Hierarchical management of storage capacity and data volumes in a converged system

    公开(公告)号:US10824355B2

    公开(公告)日:2020-11-03

    申请号:US15403069

    申请日:2017-01-10

    IPC分类号: G06F3/06

    摘要: A computer-implemented method according to one embodiment includes identifying a plurality of storage resources. Additionally, the method includes creating a storage capacity, where the storage capacity has a first plurality of associated attributes. Further, the method includes defining one or more data volumes for the storage capacity, where each of the one or more data volumes has a second plurality of associated attributes and inherits the first plurality of associated attributes. Further still, the method includes configuring one or more volume shares for each data volume, where each of the volume shares has a third plurality of associated attributes and inherits the first plurality of associated attributes as well as the second plurality of associated attributes.

    ACCELERATING SOFTWARE BUILDS
    3.
    发明申请

    公开(公告)号:US20180307467A1

    公开(公告)日:2018-10-25

    申请号:US15973565

    申请日:2018-05-08

    发明人: Khalid Ahmed

    IPC分类号: G06F8/41 G06F12/0875

    摘要: A set of source files is stored in a shared storage repository for nodes of a distributed computing environment for software compilation. An object file is created based on at least a portion of the set of source files. A directed acyclic graph (DAG) is generated corresponding to a group of software build tasks and the relationship between the software build tasks based on the set of source files. A replication factor for the object file is determined based on the number of relationships of the object file identified from the DAG. The object file is stored in a local memory cache of at least one of the number of the nodes, wherein the number of the nodes is based on the replication factor for the object file.

    ACCELERATING SOFTWARE BUILDS
    4.
    发明申请

    公开(公告)号:US20180246707A1

    公开(公告)日:2018-08-30

    申请号:US15973567

    申请日:2018-05-08

    发明人: Khalid Ahmed

    IPC分类号: G06F8/41 G06F17/30

    摘要: A set of source files is stored in a shared storage repository for nodes of a distributed computing environment for software compilation. An object file is created based on at least a portion of the set of source files. A directed acyclic graph (DAG) is generated corresponding to a group of software build tasks and the relationship between the software build tasks based on the set of source files. A replication factor for the object file is determined based on the number of relationships of the object file identified from the DAG. The object file is stored in a local memory cache of at least one of the number of the nodes, wherein the number of the nodes is based on the replication factor for the object file.

    Accelerating software builds
    7.
    发明授权

    公开(公告)号:US10048954B2

    公开(公告)日:2018-08-14

    申请号:US15271700

    申请日:2016-09-21

    发明人: Khalid Ahmed

    IPC分类号: G06F8/41 G06F17/30

    摘要: A set of source files is stored in a shared storage repository for nodes of a distributed computing environment for software compilation. An object file is created based on at least a portion of the set of source files. A directed acyclic graph (DAG) is generated corresponding to a group of software build tasks and the relationship between the software build tasks based on the set of source files. A replication factor for the object file is determined based on the number of relationships of the object file identified from the DAG. The object file is stored in a local memory cache of at least one of the number of the nodes, wherein the number of the nodes is based on the replication factor for the object file.

    Automatic diagonal scaling of workloads in a distributed computing environment

    公开(公告)号:US10812407B2

    公开(公告)日:2020-10-20

    申请号:US15819225

    申请日:2017-11-21

    摘要: Embodiments for automatic diagonal scaling of workloads in a distributed computing environment. For each of a plurality of resources of each of a plurality of application instances, a determination as to whether a change in allocation of at least one of the plurality of resources is required. Operations requirements are computed for each of the plurality of application instances, the computed requirements including vertical increase and decrease operations, and horizontal split and collapse operations. The vertical decrease and horizontal collapse operations are first processed, the vertical increase and horizontal split operations are ordered, and the vertical increase and horizontal split operations are subsequently processed based on the ordering, thereby optimizing application efficiency and utilization of the plurality of resources in the distributed computing environment.