Nutanix, Inc.

Miao Cui

Binny Sher Gill

Gregory A Smith

Tabrez Parvez Memon

Felipe Franciosi

Karan Gupta

Rajiv Mirani

Aroosh Sohi

Gaurav Poothia

Jan Olderdissen

Robert William Schwenz

Malcolm Crossley

Jaya Singhvi

Vineet Kahlon

Arunkumar Navasivasakthivelsamy

Jan Ralf Alexander Olderdissen

Aditya Ramesh

Igor Grobman

Kshitiz Jain

Srinivas Bandi Ramesh Babu

Akshay Khole

Uzui Li

Jaspal Singh Dhillon

Manosiz Bhattacharyya

Himanshu Shukla

Abhinay Nagpal

Kamalneet Singh

Alexander Michael Bunch

Fabien Hermenier

Peter Turschmid

Ashwin Thennaram Vakkayil

Pulkit Yadav

Supreeth Srinivasan

Arun Navasivasakthivelsamy

Mengyang Li

Weiheng Chen

Brian Andrew Griffiths Finn

Malcolm Gordon Crossley

Ajay Prakash Kulkarni

Peter Alan Turshmid

Gregory Andrew Smith

Systems for high-performance computing. A storage control architecture is implemented by a plurality of nodes, where a node comprises combinations of executable containers that execute in cooperation with virtual machines running above a hypervisor. The containers run in a virtual machine above a hypervisor, and/or can be integrated directly into the operating system of a host node. Sensitive information such as credit card information may be isolated from the containers in a separate virtual machine that is configured to be threat resistant, and which can be accessed through a threat resistant interface module. One of the virtual machines of the node may be a node-specific control virtual machine that is configured to operate as a dedicated storage controller for a node. One of the virtual machines of the node may be a node-specific container service machine that is configured to provide storage-related and other support to a hosted executable container.

Architecture for managing I/O and storage for a virtualization environment using executable containers and virtual machines

Examples of systems are described herein which may dynamically allocate compute resources to recovery clusters. Accordingly, a recovery site may utilize fewer compute resources in maintaining recovery clusters for multiple associate clusters, while ensuring that, during use, compute resources are allocated to a particular cluster. This may reduce and/or avoid vulnerabilities arising from a use of shared resources in a virtualized and/or cloud environment.

Dynamic allocation of compute resources at a recovery site

Architecture for managing i/o and storage for a virtualization environment using executable containers and virtual machines

Methods, systems and computer program products for computer cluster management. Multiple components are operatively interconnected to carry out operations for placing virtual machines onto a multi-tenant computing cluster, where the placement achieves adherence to a set of security requirements. Initially, data characterizing logical CPU resources of the multi-tenant computing cluster are gathered. Upon receipt of a request to place a virtual machine onto a node of the multi-tenant computing cluster, a set of security rules that are used to achieve the set of security requirements associated with the multi-tenant computing cluster are accessed. In accordance with the security rules the virtual machine is assigned to execute in a portion of the logical CPU resources. The virtual machine does not share logical CPU resources with any other tenant.

Security-aware scheduling of virtual machines in a multi-tenant infrastructure

A method for providing external access into a secured networked virtualization environment, includes performing a leadership election amongst nodes of the secured networked virtualization environment to elect a leader node, assigning a cluster virtual IP address to the leader node and generating a reverse tunnel, using a processor, by the leader node to allow for an external entity to communicate with the secured networked virtualization environment.

Mechanism for providing external access to a secured networked virtualization environment

Disclosed is an improved approach to implement virtualization objects in a virtualization system. The virtualization object from a first namespace is cloned as a snapshot that is accessible within a second namespace. To implement this, the virtualization object can be mounted as a target (implemented as a snapshot) that is locally accessible to the host.

Method and system for implementing virtual machine images

Systems and methods for rebalancing storage-oriented workloads across resources of a distributed data storage facility. Communications are initiated between a client computing device and a plurality of storage target devices of a distributed storage system. The distributed storage system comprises one or more computing nodes that can host virtualized controllers. A client computing device interfaced with the distributed storage system uses an IP address to access an initial virtualized controller. Upon detecting a change event, conditions of the computing environment are analyzed to determine rebalancing options. Analysis of the rebalancing options results in identification of an alternative virtualized controller. A redirect message that identifies the alternative virtualized controller is sent to the computing device. The client computing device connects to the alternative virtualized controller. Messages are sent between the client computing device and the alternative virtualized controller to access one of the storage target devices for performing storage I/O protocols.

Rebalancing storage I/O workloads by storage controller selection and redirection

A method and system for managing communication connections in a virtualization environment implemented by a cluster of host machines, each of the host machines comprises a hypervisor, at least one user virtual machine (UVM), a connection manager, and an I/O controller. The system includes a virtual disk accessible by all of the I/O controllers and comprising a plurality of storage devices. The system includes a first host machine of the host machines designated as a leader node, wherein the leader node configured to confirm a second one of the host machines is unreachable; and transmit, in response to the confirmation, an update message to other host machines in the cluster. The update message identifies the unreachable host machine and causes the other host machines to block messages from the unreachable host machine and send an acknowledgement of the update message back to the leader node.

Preventing corruption by blocking requests

Systems and methods for storage resource and computation resource expansion. A method embodiment includes migrating a computing task from an external computing environment to a different computing/storage environment. The method commences by identifying a storage system having virtualized controllers and by identifying a computing device that performs a workload that interfaces with the storage system. The virtualized controllers execute in the second computing environment to manage access to storage target devices by accessing a storage target device identified by an IP address. A particular virtualized controller that is connected to the storage target device is selected and configured to process storage I/O from a migrated workload. A user virtual machine or user executable container is configured to execute the workload on one of the nodes in the computing and storage system within the second computing environment. After migration, the computing task from the external computing environment is discarded or decommissioned.

Efficient scaling of computing resources by accessing distributed storage targets

Communication between VMs running in a clustered virtualization environment and a distributed storage system is managed. The distributed storage system consists of multiple storage/compute nodes. A hypervisor communicates with a controller in a local node on behalf of a VM. The controller will redirect a connection to a second controller on different node. The controller to which the connection is redirected is selected so as to distribute the load evenly across the cluster.

Hypervisor attached volume group load balancing

A system and method for facilitating communication between one or more of a plurality of user virtual machines and external devices is disclosed. The system includes a plurality of uplink bridges configured to facilitate communication between the plurality of user virtual machines and the external devices, a plurality of local bridges, with each of the plurality of user virtual machines being connected to one or more of the plurality of local bridges, and a first multiplexing bridge connected to the plurality of local bridges. The first multiplexing bridge is configured to direct data between the plurality of user virtual machines and the plurality of uplink bridges. The system also includes a second multiplexing bridge connected to the first multiplexing bridge and the plurality of uplink bridges. The second multiplexing bridge is configured to direct the data between the first multiplexing bridge and the plurality of uplink bridges.

Service chaining for multiple uplink bridges in a virtualization environment

A system and method for dynamically adjusting the amount of memory allocated to a virtual machine includes generating, by a memory resizing system, a current memory usage profile for the virtual machine. The memory resizing system and the virtual machine are part of a virtual computing system and the current memory usage profile is generated by mapping, as a function of time, memory usage information from the virtual machine. The system and method also include computing an upper baseline based upon a peak memory usage in the current memory profile, updating an initial memory allocation of the virtual machine based upon the upper baseline and a predetermined threshold for obtaining an initial revised memory allocation, determining a moving average of memory usage from a historical memory usage profile, and updating the initial revised memory allocation based upon the moving average of memory usage for obtaining a final revised memory allocation.

System and method for memory resizing in a virtual computing environment

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New York, NY, United States of America

Miao Cui