Method and apparatus for data driven and cluster specific version/update control

    公开(公告)号:US10824412B2

    公开(公告)日:2020-11-03

    申请号:US15964928

    申请日:2018-04-27

    Applicant: Nutanix, Inc

    Abstract: A method and apparatus for data driven and cluster specific version/update control. The apparatus includes an automated multi-clusters management apparatus that interfaces with a plurality of remote clusters to provide data driven version/update control on a cluster by cluster basis. Generally, operation includes collection/identification of cluster specific data pertaining to software, hardware, and cluster requirements. The cluster specific data is later compared/analyzed against multi-cluster data pertaining to software releases, hardware characteristics, and known bugs/issues for each. The results of the comparison/analysis can then be ranked according to various metrics to different possible solutions and to differentiate the less desirable results from the more desirable results. Thus, the automated multi-cluster management apparatus provides for selection of versions/updates that is dependent on the cluster specific data. Additionally, the present disclosure provides for scheduling and distribution planning for selected versions/updates.

    System and method for managing a remote office branch office location in a virtualized environment

    公开(公告)号:US10917323B2

    公开(公告)日:2021-02-09

    申请号:US16177161

    申请日:2018-10-31

    Applicant: Nutanix, Inc.

    Abstract: A system and method for transmitting data from a local management system of a remote office branch office site in a virtual computing system to a central management system includes assigning, by the local management system, an initial priority to each piece of data, identifying data requested by the central management system since a previous data transmission, and updating the initial priority of each piece of data to an updated priority. The data requested by the central management system is prioritized higher than other data. The system and method also include combining, by the local management system, at least a portion of the data starting with data having a highest priority, into a data packet until the data packet achieves a computed data packet size, transmitting the data packet to the central management system, and updating the initial priority with the updated priority for future data transmissions.

    PLATFORM-AS-A-SERVICE DEPLOYMENT INCLUDING SERVICE DOMAINS

    公开(公告)号:US20210112128A1

    公开(公告)日:2021-04-15

    申请号:US16945306

    申请日:2020-07-31

    Applicant: Nutanix, Inc.

    Abstract: A platform-as-a-service (PaaS) manager abstracts deployment of PaaS software stacks to different computing platforms such that the PaaS software stacks provide a common platform to host an application despite differences in the underlying architectures of the computing platforms. Each PaaS software stack is hosted on a service domain installed on a respective one of the computing platforms, and includes an operating system and provides access to a set of services for execution of applications. The some examples, the different computing platforms include multiple different cloud architectures.

    Policy-based data deduplication
    6.
    发明授权

    公开(公告)号:US10922280B2

    公开(公告)日:2021-02-16

    申请号:US15949989

    申请日:2018-04-10

    Applicant: Nutanix, Inc.

    Abstract: A data storage site receives data from different data producer sites. Each of the data producer sites has a particular relationship to the data storage site, and each particular relationship carries corresponding data storage policies, constraints and commitments. When a data storage site receives a data storage request from a data producer, and that particular data is already present from a prior storage operation at the data storage site, the characteristics of the policies, constraints and commitments that were applied when that data was saved by the prior storage operation are reconciled with the policies, constraints and commitments of the requesting data producer. Deduplication logic reconciles different sets of policies, constraints and commitments such that the data can be effectively deduplicated by saving data-producer-specific metadata. Alternatively, the data can be effectively deduplicated by promoting the storage of the data so it covers a broader set of policies, constraints and commitments.

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