Comm Vault Systems, Inc.

Bhavyan Bharatkumar Mehta

Anand Vibhor

Amey Vijaykumar Karandikar

Parag Gokhale

Mrityunjay Upadhyay

Rajiv Kottomtharayil

Jun H Ahn

Hemant Mishra

Tirthankar Chatterjee

Gokul Pattabiraman

Aaron E Bilbrey

Niteen Jain

Sri Karthik Bhagi

Pavan Kumar Reddy Bedadala

Prosenjit Sinha

Manoj Kumar Pradhan

Marcelo Dos Reis Mansano

Jagadeesh Narayanan Kallidaikurichi Swaminathan

Suraj Bharech

An information management system according to certain aspects can implement application archiving. The system may archive one or more applications on computing devices to make more storage space available on these devices. The system can determine which applications on client computing device to archive based on various factors. Some examples of factors can include frequency of use, application type, amount of application data and/or storage, user and/or device location, etc. The data to be archived can include one or more executable file(s), metadata, actual data, etc. After an application is archived, the system can generate a placeholder for the application; a placeholder can include information for restoring the archived application.

Archiving applications in information management systems

An improved information management system is described herein in which the information management system can evaluate the deduplication performance of secondary copy operations and dynamically adjust the manner in which secondary copy data is created to minimize the negative effects of performing deduplication. Furthermore, the improved information management system can improve deduplication performance by applying different storage policies to different types of applications running on a client computing device. Moreover, the improved information management system can automatically detect the region of a client computing device and apply an appropriate information management policy to the client computing device to avoid inconsistencies or other errors resulting from administrator control.

Performing secondary copy operations based on deduplication performance

A system or method for managing an auxiliary data location and a secondary data location. A client computing device may have secondary copies of its primary data stored at a secondary storage device, as well as auxiliary copies of the secondary copies at an auxiliary storage device. The client computing device may move from one geographic location that is near the secondary storage device to a second geographic location that is far from the secondary storage device, but closer to the auxiliary storage device. A method is provided with input signals in response to the move, and outputs a probability value that the move is temporary or permanent. Based on the output, a storage manager that manages the client computing device may then direct the client computing device to use the auxiliary storage device for storing secondary copies.

Geo-location-based data replication

Embodiments are described for distributed and scalable client-based storage management and microservices-based storage management, which can operate in combination. Embodiments distribute responsibilities and client-specific information needed for storage management jobs away from a central storage manager and its management database. New features and components minimize communications to/from the storage manager and ensure the integrity and synchronization of data being distributed. The management database at the storage manager retains its role as repository of information for the data storage management system as a whole, yet without being a bottleneck to storage operations. Improvements are implemented within the storage manager, through new functionality added to clients, and further through a new micro-server component interposed between storage manager and clients.

Distributed and scalable client-based and microservices-based storage management

An illustrative data storage management system enables a Tenant to retain control over criteria for protecting the Tenant's data, and hides details of the Service Provider's infrastructure. The Service Provider may have many data centers, each one represented within the system by a Resource Pool with attributes that reflect the infrastructure resources of the corresponding data center. A system analysis, which is triggered by the Tenant's choices for data protection, keys in on a suitable Resource Pool. The system analysis identifies suitable system resources within the Resource Pool and associates them to the data source. Subsequent data protection jobs invoke proper system components based on the associations created by the system analysis. In some embodiments, the system will invoke infrastructure resources created on demand when a data protection job is initiated rather than being pre-existing resources.

Using resource pool administrative entities in a data storage management system to provide shared infrastructure to tenants

A client computing device receives a behavior model corresponding to a user group associated with a user. The behavior model has been trained with monitored user interactions of one or more files associated with the user group. The client computing device further mounts a snapshot of a file and determines, based on the behavior model, which files of the mounted snapshot to transfer to a locally accessible cache. During use of the client computing device, the client computing device may determine whether the mounted snapshot is accessible. If the mounted snapshot is not accessible, the client computing device may selectively delete, based on the behavior model, one or more of the files stored in the locally accessible cache. If the mounted snapshot is accessible, the client computing device may update the one or more files of the locally accessible cache with monitored user interactions with the mounted snapshot.

Intelligent cache management for mounted snapshots based on a behavior model

A system may measure one or more metrics relating to the performance of a job for a set of occurrences of the job with respect to a data set. The measurements may be used to predict a completion time for a subsequent job or phase of the job on the data set. This prediction may be used to present a more accurate indication of a job completion status on the data set. The process may be repeated or performed separately for each client or set of data to provide an individualized progress meter or indicator. Thus, in some cases, variances in the data or computing systems may be reflected in the displayed progress of the job providing for a more accurate indication of job progress.

Dynamic computing progress tracker

An information management system implements a geo-location-based data replication using a machine-learning algorithm implemented by a client computing device. The client computing device may create secondary copies at a secondary storage device, wherein a secondary storage computing device creates auxiliary copies of the secondary copies at an auxiliary storage device. The client computing device may move from one geographic location that is near the secondary storage device to a second geographic location that is far from the secondary storage device, but closer to the auxiliary storage device. The machine-learning algorithm is provided with input signals in response to the move, and outputs a probability value that the move is temporary or permanent. Based on the output from the machine-learning algorithm, a storage manager that manages the client computing device may then direct the client computing device to use the auxiliary storage device for storing secondary copies.

In general, a data synchronization management system is disclosed in which files (and/or other data) are synchronized among two or more computing devices. Synchronization policies specify files to be synchronized based on selected criteria including file data, metadata, and location information. In general, files are initially copied from a primary client computing device to secondary storage. Thereafter, files to be synchronized are identified from the secondary storage and copied to other computing devices. Additionally, synchronized files may be viewed and accessed through a cloud and/or remote file access interface.

Data synchronization management

Described herein are techniques for better understanding problems arising in an illustrative information management system, such as a data storage management system, and for issuing appropriate alerts and reporting to data management professionals. The illustrative embodiments include a number of features that detect and raise awareness of anomalies in system operations, such as in deduplication pruning operations. Such anomalies can include delays in the processing of archive files to be deleted and/or delays in the generation of the list of archive files to delete. Anomalies are characterized by frequency anomalies and/or by occurrence counts. Utilization is also of interest for certain key system resources, such as deduplication databases, CPU and memory at the storage manager, etc., without limitation. Predicting low utilization periods for these and other key resources is useful for scheduling maintenance activities without interfering with ordinary deduplication pruning operations and/or other data protection jobs.

Anomaly detection in deduplication pruning operations

Described herein are techniques for better understanding problems arising in an illustrative information management system, such as a data storage management system, and for issuing appropriate alerts and reporting to data management professionals. The illustrative embodiments include a number of features that detect and raise awareness of anomalies in system operations. Categories of interest include events and job anomalies, such as long-running jobs and job success/failure rates. Anomalies are characterized by frequency anomalies and/or by occurrence counts. Utilization is also of interest for certain key system resources, such as deduplication databases, CPU and memory at the storage manager, etc., without limitation. Predicting low utilization periods for these and other key resources is useful for scheduling maintenance activities without interfering with ordinary data protection jobs.

Anomaly detection in data protection operations

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

A region-based distributed information management system is described herein in which some or all of the operations typically performed by a centralized storage manager can be distributed to storage managers located in the various geographic regions. These regional storage managers can manage components of the information management system located in their respective geographic region, and communicate with the centralized storage manager (also referred to herein as a 'master storage manager') for synchronization purposes and/or to hand off operations that cannot be performed by the regional storage manager.

Region-based distributed information management system

An information management system is provided herein that combines data backup and data migration operations such that data appears available in a network-accessible folder when in fact the data is stored as a secondary copy in a secondary storage device. For example, a user can indicate that a first file should be added to the network-accessible folder. A client computing device can transmit the first file to a secondary storage computing device that performs a backup operation to store a backup copy of the first file in the secondary storage device. The secondary storage computing device can also generate an index of the first file, which includes a location of the backup copy of the first file, and transmit the index to a server that manages the network-accessible folder. Thus, the backup copy of the first file can be retrieved if the first file is selected via the network-accessible folder.

Growing community of inventors

Edison, NJ, United States of America

Bhavyan Bharatkumar Mehta