Microsoft Technology Licensing, LLC

Gaurav Jagtiani

Saad Syed

Sushant Pramod Rewaskar

Ajay Mani

Abhishek Kumar Singh

Wei Zhao

Thiruvengadam Venketesan

Akram Hassan

Abhay Sudhir Ketkar

Binit Ranjan Mishra

Emma Sutherland Boyd

Scott Chao-Chueh Lee

Jason Stewart Wohlgemuth

James Anthony Schwartz, Jr

Shekhar Agrawal

Nic Allen

Thomas Moscibroda

Hari R Pulapaka

Karan Mehra

James George Cavalaris

Emily Nicole Wilson

Shen Wang

Karthikeyan Subramanian

Shandan Zhou

Naga Govindaraju

Yuri Dotsenko

Minsang Kim

Aacer Hatem Daken

Steven Adrian West

Cody D Hartwig

Peter Hanpeng Jiang

Emily Cara Clemens

Luke Rafael Rodriguez

Yu Yao

Sathyanarayana Singh

Gil Lapid Shafriri

Jennifer Marie Bourlier

Sharon Scarlet Tang

Christina Marianne Curlette

Terence Kwok Tak Chan

Drew Douglas Cross

Sri Harsha Kanukuntla

Raz Meir Aloni

Tri Minh Tran

Mukhtar Ahmed

Shailesh Padmakar Joshi

David Wimmel

Vijaybalaji Madhanagopal

Amruta Bhalchandra Pathak

Aravind Narayanan Krishnamoorthy

Derek James Boyer

Dalianna Victoria Vaysman

Rohit Pandey

Shweta Balkrishna Patil

Hemant Malik

Yancheng Chen

Sam Prakash Bheri

Durmus Ugur Karatay

Abhishek Singh

Sushant Pramad Rewaskar

A computer system identifies an event from a management system log associated with a first container host. The presence of the event in the management system log is indicative that the first container host identified a fatal system error at the first container host. Based on the event, the computer system determines that a first instance of a container that is provisioned at the first container host has been isolated to the first container host. Based on the first instance of the container having been isolated to the first container host, the computer system instructs a second container host to provision a second instance of the container at the second container host.

Accelerated fatal system error recovery of container host

The present disclosure relates to utilizing a host failure recovery system to efficiently and accurately determine the health of host devices. For example, the host failure recovery system detects when a host server is failing by utilizing a power failure detection model that determines whether a host server is operating in a healthy power state or an unhealthy power state. In particular, the host failure recovery system utilizes a multi-layer power failure detection model that determines power-draw failure events on a host device. The failure detection model determines, with high confidence, the health of a host device based on power-draw signals and/or usage characteristics of the host device. Additionally, the host failure recovery system can initiate a quick recovery of a failing host device.

Utilizing power-draw device signals to improve the recovery of virtual machine host devices

In-place recovery of fatal system errors at virtualization hosts. A device identifies an occurrence of a fatal system error in the first instance of a host operating system (OS) executing in a computer system. The device determines to perform an in-place recovery for the fatal system error. The device performs the in-place recovery, including pausing the execution of a virtual machine (VM) by the first instance of the host OS, preserving a state of the VM within system memory of the computer system, and resuming the execution of the VM by a second instance of the host OS executing in the computer system based on the state of the VM that is preserved within the system memory of the computer system.

In-place recovery of fatal system errors at virtualization hosts

A computer implemented method includes receiving telemetry data corresponding to capacity health of nodes in a cloud based computing system. The received telemetry data is processed via a prediction engine to provide predictions of capacity health at multiple dimensions of the cloud based computing system. Node recoverability information is received and node recovery execution is initiated as a function of the representations of capacity health and node recoverability information.

Capacity aware cloud environment node recovery system

Various techniques for deferred server recovery are disclosed herein. In one embodiment, a method includes receiving a notification of a fault from a host in the computing system. The host is performing one or more computing tasks for one or more users. The method can then include determining whether recovery of the fault in the received notification is deferrable on the host. In response to determining that the fault in the received notification is deferrable, the method includes setting a time delay to perform a pending recovery operation on the host at a later time and disallowing additional assignment of computing tasks to the host.

Deferred server recovery in computing systems

Methods, systems, and computer program products are described herein for minimizing the downtime for nodes in a network-accessible server set. The downtime may be minimized by determining an optimal timeout value for which a fabric controller waits to perform a recovery action. The optimal timeout value may be determined for each cluster in the network-accessible server set. The optimal timeout value advantageously reduces the overall downtime for customer workloads running on a node for which contact has been lost. The optimal timeout value for each cluster may be based on a predictive model based on the observed historical patterns of the nodes within that cluster. In the event that an optimal timeout value is not determined for a particular cluster (e.g., due to a lack of observed historical patterns), the fabric controller may fall back to a less than optimal timeout value.

Determining for an optimal timeout value to minimize downtime for nodes in a network-accessible server set

Embodiments described herein are directed to migrating affected services away from a faulted cloud node and to handling faults during an upgrade. In one scenario, a computer system determines that virtual machines running on a first cloud node are in a faulted state. The computer system determines which cloud resources on the first cloud node were allocated to the faulted virtual machine, allocates the determined cloud resources of the first cloud node to a second, different cloud node and re-instantiates the faulted virtual machine on the second, different cloud node using the allocated cloud resources.

Healing cloud services during upgrades

Growing community of inventors

Newcastle, WA, United States of America

Gaurav Jagtiani