Microsoft Technology Licensing, LLC

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David Allen Dion

Lokesh Srinivas Koppolu

Michael T Massa

Vladimir Petter

Rajsekhar Das

Andrea D'Amato

Gor Nishanov

Amitabh Prakash Tamhane

David Matthew Kruse

Rudolf Opavsky

David Bruce Lomet

Rod N Gamache

Vyacheslav Kuznetsov

Rohit Jain

Rushabh A Doshi

Qibo Zhu

Abhinit Kumar

Philip Alan Bernstein

Sunita Shrivastava

Elden Christensen

Mykyta Synytskyy

Nicholas Maliwacki

Mathew George

Parveen Kumar Patel

Angshuman Bezbaruah

Vinod R Shankar

Lars Reuther

Christopher Leland Eck

Marios Zikos

Jonathan Fischer

Sergey Dmitriyevich Meshcheryakov

Rajesh Dave

Suresh Chandra Pippari

Volodymyr Ivanov

Steven Ekren

Mark Eugene Russinovich

Philip A Bernstein

James Ernest Johnson

Ajay Mani

Marcus Felipe Fontoura

Gregory Irving Thiel

Esaias Engelbertus Greeff

Gopal Kakivaya

Milan Vukosavljevic

Raj Das

Shailesh Padmakar Joshi

Symon Perriman

Zongwei Sun

Maksym Yanchenko

Sunita V Nishanov

Kurt Lawrence Friedrich

Daniel Upton

Esaias Englebertus Greeff

Shailesh P Joshi

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

According to examples, an apparatus may include a processor and a memory on which is stored machine readable instructions that are to cause the processor to receive an allocation request from an allocator client, determine a resource allocation for the received job allocation request, store a record of the determined resource allocation in a records store, and send the determined resource allocation to the allocator client, in which an acknowledgement to the sent determined resource allocation is to be received from the allocator client. The instructions may also cause the processor to manage a state of the determined resource allocation using the record stored in the records store based on whether the acknowledgement is received from the allocator client.

Resource allocation state management

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 provide a method and system for enabling access to a storage device. Specifically, a node may request admittance to a cluster that has read and write access to a storage device. The node seeking access to the storage device must be first be approved by other nodes in the cluster. As part of the request, the node seeking access to the storage device sends a registration key to a storage device. Upon expiration of a registration timer, the node seeking access to the storage device receives a registration table from the storage device and determines whether its registration key is stored in the registration table. If the registration key is stored in the registration table the node has been accepted in the cluster and as a result, has been granted read and write access to the storage device.

Controlling storage access by clustered nodes

Described is a technology by which an owner node in a server cluster maintains ownership of a storage mechanism through a persistent reservation mechanism, while allowing non-owning nodes read and write access to the storage mechanism. An owner node writes a reservation key to a registration table associated with the storage mechanism. Non-owning nodes write a shared key that gives them read and write access. The owner node validates the shared keys against cluster membership data, and preempts (e.g., removes) any key deemed not valid. The owner node also defends ownership against challenges to ownership made by other nodes, so that another node can take over ownership if a (formerly) owning node is unable to defend, e.g., because of a failure.

Resource arbitration for shared-write access via persistent reservation

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

Certain embodiments of computing systems, devices, components, modules, routines, and processes for implementing distributed operational control in a computing fabric are described herein. In one embodiment, a method includes receiving, at a control cluster, a tenant request for a cloud-based computing service at the computing system. The method also includes creating an application configured to provide the requested cloud-based computing service based on the tenant request and pushing configuration data of the created application to the execution cluster to be executed at the execution cluster without further intervention from the control cluster.

Distributed operational control in computing systems

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Bothell, WA, United States of America

David Allen Dion