Comm Vault Systems, Inc.

Tinton Falls, Inc.

Parag Gokhale

Rajiv Kottomtharayil

Anand Prahlad

Rahul S Pawar

Manoj Kumar Vijayan

Amey Vijaykumar Karandikar

Jun Lu

Marcus S Muller

Srinivas Kavuri

David Ngo

Anand Vibhor

Varghese Devassy

Prakash Varadharajan

Manoj Kumar Vijayan Retnamma

Sri Karthik Bhagi

Sanjay Harakhchand Kripalani

Deepak Raghunath Attarde

Yu Albert Wang

Prosenjit Sinha

Manoj Kumar Pradhan

Manas Bhikchand Mutha

Dmitriy Borisovich Zakharkin

Arun Prabu Duraisamy

Vipul Pawale

Pushpendra Singh

Bhavyan Bharatkumar Mehta

Sanath Kumar

Jaya Rama Raju Inavolu

Pavlo Mazur

Henry Wallace Dornemann

Brian Brockway

Bheemesh R Dwarampudi

Robert Keith Brower, Jr

Suresh Parpatakam Reddy

Jared Meade

Yanhui Lu

Jun H Ahn

Michael F Klose

Andrei Erofeev

Sumer Dilip Deshpande

Parminder Singh

Jeremy Alan Schwartz

Duncan Alden Littlefield

Arun Amarendran

Kuldeep Kumar

David W Owen

Pavan Kumar Reddy Bedadala

Andre Duque Madeira

Gopikannan Venugopalsamy

David M Cunningham

Christopher A Alonzo

Marcelo Dos Reis Mansano

Manoj Kumar

Michael Fasulo

Muath S Ali-Ali

Ankur Varsheny

Jaidev Oppath Kochunni

David Alan Oshinsky

Manoj Vijayan Retnamma

Kamleshkumar K Lad

Praveen Kumar Krishnan

Rama Naga Bheemeswara Reddy Dwarampudi

Manoj Kumar Retnamma Vijayan

Data storage operations, including content-indexing, containerized deduplication, and policy-driven storage, are performed within a cloud environment. The systems support a variety of clients and cloud storage sites that may connect to the system in a cloud environment that requires data transfer over wide area networks, such as the Internet, which may have appreciable latency and/or packet loss, using various network protocols, including HTTP and FTP. Methods are disclosed for content indexing data stored within a cloud environment to facilitate later searching, including collaborative searching. Methods are also disclosed for performing containerized deduplication to reduce the strain on a system namespace, effectuate cost savings, etc. Methods are disclosed for identifying suitable storage locations, including suitable cloud storage sites, for data files subject to a storage policy. Further, systems and methods for providing a cloud gateway and a scalable data object store within a cloud environment are disclosed, along with other features.

Data object store and server for a cloud storage environment

An improved content indexing (CI) system is disclosed herein. For example, the improved CI system may include a distributed architecture of client computing devices, media agents, a single backup and CI database, and a pool of servers. After a file backup occurs, the backup and CI database may include file metadata indices and other information associated with backed up files. Servers in the pool of servers may, in parallel, query the backup and CI database for a list of files assigned to the respective server that have not been content indexed. The servers may then request a media agent to restore the assigned files from secondary storage and provide the restored files to the servers. The servers may then content index the received restored files. Once the content indexing is complete, the servers can send the content index information to the backup and CI database for storage.

Distributed framework for data proximity-based task splitting in a content indexing system

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

Techniques for providing data retention services based on a geographic region are disclosed. In one aspect, a location of a computing device is determined. A geographic entity corresponding to the location of the computing device is then determined. A data retention policy is assigned to data of the computing device based on regulations of the geographic entity. Other aspects are also disclosed.

Application of information management policies based on operation with a geographic entity

Indexing preferences generally associate each data source with a type of indexing technology and/or with an index/catalog and/or with a computing device that hosts the index/catalog for tracking backup data generated from the source data. Indexing preferences govern which index/catalog receives transaction logs for a given storage operation. Thus, indexing destinations are defined granularly and flexibly in reference to the source data. Load balancing without user intervention assures that the various index/catalogs are fairly distributed in the illustrative backup systems by autonomously initiating migration jobs. Criteria for initiating migration jobs are based on past usage and going-forward trends. An illustrative migration job re-associates data sources with a different destination media agent and/or index/catalog, including transferring some or all relevant transaction logs and/or indexing information from the old host to the new host.

Heterogeneous indexing and load balancing of backup and indexing resources

Data object store and server for a cloud storage environment, including data deduplication and data management across multiple cloud storage sites

Exemplary systems and methods for archiving data objects using secondary copies are disclosed. The system creates one or more secondary copies of primary data that contains multiple data objects. The system may maintain a first data structure that tracks the data objects for which the system has created secondary copies and the locations of the secondary copies. To archive data objects in the primary data, the system identifies data objects to be archived, verifies that previously-created secondary copies of the identified data objects exist, and replaces the identified data objects with stubs. The system may maintain a second data structure that both tracks the stubs and refers to the first data structure, thereby creating an association between the stubs and the locations of the secondary copies.

Archiving data objects using secondary copies

An information management cell health monitoring system is provided herein that can monitor one or more information management systems, identify any performance issues that are occurring within an information management system, and automatically, or in response to a user input, transmit an instruction to the information management system to execute a workflow to resolve the performance issue(s). For example, the information management cell health monitoring system receives operational data, secondary copy policies, and/or similar data from an information management cells via a network. The information management cell health monitoring system analyzes the received information to identify any issues. If an issue is detected, the information management cell health monitoring system retrieves workflows and determines whether any of the workflows can be used to resolve the detected issue. The information management cell health monitoring system transmits a workflow that resolves the detected issue to the information management system for execution.

Information management cell health monitoring system

An improved content indexing system is disclosed herein that content indexing system combines the functionality of the backup metadata database and the content index database into a single backup and content index database to avoid the need to perform synchronization operations. By using a single backup and content index database, the content indexing system also reduces the computing performance costs that would be associated with the synchronization operations as the amount of indexed content increases, thereby solving scalability issues.

Distributed architecture for tracking content indexing

Virtualization sprawl can lead to virtual machines with no designated periodic backup. If the data associated with these unprotected virtual machines is not backed up, it cannot be restored if needed, leading to system failures. A data storage system identifies and protects the unprotected virtual machines. For instance, the system compares a list of virtual machines with a list of computing devices having a designated backup policy in the data storage system and determines which of the virtual machines are unprotected. The system further automatically categorizes the unprotected virtual machines, identifies those unprotected virtual machines that remain uncategorized, and applies a default backup policy to the uncategorized and unprotected virtual machines to provide protected virtual machines.

Systems and methods to identify unprotected virtual machines

Differential health-check systems and accompanying methods provide health-checking and reporting of one or more information management systems in reference to a first time period before and a second time period after a triggering event. A triggering event may be an upgrade of at least part of the information management system, or a restore operation completed in the information management system for example following a disaster, or any number of other events, etc. The health-checking and reporting may comprise a comparison of one or more performance metrics of one or more components and/or operations of the information management system during the first and second time periods.

Differential health checking of an information management system

Failover systems and methods for performing backup operations, including heterogeneous indexing and load balancing of backup and indexing resources

Growing community of inventors

Marlboro, NJ, United States of America

Parag Gokhale