REBALANCING IN A FLEET OF STORAGE SYSTEMS USING DATA SCIENCE

    公开(公告)号:WO2022240938A1

    公开(公告)日:2022-11-17

    申请号:PCT/US2022/028698

    申请日:2022-05-11

    Abstract: Rebalancing in a fleet of storage systems using data science including generating, by the cloud-based rebalancing system, a plurality of workload migration scenarios to address a detected workload imbalance among a plurality of workloads in a fleet of storage systems; determining, by the cloud-based rebalancing system, a plurality of movement vectors for each workload migration scenario, wherein each of the plurality of movement vectors describes a consideration factor for migrating a workload of the plurality of workloads within the fleet of storage systems; and generating, by the cloud-based rebalancing system, at least one rebalancing proposal based on the plurality of movement vectors for each workload migration scenario.

    TENANT DATABASE PLACEMENT IN OVERSUBSCRIBED DATABASE-AS-A-SERVICE CLUSTER

    公开(公告)号:WO2022271371A1

    公开(公告)日:2022-12-29

    申请号:PCT/US2022/030455

    申请日:2022-05-23

    Abstract: Placement of a tenant database in an oversubscribed, database-as-a-service cluster comprised of a plurality of nodes is described. The placement may be based on per-node estimates of a probability of resource demand violation if the tenant database is placed on the node. Past resource usage of similar tenant databases subscribed to the cluster that are collected and stored as compressed traces may be used to obtain the estimates. In some examples, based on the estimates, a per-node expected number of resource violations is determined and compared across nodes, where the determined placement minimizes the number of resource violations. In other examples, when the tenant database is being placed in parallel with other tenant databases, a score assigned to each valid configuration for the placement may be modified based on the estimates, where the determined placement is the configuration having a lowest score.

    CLOUD LOAD ORCHESTRATOR
    6.
    发明申请

    公开(公告)号:WO2021262282A1

    公开(公告)日:2021-12-30

    申请号:PCT/US2021/026498

    申请日:2021-04-09

    Abstract: Testing methods and systems are provided for testing a resource manager of an application management system. The testing systems include a load orchestrator configured to obtain an artificial metric that is determined based on a utilization model (e.g., CPU usage, memory allocation, or disk usage, number of webserver sessions). The load orchestrator transmits the artificial metric to applications in a cluster of computing nodes. The applications transmit the artificial metric to the resource manager. In response, the resource manager generates control output for managing applications in the cluster based on the artificial metric (e.g., scaling, load balancing, application placement, failover of applications, or defragmenting data). The utilization model may include executable code for generating artificial metric values. The model may be received as a result of an API call. The load orchestrator may be instantiated in an orchestration framework or in each node of the cluster.

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