20240036998. OPTIMIZING HIGH-AVAILABILITY VIRTUAL MACHINE PLACEMENTS IN ADVANCE OF A COMPUTING CLUSTER FAILURE EVENT simplified abstract (Nutanix, Inc.)

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OPTIMIZING HIGH-AVAILABILITY VIRTUAL MACHINE PLACEMENTS IN ADVANCE OF A COMPUTING CLUSTER FAILURE EVENT

Organization Name

Nutanix, Inc.

Inventor(s)

Bojan Poprzen of Novi Sad (RS)

Danilo Medjo of Belgrade (RS)

Fabien Hermenier of Grasse (FR)

Karan Talreja of San Jose CA (US)

Nevena Milinkovic of Belgrade (RS)

Nitin Chandra Badam of San Jose CA (US)

Vinaya Khandelwal of Sunnyvale CA (US)

OPTIMIZING HIGH-AVAILABILITY VIRTUAL MACHINE PLACEMENTS IN ADVANCE OF A COMPUTING CLUSTER FAILURE EVENT - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240036998 titled 'OPTIMIZING HIGH-AVAILABILITY VIRTUAL MACHINE PLACEMENTS IN ADVANCE OF A COMPUTING CLUSTER FAILURE EVENT

Simplified Explanation

The patent application describes a mechanism for automatically placing computing entities onto nodes of a multi-node computing cluster. The goal is to optimize the placement scenario in order to satisfy a high-availability requirement of the cluster.

  • The mechanism analyzes the cluster and generates multiple feasible placement scenarios before a failure event occurs.
  • Optimization criteria are applied to these scenarios to identify the best choice.
  • The chosen placement scenario is then applied to the virtual machine placements over the cluster.
  • A change monitoring and detection facility continuously observes the cluster for changes in failure mode parameters or virtual machine configurations.
  • Certain changes trigger the generation, evaluation, selection, and application of new feasible placement scenarios.

Potential applications of this technology:

  • Cloud computing platforms: This mechanism can be used in cloud computing environments to optimize the placement of virtual machines on physical servers, ensuring high availability and efficient resource utilization.
  • Data centers: It can be applied in data centers to automatically place computing entities on servers, improving fault tolerance and minimizing downtime.

Problems solved by this technology:

  • High-availability requirement: The mechanism addresses the challenge of ensuring that computing entities are placed in a way that satisfies the high-availability requirement of the cluster, minimizing the impact of failures.
  • Resource optimization: By applying optimization criteria, the mechanism optimizes the placement scenario to maximize resource utilization and minimize the risk of resource bottlenecks.

Benefits of this technology:

  • Improved fault tolerance: By automatically generating and applying optimized placement scenarios, the mechanism enhances the fault tolerance of the computing cluster, reducing the impact of failures.
  • Efficient resource utilization: The optimization criteria ensure that computing entities are placed in a way that maximizes resource utilization, leading to improved performance and cost-effectiveness.
  • Reduced downtime: By continuously monitoring and detecting changes, the mechanism can quickly adapt the placement scenario to address any changes in failure mode parameters or virtual machine configurations, minimizing downtime.


Original Abstract Submitted

placement scenario optimization mechanisms for automatic placement of computing entities onto nodes of a running multi-node computing cluster. a set of failure mode parameters define a high-availability requirement of the multi-node computing cluster. in advance of a failure event, and responsive to a determination that a then-current computing entity placement does not satisfy the high-availability requirement, the cluster is analyzed and a plurality of feasible placement scenarios are generated. optimization criteria are applied to the feasible placement scenarios such that a best choice from among the feasible placement scenarios is identified and applied to the virtual machine placements over the cluster. a change monitoring and detection facility continually observes the multi-node computing cluster to detect a change of a failure mode parameter or to detect a change to the configuration of the virtual machines. certain of such changes cause feasible placement scenarios to be generated, evaluated, selected, and applied.

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