Comm Vault Systems, Inc.

Commvalut Systems, Inc.

Hemant Mishra

Pavan Kumar Reddy Bedadala

Manoj Kumar Pradhan

Gopikannan Venugopalsamy

Dmitriy Borisovich Zakharkin

Hetalkumar N Joshi

Divakar Radhakrishnan

Jayasree Yakkala

Rohit Sivadas

Paramasivam Kumarasamy

Sanath Kumar

Muthusamy Senthilnathan

Sunil Babu Telagamsetti

Ravi Thati

Anand Vibhor

Amey Vijaykumar Karandikar

Jaidev Oppath Kochunni

Chong Liu

Gokul Pattabiraman

Bhavyan Bharatkumar Mehta

Certain embodiments disclosed herein reduce or eliminate a communication bottleneck at the storage manager by reducing communication with the storage manager while maintaining functionality of an information management system. In some implementations, a client obtains information for enabling a secondary storage job (e.g., a backup or restore) from a storage manager and stores the information (which may be referred to as job metadata) in a local cache. The client may then reuse the job metadata for multiple storage jobs reducing the frequency of communication with the storage manager. When a configuration of the information management system changes, or the availability of resources changes, the storage manager can push updates to the job metadata to the clients. Further, a client can periodically request updated job metadata from the storage manager ensuring that the client does not rely on out-of-date job metadata.

Network storage backup using distributed media agents

To perform Recovery Point Objective (RPO) driven backup scheduling, the illustrative data storage management system is enhanced in several dimensions. Illustrative enhancements include: streamlining the user interface to take in fewer parameters; backup job scheduling is largely automated based on several factors, and includes automatic backup level conversion for legacy systems; backup job priorities are dynamically adjusted to re-submit failed data objects with an 'aggressive' schedule in time to meet the RPO; only failed items are resubmitted for failed backup jobs.

Recovery Point Objective (RPO) driven backup scheduling in a data storage management system

Multi-tiered backup indexing

This application discloses a system for processing requests for data in production and archive/backup databases. The system stores a mapping of data in production and archive databases to multiple different data storage locations, including a production system storing at least one production database and an archive system storing at least one archive database. The system receives a data request from an application component, which manages or receives data from a user interface and has received the data request directly from the user interface. The system translates the data request to one or more database queries based on the mapping. The system causes to execute the database queries against data on the production or archive system. The system returns a result of executing the one or more database queries to the application component, where the application component returns the result to the user via the user interface.

Handling user queries against production and archive storage systems, such as for enterprise customers having large and/or numerous files

Certain embodiments disclosed herein reduce or eliminate a communication bottleneck at the storage manager by reducing communication with the storage manager while maintaining functionality of an information management system. In some implementations, operations performed as part of a backup process may be stored in transaction logs. These transaction logs may include information about a transaction performed between the client computing system and the network storage that hosts the backup of the client computing system. The transaction logs may be provided to a secondary storage system that can be used to form a backup index. The backup index may be used to facilitate accessing the data stored at the network storage. Advantageously, generating the transaction logs and separating the generation of the backup index from the backup process can reduce resource usage during performance of the backup and speed up the backup process while further reducing interaction with the storage manager.

Transaction log index generation in an enterprise backup system

Backup-based media agent configuration

This application discloses a server for handling data reporting requests in a system that also comprises storage managers, primary storage devices, and secondary storage devices connected over one or more networks. The server receives, from each storage manager, a copy of data associated with the storage manager, and stores the received copies in one or more local databases. The server builds offline one or more indices for part or all of the received copies to improve query processing against the one or more local databases. Next, the server receives a request over a network from one of the storage managers or a standalone console, which received the request from a user for a report of data associated with the storage managers. The server produces a data report in response to the request, using the one or more indices and without impacting performance of the storage managers.

Efficient database search and reporting, such as for enterprise customers having large and/or numerous files

This application discloses a system for presenting data to a user based on requests to move data from primary storage to secondary storage. The system receives a request to move data that satisfies at least one criterion, from primary to secondary data storage. The system then identifies an initial database query from the request, and further builds a nested database query from the initial database query according to a database schema. Next, the system estimates a size of a result of executing the nested database query. Finally, the system provides for display to the user the estimated size.

Predicting scale of data migration

To perform Recovery Point Objective (RPO) driven backup scheduling, the illustrative data storage management system is enhanced in several dimensions, including an illustrative enhanced data agent and an illustrative enhanced storage manager. Illustrative enhancements include: streamlining the user interface to take in fewer parameters; backup job scheduling is largely automated based on several factors, and includes automatic backup level conversion for legacy systems; backup job priorities are dynamically adjusted to re-submit failed data objects with an 'aggressive' schedule in time to meet the RPO; only failed items are resubmitted for failed backup jobs.

Recovery point objective (RPO) driven backup scheduling in a data storage management system using an enhanced data agent

Recovery point objective (RPO) driven backup scheduling in a data storage management system

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Englishtown, NJ, United States of America

Hemant Mishra