Comm Vault Systems, Inc.

Kuldeep Kumar

Rajesh Polimera

Pramukh Shenoy Bantwal

Jagadeesh B Nuthakki

Rajiv Kottomtharayil

Parag Gokhale

Henry Wallace Dornemann

Jun H Ahn

Sri Karthik Bhagi

Duncan Alden Littlefield

Sarath Cheriyan Joseph

Venkata Chalapathi Sucheth Ramgiri

Madhumitha Mani

Ashwin Gautamchand Sancheti

Prasad Nara

An illustrative storage management appliance is interposed between client computing devices and one or more cloud storage resources. The appliance uses cloud storage resources in conjunction with a network attached storage device configured within the appliance to provide to the client computing devices seemingly unlimited network attached storage on respective network shares. The storage management appliance monitors data objects on the network shares and when a data object meets one or more criteria for archiving, the storage management appliance archives the data object to a cloud storage resource and replaces it with a stub and preview image on the network share. When access to the stub and/or preview image is detected, the storage management appliance restores the data object from the cloud storage resource. The criteria for archiving flexibly allow individual data objects to be archived to cloud storage without archiving frequently-accessed 'neighboring' data objects on the same network share.

Enhanced network attached storage (NAS) services interfacing to cloud storage

Snapshot-based disaster recovery (DR) orchestration systems and methods for virtual machine (VM) failover and failback do not require that VMs or their corresponding datastores be actively operating at the DR site before a DR orchestration job is initiated, i.e., before failover. An illustrative data storage management system deploys proprietary components at source data center(s) and at DR site(s). The proprietary components (e.g., storage manager, data agents, media agents, backup nodes, etc.) interoperate with each other and with the source and DR components to ensure that VMs will successfully failover and/or failback. DR orchestration jobs are suitable for testing VM failover scenarios ('clone testing'), for conducting planned VM failovers, and for unplanned VM failovers. DR orchestration jobs also handle failback and integration of DR-generated data into the failback site, including restoring VMs that never failed over to fully re-populate the source/failback site.

Snapshot-based disaster recovery orchestration of virtual machine failover and failback operations

Certain embodiments described herein relate to an improved selective data backup system. In some embodiments, one or more components in an information management system can determine that a portion of the primary data scheduled for backup was previously backed up or is scheduled to be backed up as part of another backup operation. For example, a data agent performing a cluster-level backup operation for an entire cluster of storage servers may check whether any part of the primary data was previously backed up by a prior server-level backup operation for one of the storage servers in the cluster. If so, the data agent may skip, in the cluster-level backup operation, any portion of the primary data stored in the storage server previously backed up as part of the prior server-level backup operation.

Skipping data backed up in prior backup operations

Enhanced network attached storage (NAS) interoperating with and overflowing to cloud storage resources

Storage of data that no longer has a useful life is established by the data objects' user(s) and overcomes predetermined rules required by information management policies. An illustrative data agent may receive instructions from an illustrative storage manager to perform secondary copy operations for certain data objects. The instructions may instruct that expiry-marked data objects are to be treated based on parsing each data object's user-supplied expiry timeframe. The illustrative system (i) will delete expired data objects including expired secondary copies; (ii) will refrain from making secondary copies of expired data objects; and (iii) if an expiry-marked data object is not expired, the illustrative system will make secondary copies according to the instructions, but will track those expiry-marked secondary copies for future deletion after they expire, (iv) and will delete expired secondary copies even if the original expiry-marked data object has been deleted from the system prior to its expiration.

Organically managing storage of a data object based on an expiry timeframe supplied by a user of the data object

The illustrative systems and methods advantageously reduce the amount of storage space occupied by data that no longer has a useful life&#x2014;as established by the data objects' user(s) and overcoming predetermined rules required by information management policies. An illustrative data agent may receive instructions from an illustrative storage manager to perform secondary copy operations for a given set of data objects. The instructions may generally instruct that expiry-marked data objects are to be treated based on parsing each data object's user-supplied expiry timeframe. The illustrative system (i) will delete expired data objects including expired secondary copies; (ii) will refrain from making secondary copies of expired data objects; and (iii) if an expiry-marked data object is not expired, the illustrative system will make secondary copies according to the instructions from the storage manager, but will track those expiry-marked secondary copies for future deletion after they expire, (iv) and will delete expired secondary copies even if the original expiry-marked data object has been deleted from the system prior to its expiration.

Organically managing primary and secondary storage of a data object based on an expiry timeframe supplied by a user of the data object

Systems and methods that facilitate an information management system to store sets of data, such as backup or secondary copies of production data, to cloud storage libraries in a format native to the cloud storage library are disclosed. The systems and methods create storage policies for the sets of data that identify the cloud storage libraries to which the sets of data are to be stored. Via the storage policies, one or more media agents or servers transfer data blocks of the sets of data to cloud storage SDKs associated with the cloud storage libraries. The cloud storage SDKs then add external metadata, such as metadata associated with a native format for the cloud library to the data blocks, before the data blocks are stored to the cloud storage library.

Storing data to cloud libraries in cloud native formats

Organically managing primary and secondary storage of a data object based on expiry timeframe supplied by a user of the data object

Growing community of inventors

Hyderabad Telangana, India

Kuldeep Kumar