Microsoft Technology Licensing, LLC

Brett Damon Alan Flegg

David C James

Brad R Anderson

Yian Mo

Toshitha Jagadeesh

Marc Shepard

Gaurav Raghu Dhawan

Prabagar Ramadasse

Loretta Marie Macklem-Clements

Jason Robert Githens

Michael J Wallent

Maayan Bar-Niv

Yongcheng Huang

Koen Van Der Hoeven

Bruno Ryuichi Yoshioka

Hang Heidi Cheng

Michael John Wallent

Techniques are described herein that are capable of providing a recommendation of an admin change (i.e., an admin change recommendation) in an enterprise. A type of intended admin change that an administrator is to perform with regard to an enterprise is determined. The type is cross-referenced with information indicating admin changes made by administrator(s) in environment(s) of enterprise(s) and values of metrics resulting therefrom to identify subsets of the information to which the type corresponds. A causal relationship is inferred between admin change(s) made after an admin change of the type and an increase in value(s) of metric(s) that are indicated by information in the subsets. A recommended admin change is recommended to be performed by the administrator based at least in part on a causal relationship between the recommended admin change and an increase in at least one of the value(s) of at least one of the respective metric(s).

Admin change recommendation in an enterprise

Techniques are described herein that are capable of estimating a result of configuration change(s) in an enterprise. Enterprise information regarding a designated enterprise is gathered. The enterprise information is combined with anonymized information that is received from multiple enterprises to provide combined information. An actual impact of configuration changes in at least one enterprise (e.g., with regard to a first subset of the machines therein) is determined and/or a predictive impact of the configuration change(s) in at least one enterprise (e.g., with regard to a second subset of machines therein) is inferred. An estimate of a net financial result of implementing the configuration change(s) (e.g., with regard to the second subset of the machines) in the designated enterprise is generated based at least in part on the actual impact and/or the predictive impact.

Estimating a result of configuration change(s) in an enterprise

Techniques are described herein that are capable of selectively throttling an implementation of configuration changes in an enterprise. For instance, incremental phases of the implementation on respective subsets of clients are selectively throttled during respective periods of time by performing operations for each subset during a respective phase that precedes a respective next phase of the implementation. The operations include gathering information regarding the phase from the clients in the subset; generating a score that indicates an extent to which metrics associated with the implementation are satisfied during the phase based at least in part on the information; comparing the score to a reference score for the subset to determine whether the score is within a tolerance associated with the reference score; and selectively throttling the next phase of the implementation based at least in part on whether the score is within the tolerance.

Selectively throttling implementation of configuration changes in an enterprise

Techniques are described herein that are capable of utilizing agent-based configuration co-management to selectively migrate workloads from a first configuration management authority to a second configuration management authority. The first configuration management authority has a first management client and a first management server that provides a first management service. The second configuration management authority has a second management client and a second management server that provides a second management service. An operating system that runs on a computing device enrolls the first management agent and the second management agent into the second configuration management authority. The first management agent negotiates with the second management agent to determine a first subset of the workloads that is to be handled by the first management agent and a second subset of the workloads that is to be handled by the second management agent.

Agent-based configuration co-management to selectively migrate workloads

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Redmond, WA, United States of America

Brett Damon Alan Flegg