Microsoft Technology Licensing, LLC

Amitabh Prakash Tamhane

David Allen Dion

Lokesh Srinivas Koppolu

Andrea D'Amato

David Matthew Kruse

Mark Fishel Novak

Anders Bertil Vinberg

Niels Thomas Ferguson

Nir Ben-Zvi

Samartha Chandrashekar

Christopher Warner McCarron

Qiang Wang

Yevgeniy Anatolievich Samsonov

John Anthony Messec

Abhinit Kumar

Elden Christensen

Gor Nishanov

Kinshumann

Nicholas Maliwacki

Mykyta Synytskyy

Suresh Chandra Pippari

Kinshuman Kinshumann

Daniel Upton

Christopher Mccarron

A virtual secure mode is enabled for a virtual machine operating in a computing environment that is associated with a plurality of different trust levels. First, a virtual secure mode image is loaded into one or more memory pages of a virtual memory space of the virtual machine. Then, the one or more memory pages of the virtual memory space are made inaccessible to one or more trust levels having a relatively lower trust level than a launching trust level that is used by a virtual secure mode loader to load the virtual secure mode image. A target virtual trust level is also enabled on a launching virtual processor for the virtual machine that is higher than the launching trust level.

Secure management of operations on protected virtual machines

Technologies for cluster systems that are natively geo-site-aware. Such a cluster system makes use of this awareness to determine the subsets of nodes located at various geo-sites at physical configuration, to optimize workload placement based on the geo-sites, to make failover and failback decisions based on the geo-sites, and to assign voting and prune nodes for quorum management based on the geo-sites. Such capabilities result in cluster systems that are more resilient and more efficient in terms of resource usage than cluster systems without such native geo-site awareness.

Optimal storage and workload placement, and high resiliency, in geo-distributed cluster systems

Embodiments provide workload processing for clustered systems. In an illustrative, non-limiting embodiment, a computer-implemented method may include identifying a server as an active node of a cluster; assigning a workload to the server in response to the identification; determining, after the assignment, that the server is no longer an active node of the cluster; calculating, in response to the determination, a probability that the server is capable of continuing to execute the workload; and deciding, based upon the probability, whether to allow the workload to remain assigned to the server.

Providing higher workload resiliency in clustered systems based on health heuristics

Embodiments are directed to organizing computing nodes in a cluster federation and to reassigning roles in a cluster federation. In one scenario, a computer system identifies computing nodes that are to be part of a cluster federation which includes a master cluster and worker clusters. The computer system assigns a director role to a master node in the master cluster which governs decisions that affect consistency within the federation, and further assigns a leader role to at least one master node which monitors and controls other master nodes in the master cluster. The computer system assigns a worker agent role to a worker node which receives workload assignments from the master cluster, and further assigns a worker role to a worker node which processes the assigned workload. The organized cluster federation provides fault tolerance by allowing roles to be dynamically reassigned to computing nodes in different master and worker clusters.

Fault tolerant federation of computing clusters

Managing a distributed system. Embodiments may allow for a quorum to dynamically change the quorum vote. One example is illustrated in a method. The method includes determining a change to a voter's level of participation in a cluster. A quorum of voters changes the voter's voting privileges, based on the change in the voter's level of participation.

Dynamic quorum for distributed systems

Deploying an encrypted entity on a trusted entity is illustrated herein. A method includes, at a trusted entity, wherein the trusted entity is trusted by an authority as a result of providing a verifiable indication of certain characteristics of the trusted entity meeting certain requirements, receiving an encrypted entity from an untrusted entity. The untrusted entity is not trusted by the authority. At the trusted entity, a trust credential from the authority is used to obtain a key from a key distribution service. The key distribution service is trusted by the authority. The key is used to decrypt the encrypted entity to allow the encrypted entity to be deployed at the trusted entity.

Placing an application on a node in a cluster. A method includes detecting an unexpected event indicating that an application should be placed on a node in the cluster. Real time information about resource utilization on one or more nodes in the cluster is received. Based on the real time information, a determination of a node to place the application is made. The application is placed on the determined node.

Resource aware placement of applications in clusters

Placing an application on a node in a cluster. A method includes determining that a first application cannot be placed on a first node in the first node's current running state. The method further includes determining that the first application may be able to be placed on the first node by shutting down or moving one or more other applications running on the first node. The method further includes attempting to shut down or move the one or more other applications on the first node to place the first application.

Automatic preemption in multiple computer systems

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Redmond, WA, United States of America

Amitabh Prakash Tamhane