Nutanix, Inc.

Jaya Singhvi

Binny Sher Gill

Miao Cui

Tabrez Parvez Memon

Ajaykrishna Raghavan

Varun Kumar Arora

Dmitri Bronnikov

Minghui Yang

Timothy Sujay Isaacs

Peihong Huang

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

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

Systems and methods for managing access to storage devices in a distributed data storage environment. Embodiments operate to manage communications between a client computing device and storage target devices in a distributed storage system. The distributed storage system comprises one or more computing nodes and at least one storage target device. A client computing device interfaced with the distributed storage system uses an IP address to access a leader virtualized controller. Upon receipt of a storage access protocol message by the leader virtualized controller elected from a set of virtualized controllers, a redirect message comprising a second IP address that identifies a second virtualized controller is sent to the client computing device. The client computing device connects to the second virtualized controller. Messages are sent between the client computing device and the second virtualized controller, which in turn accesses the storage target device to carry out storage I/O protocol messaging.

Efficient scaling of distributed storage systems

Dynamic erasure coding for computing and data storage systems. A method embodiment commences upon accessing a set of fault tolerance policy attributes associated with the computing and data storage system. The topology of the system is analyzed to form mappings between the computing nodes of the system and the availability domains of the system. Based on the fault tolerance policy attributes, the topology, and the generated mapping, a plurality of feasible erasure coding configurations are generated. The feasible erasure coding configurations are scored. One or more high-scoring feasible erasure coding configurations are selected and deployed to the computing and data storage system. The method is repeated when there is a change in the fault tolerance policy attributes or in the topology. Depending on the topology and/or the nature of a change in the topology, more than one erasure coding configurations can be deployed onto the computing and data storage system.

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Cupertino, CA, United States of America

Jaya Singhvi