Microsoft Technology Licensing, LLC

Kevin Grealish

Bassam Tabbara

Geoffrey Hugh Outhred

Galen Clyde Hunt

Robert Victor Welland

Aamer Hydrie

Rob M Mensching

Anders Bertil Vinberg

Robert M Fries

Rene Antonio Vega

John M Parchem

Eric Joseph Winner

Jeffrey A Woolsey

Glenn R Peterson

David Searle Noble

Charlie D Chase

Alexander Torone

Mathilde C Brown

Edwin R Lassettre

Ashvinkumar J Sanghvi

Vij Rajarajan

Vitaly Voloshin

Anand Lakshminarayanan

Amir Netz

Giovanni Moises Della-Libera

David John Nettleton

Andrew James Peacock

Michael Justin Flasko

Mark Wade Heninger

Christina Storm

Chiu Ying Cheung

Cheryl Couris

Sonia P Carlson

Paula M Bach

David Wortendyke

Michael James Coulson

Andrea Westerinen

Marco Chierotti

Przemek Pardyak

Job execution can be scheduled and monitored. Execution of a job results in generation of one or more data slices, which can be consumed as input by one or more related jobs. Data slices can be presented in an interactive view. Selection of a data slice in the view can trigger automatic identification of related data slices based on dependencies between data slices. Each data slice can also include and be presented with a status indicating the availability of corresponding data, such as pending, ready, or failed. Furthermore, selection of a data slice that failed to generate successfully can trigger identification of related data slices that failed or are predicted to fail to generate successfully.

Job scheduling and monitoring in a distributed computing environment

Model-based virtual system provisioning includes accessing a model of a workload to be installed on a virtual machine of a system as well as a model of the system. A workload refers to some computing that is to be performed, and includes an application to be executed to perform the computing, and optionally includes the operating system on which the application is to be installed. The workload model identifies a source of the application and operating system of the workload, as well as constraints of the workload, such as resources and/or other capabilities that the virtual machine(s) on which the workload is to be installed must have. An installation specification for the application is also generated, the installation specification being derived at least in part from the model of the workload and the model of the virtual system.

Model-based virtual system provisioning

A view of data transformation jobs can be presented by way of a user interface. Related jobs can subsequently be identified automatically after a job is selected based on data dependencies between jobs. Execution status can also be determined and presented such that successful and failed execution of jobs, for example, can be differentiated. Furthermore, selection of a job run that failed to execute successfully can trigger identification of related jobs runs that failed or are predicted to fail to execute successfully.

Model-based system monitoring includes accessing a model of a system that includes multiple components and executing a monitoring policy to monitor performance of the system. A notification of a problem is received from a first component. A determination is made regarding the cause of the problem. The determination is made, at least in part, based on the model of the system. At least one component associated with the cause of the problem is then identified.

Model-based system monitoring

Described herein are techniques for specifying and utilizing static data in the environment of a tag-based or meta-markup document description language such as XML.

Using static data in a markup language

Integrating design, deployment, and management phases for a system in accordance with certain aspects includes using a system definition model to design a system. The system definition model is subsequently used to deploy the system on one or more computing devices and, after deployment of the system, the system definition model is used to manage the system deployed on the one or more computing devices.

Integrating design, deployment, and management phases for systems

An architecture and methodology for designing, deploying, and managing a distributed application onto a distributed computing system is described.

Architecture for distributed computing system and automated design, deployment, and management of distributed applications

Model-based provisioning of test environments includes accessing a model of an application to be installed in a test environment of a system and further accessing a model of the system and a model of the test environment. An installation specification for the application is also generated, the installation specification being derived at least in part from the model of the application, the model of the system, and the model of the test environment.

Model-based provisioning of test environments

In accordance with certain aspects of the design time validation of systems, a description of a system being designed and a description of an environment are received. Both of the received descriptions are used to validate the system against the environment while the system is being designed and prior to attempting to deploy the system.

Design time validation of systems

Model-based system monitoring includes identifying multiple monitors configured to monitor multiple components in a system, and accessing multiple health models associated with the multiple monitors. A monitoring policy is generated to monitor the system. The monitoring policy is derived, at least in part, from the multiple health models.

Model-based system monitoring includes accessing a model of a system that includes multiple components and identifying relationships among the multiple components based on the model of the system. A proposed change to at least one of the multiple components is identified. A determination is made regarding an expected impact on the system caused by the proposed change. This determination is made, at least in part, based on the model of the system.

Model-based system provisioning includes accessing a model of an application to be installed in a system and further accessing a model of the system. An installation specification for the application is also generated, the installation specification being derived at least in part from the model of the application and the model of the system.

Model-based system provisioning

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Kevin Grealish