Vmware, Inc.

Maarten Wiggers

Manoj Krishnan

Rajesh Venkatasubramanian

Keith Farkas

Sahan Bamunavita Gamage

Anne Holler

Konstantinos Roussos

Pranshu Jain

Alkesh Shah

Leonid Livshin

Cheng Cheng

Anil Kapur

Gabriel Tarasuk-Levin

Derek William Beard

Fei Guo

Praveen Vegulla

Ivaylo Radoslavov Radev

Sabareesh Subramaniam

Lei Lu

Sai Inabattini

Tomo Vladimirov Simeonov

Varun S Lingaraju

Aniket Avinash Sakhardande

Avinash Goud

Deepak Babarjung

Biliana Gueorguieva Gelkova

Janani Subhashini Umamaheswaran

Leda Lyudmilova Grigorova-Borisova

Sruthi Cherukuri

Pamel Shinh

Pradeep Ramachandra

An example method of scheduling a workload in a virtualized computing system including a host cluster having a virtualization layer directly executing on hardware platforms of hosts is described. The virtualization layer supports execution of virtual machines (VMs) and is integrated with an orchestration control plane. The method includes: receiving, at the orchestration control plane, a workload specification for the workload; selecting, at the orchestration control plane, a plurality of nodes for the workload based on the workload specification, each of the plurality of nodes implemented by a host of the hosts; selecting, by the orchestration control plane in cooperation with a virtualization management server managing the host cluster, a node of the plurality of nodes; and deploying, by the orchestration control plane in cooperation with the virtualization management server, the workload on a host in the host cluster implementing the selected node.

Scheduling workloads in a container orchestrator of a virtualized computer system

Aspects of managing inventory for data transport connections within a virtualized computing environment are described. A virtualized management system managing a cluster of host devices obtains a data transport capacity parameter and an aggregate memory consumption value from respective host devices. The virtualized management system further identifies an update status associated with each of the host devices. In response to receiving a data transport connection request, the virtualized management system selects a host from the cluster of hosts to satisfy the data transport connection request based at least in part on the upgrade status, data transport capacity parameter and aggregate memory consumption value.

Inventory management for data transport connections in virtualized environment

Techniques are disclosed for reallocating host resources in a virtualized computing environment when certain criteria have been met. In some embodiments, a system identifies a host disabling event. In view of the disabling event, the system identifies a resource for reallocation from a first host to a second host. Based on the identification, the computer system disassociates the identified resource's virtual identifier from the first host device and associates the virtual identifier with the second host device. Thus, the techniques disclosed significantly reduce a system's planned and unplanned downtime.

Method for repointing resources between hosts

An example method may include receiving a first GUI selection of a first management server corresponding to a first cluster of virtual infrastructure objects, receiving a second GUI selection of one or more first virtual infrastructure object tags to be assigned to at least one virtual infrastructure object from the first cluster of virtual infrastructure objects after a creation process of a first policy, wherein the first policy is configured to regulate the at least one virtual infrastructure object from the first cluster of virtual infrastructure objects with the one or more first virtual infrastructure object tags, receiving first real-time feedback associated with the first cluster of virtual infrastructure objects and the one or more first virtual infrastructure object tags from the first management server, and displaying a object count in a first GUI element supported by the configuration client.

Real-time feedback associated with configuring virtual infrastructure objects using tags

Methods, apparatus, systems, and articles of manufacture are disclosed for high availability (HA) application migration in a virtualized environment. An example apparatus includes at least one memory, instructions in the apparatus, and processor circuitry to at least one of execute or instantiate the instructions to identify an HA slot in a virtual server rack, the HA slot to facilitate a failover of an application executing on a first virtual machine (VM) in the virtual server rack, the first VM identified as a protected VM, deploy a second VM in the HA slot, transfer data from the first VM to the second VM, and, in response to not identifying a failure of at least one of the first or second VMs during the transfer, trigger a shutdown of the first VM, and synchronize migration data associated with the virtual server rack to identify the second VM as the protected VM.

Systems, methods, and apparatus for high availability application migration in a virtualized environment

The disclosure provides an approach for the dynamic configuration of virtualized objects. A virtual object may be associated with a desired state defining a first plurality of resources for allocating to the virtual object. The first plurality of resources correspond to one or more resource types. Techniques include determining that each of a plurality of hosts does not have sufficient available resources to allocate the first plurality of resources to the virtual object according to the desired state. Techniques include selecting, a first host of the plurality of hosts to run the virtual object. Techniques include allocating a second plurality of resources to the virtual object from the first host, wherein the second plurality of resources is less than the first plurality of resources, and running the virtual object in the first host.

Dynamic configuration of virtual objects

Workloads are scheduled on a common set of resources distributed across a cluster of hosts using at least two schedulers that operate independently. The resources include CPU, memory, network, and storage, and the workloads may be virtual objects, including VMs, and also operations including live migration of virtual objects, network file copy, reserving spare capacity for high availability restarts, and selecting hosts that are to go into maintenance mode. In addition, the at least two independent schedulers are assigned priorities such that the higher priority scheduler is executed to schedule workloads in its inventory on the common set of resources before the lower priority scheduler is executed to schedule workloads in its inventory on the common set of resources.

Scheduling workloads on a common set of resources by multiple schedulers operating independently

The present disclosure describes a technique for honoring virtual machine placement constraints established on a first host implemented on a virtualized computing environment by receiving a request to migrate one or more virtual machines from the first host to a second host and without violating the virtual machine placement constraints, identifying an architecture of the first host, provisioning a second host with an architecture compatible with that of the first host, adding the second host to the cluster of hosts, and migrating the one or more virtual machines from the first host to the second host.

Honoring resource scheduler constraints during maintenances

Examples described herein include systems and methods for backing up and recovering a software-defined data center ('SDDC'). In one example, entities of the SDDC, such as virtual machines, hosts, and clusters, can coexist with corresponding entity stores. The entity stores can store current state information for each SDDC entity. For example, an identifier or name of a virtual machine can be stored in that virtual machine's corresponding entity store. When recovery of a controller is needed, the controller can rebuild state information that has changed after the controller was backed up, by retrieving state information from entity stores of the various SDDC entities.

Recovery of a software-defined data center from persistent entity stores for virtual machines

Recovery of a software-defined data center

Disclosed are aspects of proactive high availability that proactively identify and predict hardware failure scenarios and migrate virtual resources to healthy hardware resources. In some aspects, a mapping that maps virtual resources to hardware resources. A plurality of hardware events are identified in association with a hardware resource. A hardware failure scenario is predicted based on a health score of a first hardware resource. A health score is determined based on the hardware events, and a fault model that indicates a level of severity of the hardware events. A particular virtual resource is migrated from the hardware resource to another hardware that has a greater health score.

Proactive high availability in a virtualized computer system

A system and method for automatically consolidating clusters of host computers in a distributed computer system uses a digital representation of a simulated merged cluster of host computers to produce resource management analysis results on the simulated merged cluster of host computers. The simulated merged cluster of host computers is a simulation of a consolidation of first and second clusters of host computers. In addition, the system and method involves executing an automatic consolidation operation on the first and second clusters of host computers to generate a merged cluster of host computers that includes the host computers from both the first and second clusters.

Automatic cluster consolidation for efficient resource management

A method of managing virtual resources executing on a hardware platform that employs sensors to monitor the health of hardware resources of the hardware platform, includes filtering sensor data from the hardware platform and combining the sensor data with a fault model for the hardware platform to generate a health score, receiving an inventory that maps the virtual resources to the hardware resources of the hardware platform, receiving resource usage data describing use of the hardware resources of the hardware platform by the virtual resources, and generating resource utilization metrics from the resource usage data. The method includes receiving policy data specifying rules applicable to the inventory, determining a set of recommendations for changes to the inventory based on the health score, the resource usage data, and the policy data, and executing at least one recommendation to implement the changes to the inventory.

Growing community of inventors

Mountain View, CA, United States of America

Maarten Wiggers