Abstract: Embodiments of the present disclosure relate to IO initiator aware data migration. A set of statistical metrics for a replica of a data block on a first node of a plurality of nodes is obtained. The first set of statistical metrics is associated with read operations on the replica. The read operations are operations initiated by a second node of the plurality of nodes. If it is determined that a first statistical metric in the set of statistical metrics exceeds a predefined threshold, the replica is migrated from the first node to the second node.

Abstract: Data-locality-aware task scheduling on hyper-converged computing infrastructures is provided. A plurality of data blocks referenced in an input/output (I/O) request are identified. The I/O request is based on scheduling logic that executes within a container that is deployed on a hyper-converged infrastructure. A block-location mapping table is scanned using a data block identifier that is associated with a present data block of the plurality of data blocks. Physical node(s) of the hyper-converged infrastructure that store the present data block are identified. A container-instance mapping table is scanned using one or more physical node identifiers that are associated with the physical node(s) that store the present data block. Container(s) deployed on physical node(s) that store the present data block are identified. The scheduling logic is provided with a list of identifier(s) that are respectively associated with the containers that are deployed on the physical node(s) that store the present data block.

Abstract: An approach, for fileset based data locality management in Distributed File Systems. A data locality manager receives fileset identifiers and associated block allocation information, for storing in data block locality tables. The data locality manager determines data block locality factors based on the fileset identifiers and the block allocation information, creating a collection of the data block locality factors. The data locality manager stores the collection of the data block locality factors in the data block locality tables. The data locality manager receives the fileset identifiers for determining the collection of the data block locality factors associated to the fileset identifiers and outputs the collection of the data block locality factors.

Abstract: Embodiments of the present disclosure relate to IO initiator aware data migration. A set of statistical metrics for a replica of a data block on a first node of a plurality of nodes is obtained. The first set of statistical metrics is associated with read operations on the replica. The read operations are operations initiated by a second node of the plurality of nodes. If it is determined that a first statistical metric in the set of statistical metrics exceeds a predefined threshold, the replica is migrated from the first node to the second node.

Abstract: Configuration of a multi-tenant distributed file system on a node. Various tenants and tenant clusters are correlated to a distributed file system, and the distributed file system communicates with various tenants through a connector service. The entire distributed file system exists on a physical node.

Abstract: Configuration of a multi-tenant distributed file system on a node. Various tenants and tenant clusters are correlated to a distributed file systems, and the distributed file system communicates with various tenants through a connector service. The entire distributed file system exists on a physical node.

Abstract: Data-locality-aware task scheduling on hyper-converged computing infrastructures is provided. A plurality of data blocks referenced in an input/output (I/O) request are identified. The I/O request is based on scheduling logic that executes within a container that is deployed on a hyper-converged infrastructure. A block-location mapping table is scanned using a data block identifier that is associated with a present data block of the plurality of data blocks. Physical node(s) of the hyper-converged infrastructure that store the present data block are identified. A container-instance mapping table is scanned using one or more physical node identifiers that are associated with the physical node(s) that store the present data block. Container(s) deployed on physical node(s) that store the present data block are identified. The scheduling logic is provided with a list of identifier(s) that are respectively associated with the containers that are deployed on the physical node(s) that store the present data block.

Abstract: An approach, for fileset based data locality management in Distributed File Systems. A data locality manager receives fileset identifiers and associated block allocation information, for storing in data block locality tables. The data locality manager determines data block locality factors based on the fileset identifiers and the block allocation information, creating a collection of the data block locality factors. The data locality manager stores the collection of the data block locality factors in the data block locality tables. The data locality manager receives the fileset identifiers for determining the collection of the data block locality factors associated to the fileset identifiers and outputs the collection of the data block locality factors.