a drift value based on the first relationships and the second relationships, the drift value representative of a difference between the first relationships and the second relationships.

Methods and apparatus to detect drift in a hybrid cloud environment

Various examples are disclosed for using clustering routines to extrapolate metrics to other computing resources in a cluster. One or more computing devices can classify computing resources, such as servers, based on various characteristics of the computing resources. For each class of computing resource, a clustering routine can be applied to generate clusters of the computing resources. A minimal number of metrics required to be obtained from an end user can be determined as a function of a number of the clusters. If one or more of the metrics are obtained from the end user, the metrics can be extrapolated to other computing resources in the same cluster.

Clustering routines for extrapolating computing resource metrics

Various examples are disclosed for generating a prediction of server requirements needed to deploy an application. The application can be deployed in virtualized environment in which virtual machines can execute the application. The predicted server requirements can be generated based upon data from other deployments of the application in other virtualized environments.

Generating predictive metrics for virtualized deployments

Growing community of inventors

Bengaluru, India

Naveen Mudnal