COLD TIERING MICROSERVICE FOR DEDUPLICATED DATA

    公开(公告)号:US20240362123A1

    公开(公告)日:2024-10-31

    申请号:US18767293

    申请日:2024-07-09

    CPC classification number: G06F11/1453 G06F11/1469 G06F16/215 G06F2201/84

    Abstract: One example method includes identifying objects that each include one or more segments to be transferred from a source storage tier to a target storage tier, determining a total amount of data to be transferred, using a tiering controller to create worker nodes operable to transfer the segments to the target storage tier, where a number of worker nodes created is based on the amount of data, transferring, from the source storage tier to the target storage tier, only those segments of the objects not already present in the target storage tier, and the transferring of the segments is performed by the worker nodes, and for each of the objects, placing metadata associated with that object in a bucket.

    CONTENT INDEXING OF FILES IN VIRTUAL DISK BLOCK-LEVEL BACKUP COPIES

    公开(公告)号:US20240362121A1

    公开(公告)日:2024-10-31

    申请号:US18762887

    申请日:2024-07-03

    Abstract: A streamlined approach analyzes block-level backups of VM virtual disks and creates both coarse and fine indexes of backed up VM data files in the block-level backups. The indexes (collectively the “content index”) enable granular searching by filename, by file attributes (metadata), and/or by file contents, and further enable granular live browsing of backed up VM files. Thus, by using the illustrative data storage management system, ordinary block-level backups of virtual disks are “opened to view” through indexing. Any block-level copies can be indexed according to the illustrative embodiments, including file system block-level copies. The indexing occurs offline in an illustrative data storage management system, after VM virtual disks are backed up into block-level backup copies, and therefore the indexing does not cut into the source VM's performance. The disclosed approach is widely applicable to VMs executing in cloud computing environments and/or in non-cloud data centers. The illustrative content indexing is accomplished without restoring the VM data files being indexed to a staging location.

    DIRECTORY RESTORE FROM REMOTE OBJECT STORE
    3.
    发明公开

    公开(公告)号:US20240362118A1

    公开(公告)日:2024-10-31

    申请号:US18655446

    申请日:2024-05-06

    Applicant: NetApp, Inc.

    CPC classification number: G06F11/1435 G06F11/1469 G06F16/128 G06F2201/84

    Abstract: Techniques are provided for restoring a directory from a snapshot of a volume backed up to an object store. The snapshot may be backed up from a node to the object store, such as a cloud computing environment. A user may want to restore the directory within the volume without having to restore the entire volume, which otherwise would waste computing resources, storage, network bandwidth, and time. Accordingly, the techniques provided herein are capable of restoring just the directory from the snapshot that is stored within the object store. Because snapshot data of the snapshot may be stored across multiple objects within the object store, certain objects are identified as comprising snapshot data (backup data) of the directory and content items within the directory. In this way, the snapshot data of the directory is restored from these objects to a restore directory at a restore target.

    Integration of database with distributed storage system

    公开(公告)号:US12124341B2

    公开(公告)日:2024-10-22

    申请号:US18385245

    申请日:2023-10-30

    Applicant: Rubrik, Inc.

    CPC classification number: G06F11/1469 G06F11/1451 G06F2201/84

    Abstract: Methods, systems, and computer programs are presented for providing backup recoverable ranges in a database system. One method includes an operation for determining if a backup chain is within a recoverable range. The recoverable range defines a time interval in which data from a database system is recoverable to a point in time within the time interval. The method further includes an operation for preserving the backup chain when the backup chain is within the recoverable range. When the backup chain is not within the recoverable range, the method includes operations for checking a retention policy for the backup chain, determining whether to preserve or expire the backup chain based on the retention policy, and preserving the backup chain based on the determination on the retention policy.

    Self-service resolution of unhealthy SDNAS objects

    公开(公告)号:US12111736B1

    公开(公告)日:2024-10-08

    申请号:US18136393

    申请日:2023-04-19

    CPC classification number: G06F11/1469 G06F16/1827 G06F2201/80

    Abstract: A storage system management application User Interface (UI) includes an unhealthy SDNAS object resolution page. A set of SDNAS objects having an unhealthy status is determined from an SDNAS process executing on a base platform. Each unhealthy SDNAS object is identified, and a recovery process for the unhealthy SDNAS object is determined. The set of unhealthy SDNAS objects and the recovery procedures are returned to the unhealthy SDNAS object resolution page of the UI. Controls are provided on the page to receive input related to selection of a single unhealthy SDNAS object, a group of two or more unhealthy SDNAS objects, or all unhealthy SDNAS objects for resolution. In response to selection of one or more unhealthy SDNAS objects, the user interface provides a series of one or more API calls to the base platform to effect resolution of the selected unhealthy SDNAS objects via the SDNAS process.

    ADAPTIVE COMPRESSION WITH PRE-FILTER CHECK FOR COMPRESSIBILITY TO IMPROVE READS ON A DEDUPLICATION FILE SYSTEM

    公开(公告)号:US20240330127A1

    公开(公告)日:2024-10-03

    申请号:US18365192

    申请日:2023-08-03

    CPC classification number: G06F11/1469 G06F11/1453 G06F11/3452 G06F16/1748

    Abstract: Improving the performance of read operations in a restore path of an inline deduplication system utilizing a DDBOOST interface by providing an adaptive compression component for use with DDBOOST applications. A built-in compression mode transfers read data if there are sufficient CPU resources in the server and client to compress and decompress the read data without destabilizing the system. CPU usage is tracked to generate predicted respective client and server CPU usage. These respective predictions are compared to defined maximum threshold usage values. If the predicted values do not exceed the thresholds, compression is used, otherwise the data is transmitted over the network as non-compressed data. A pre-filter is used to first determine whether or not the data would benefit from the built-in compression mode.

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