Microsoft Technology Licensing, LLC

Lokesh Srinivas Koppolu

David Allen Dion

Andrea D'Amato

David Matthew Kruse

Vladimir Petter

Amitabh Prakash Tamhane

Qibo Zhu

Abhinit Kumar

Eran Yariv

Yi Zeng

Charles D Bassett

Sai Sudhir Anantha Padmanaban

Elden Christensen

Nicholas Maliwacki

Mykyta Synytskyy

Maksim Noy

Sarah A Wahlert

Pradeep Bahl

Anton W Krantz

Mathew George

Angshuman Bezbaruah

Lars Reuther

Christopher Leland Eck

Srivatsa K Srinivasan

Gor Nishanov

Ankit Tandon

Sundar Anantharaman

Jonathan Fischer

Sergey Dmitriyevich Meshcheryakov

Rajesh Dave

Ian M Carbaugh

Steven Ekren

Suresh Chandra Pippari

Aatif Awan

David Abzarian

Rajesh Ramanathan

Amritansh Raghav

Vadim Eydelman

Gerardo Diaz-Cuellar

Ramesh Krishna Vyaghrapuri

Pradipta Kumar Basu

Brian Scott Stucker

Adrian Potra

Stephen Hoyt Houchen

Vijay Manian

Andreas Strebel

Yu An

Symon Perriman

Zongwei Sun

Maksym Yanchenko

Sunil Kasturi

Daniel Upton

A generation identifier is employed with various systems and methods in order to identify situations where a workload has been reassigned to a new node and where a workload is still being processed by an old node during a failure between nodes. A master node may assign a workload to a worker node. The worker node sends a request to access target data. The request may be associated with a generation identifier and workload identifier that identifies the node and workload. At some point, a failure occurs between the master node and worker node. The master node reassigns the workload to another worker node. The new worker node accesses the target data with a different generation identifier, indicating to the storage system that the workload has been reassigned. The old worker node receives an indication from the storage system that the workload has been reassigned and stops processing the workload.

Distributed workload reassignment following communication failure

Embodiments are directed to communicating between computing nodes in a cluster of nodes. In one scenario, a computer system receives a data packet from a worker node including the worker node's current workload identifiers and health status, where the data packet includes an associated version number. The computer system determines that the version number in the received data packet is different than a previously received data packet and evaluates the worker node's current workload configuration to determine whether workload changes are to be made on the worker node. Then, upon determining that workload changes are to be made on the worker node, the computer system selects a subset of workload changes to apply to the worker node, generates an indication of the selected subset of workload changes to the worker node and sends the generated indication of workload changes to the worker node.

Scalable fault resilient communications within distributed clusters

Services from domainless machines are made available in a security domain under a virtual name. Each machine is not joined to the domain but can reach a security domain controller. The controller controls at least one security domain using an authentication protocol, such as a modified Kerberos protocol. One obtains a set of security domain credentials, generates a cluster name secret, gives the cluster a virtual name, and authenticates the machines to the domain controller using these items. In some cases, authentication uses a ticket-based protocol which accepts the cluster name secret in place of a proof of valid security domain membership. In some, the domain controller uses a directory service which is compatible with an active directory service; the cluster virtual name is provisioned as an account in the directory service. The cluster virtual name may concurrently serve clients on different security domains of the directory service.

Domain joined virtual names on domainless servers

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

A request identifier is employed with various systems and methods in order to enable an application to pause execution during a failure and subsequently resume execution and communication with a storage system once the failure is resolved. An application residing on a node may attempt to access target data on a storage system. The application sends a request to access the target data. The request may be associated with a request identifier that identifies the application. When the storage system experiences a failure, the application receives a failure notification. The application pauses execution as a result of the notification. When the node reestablishes a connection to the storage system, the application resumes execution using the same request identifier. If the resume request is granted, the application is guaranteed that the target data was not modified during the failure.

Safe data access following storage failure

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

Architecture that facilitates the conveyance of a trust level when the caller makes a call, the trust level in dependence on the state of the caller system. The callee (call recipient) receives notification of the trust level and can use this information in the communication such as to request verification from the caller and/or initiate other modes of communication. A caller can authenticate the caller identity in different ways to a communication server. Based on that, the server can assign an appropriate server-verified trust level to the caller. Further, an unsecured phone controller can indicate a lower client-side defined trust level. The server verified and client-side trust levels are then sent to the callee, where the callee determines whether to allow caller access to one or more secured features based on the feature values and the trust level imposed by the callee to access those features.

Access control to secured application features using client trust levels

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Redmond, WA, United States of America

Lokesh Srinivas Koppolu