Abstract: In a running distributed data storage system that actively processes I/Os, metadata nodes are commissioned and decommissioned without taking down the storage system and without introducing interruptions to metadata or payload data I/O. The inflow of reads and writes continues without interruption even while new metadata nodes are in the process of being added and/or removed and the strong consistency of the system is guaranteed. Commissioning and decommissioning nodes within the running system enables streamlined replacement of permanently failed nodes and advantageously enables the system to adapt elastically to workload changes. An illustrative distributed barrier logic (the “view change barrier”) controls a multi-state process that controls a coordinated step-wise progression of the metadata nodes from an old view to a new normal. Rules for I/O handling govern each state until the state machine loop has been traversed and the system reaches its new normal.

Abstract: A cloud-based data protection service is disclosed. In an embodiment, the data protection service may support backup of data sets from one or more sites associated with one or more organizations. In an embodiment, deduplication of backup data across multiple sites of an organization and/or multiple sites associated with different organizations may be supported. In an embodiment, backup data may be post-processed in the cloud to insert fingerprints corresponding to data blocks that did not change since a previous backup was performed, to scan the backup for security threats such as viruses, other malware, personally identifiable information, etc. In an embodiment, restore may be supported from the cloud, where restore blocks may be larger than backup data blocks. In another embodiment, restore may be based on blocks that have changed since the most recent backup (or a user-selected backup).

Abstract: An illustrative media agent (MA) in a data storage management system instructs a NAS file server (filer) to restore an MA-created synthesized-copy instead of larger filer-created backup copies. The synthesized-copy is designed only for the particular files to be restored and mimics, and is typically much smaller than, a filer-created backup copy. The synthesized-copy is fed to the filer on restore as a “restore data image.” When receiving a restore request for certain backed-up data files, the MA synthesizes the synthesized-copy on the fly. The MA generates a header mimicking a filer-created backup header; extracts files from filer-created backup copies arranging them within the synthesized-copy as if in filer-created backups; and instructs filer to perform a full-volume restore from the synthesized-copy. The MA serves the synthesized-copy piecemeal as available, rather than waiting to synthesize the entire synthesized-copy. The synthesized-copy is not stored at the MA.

Abstract: A native cloud-based VM in a cloud computing environment of choice is live-mounted without requiring nesting techniques. All operating system data needed to live-mount the VM is accessed over ISCSI. The disclosed technology: supports both Windows and Unix-like (e.g., Linux) operating systems; handles any number of partitions of the root file system without repeated mounting, exporting, and unmounting; and uses only internet protocols (e.g., HTTP, (SCSI) to live-mount the VM. The live-mounted VM gains access to a variety of secondary copies, e.g., made with file-level techniques or with block-level techniques, made within or outside the public cloud computing environment, made from other VMs having the same or a different hypervisor than the public cloud computing environment, and/or made from non-virtualized sources. Access to snapshots as a data source for the live-mounted VM is also disclosed. Thus, a streamlined and source-agnostic technology is disclosed for live-mounting VMs in a public cloud.

Abstract: Backup data is leveraged to determine whether primary data has been encrypted by malware. The disclosed approach does not rely on recognizing particular malware instances or malware provenance, and thus can be applied to any body of data. Even a novel and previously unknown malware attack can be detected in this way. An illustrative data storage management system analyzes secondary copies it created over time, applies a multi-factor analysis to data recovered from the secondary copies and, based on the analysis, infers whether the primary data from which the secondary copies were created may be encrypted. The present approach uses successive versions of backup copies to find indicia of malware encryption, rather than trying to trace or identify the malware itself. Indicia of entropy correlate highly with encryption, such as encryption performed by malware attacks. Conversely, indicia of similarity correlate highly with lack of encryption of successive versions of documents.

Abstract: An illustrative data storage management system uses a control layer that controls information content presented to users and ensures information privacy between diverse tenants and/or resellers who share the system. The system populates a relationship database as transactions roll in (intake processing), and uses information in the relationship database later when processing responses (output processing). The relationship database comprises associations between e.g., a company ID and any number of entities that were created by or on behalf of the company or that are related to the company's service in the system. The control layer parses raw results that are responsive to requests for information and prevents others' information from being included in the responsive message(s). The techniques disclosed herein are not limited to shared systems managed by service providers, and may be implemented in fully owned and operated systems to add security and privacy among diverse users and/or departments.

Abstract: 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.

Abstract: A client computing device includes an entropy driver and a volume driver for protecting the client computing device against potential ransomware. The entropy driver is configured to determine one or more entropy values for a file in response to a determination that the file has been modified or changed. The determined entropy value may then be compared with a known entropy value for a filetype of the changed or modified file. Where the known entropy value and the determined entropy value differ, the volume driver may engage one or more protection operations to secure the client computing device from further corruption and/or modifications by potential ransomware and/or malware. The protection operations may include revoking and/or restricting one or more permissions on one or more storage volumes of the client computing device and backing up one or more files of the client computing device to secondary storage.

Abstract: Techniques are disclosed relating to providing protection groups and rapid determination of expired objects and associated storage resources in a cloud-based backup storage context. In various embodiments, the disclosed techniques include generating, by a computing system, incremental backup data for a backup based on protection group information, including a set of cloud-based key-value data store buckets, filter information, and policy information. Disclosed techniques also include rapid determination of expired objects and associated storage resources. Disclosed techniques may advantageously provide a centralized view across buckets, accounts, and regions and allow users to target specific subsets of their data stores for backup, which may improve performance and reduce backup storage costs, relative to traditional techniques.

Abstract: The present inventors devised a holistic approach for protecting serverless applications in single-cloud, multi-zone, multi-cloud, and/or non-cloud data center computing environments. An illustrative data storage management system discovers application assets, relationships, and interoperability dependencies and creates an “application entity” that references the various assets. Protection preferences apply to the application entity as a whole. An orchestration function in the system coordinates storage management operations (e.g., backup, replication, live synchronization, etc.) in a suitable order of operations gleaned from asset dependencies, if any. A set of copies of the application's discovered assets are generated in coordinated fashion and represent a point-in-time copy of the application. The point-in-time copy can be restored and/or migrated to other computing services by the data storage management system.

Abstract: A system for performing continuous transaction log backups with minimal resource usage of the client computing devices that are processing the transactions is disclosed. The system detects at least one input/output (I/O) activity at a client computing device. The I/O activity can be associated with at least one database operation performed via the client computing device. The system then executes one or more native commands to backup transactions log data associated with the detected I/O activity to a virtualized location. Backing-up the transactions log data comprises dynamically identifying a mount path location corresponding to the virtualized location, and transferring the transactions log data to the dynamically identified mount path using the one or more native commands. The system can then perform data processing operations (for example, data chunking and deduplicating) on the transactions log data after it is received at the dynamically identified mount path location.

Abstract: An illustrative data storage management system comprises a management database that stores administrative preferences and system configurations, as well as results and/or statistics of completed secondary storage operations, i.e., information needed by the system to protect customers' data and to track and recover the protected data, including secondary copies such as backup copies, archive copies, etc. The disclosed data storage management system is configured to protect its own system data subject to a very aggressive (short) Recovery Point Objective (RPO), by using an innovative infrastructure that enables the system's storage manager to fail over to any number of other failover destination storage managers, each one comprising a destination management database. An illustrative database granularly tracks whether each and every transaction log file has been successfully applied to each and every destination management database to synchronize with the source management database.

Abstract: An illustrative data storage management system protects data in a replicated multi-node system (“cluster”). The illustrative system creates a new administrative entity (“pseudo-client”) that represents the cluster within the system. The system intelligently performs as an adaptive “set it and forget it” system. Preferences for the pseudo-client, including alternate rules that cover various contingencies in the cluster, need not be reset as the cluster undergoes node failures and/or role changes over time. Rather, the disclosed system adapts, on each successive secondary copy job, to the current configuration of the cluster without requiring a system administrator to provide further input or analysis. This approach ensures that jobs can begin promptly as scheduled or on demand. Component selection is based at least in part on geography/zone and/or network topology considerations, which improves the likelihood of job completion and success, and RPO/RTO service levels are more likely to be met.

Abstract: Described herein are techniques for automating media agent state management. For example, if a media agent is running poorly, then the media agent can be disabled and an alternate media agent can perform secondary copy job operations in place of the poorly running media agent. To determine whether a media agent is running poorly, a storage manager can determine whether the media agent has an anomalous number of failed jobs, pending jobs, and/or long running jobs and/or can determine whether the amount of resources used by the media agent is high or is increasing constantly, at a constant rate, or at a near constant rate.

Abstract: Systems and processes disclosed herein perform an automatic remediation process. The automatic remediation process may be a log-based remediation process. Systems disclosed herein may obtain log files from an information management system and determine the occurrence of errors at the information management system based on error codes included in the logs. Further, the systems may access a knowledgebase to determine whether solutions for the errors have been previously generated. The solutions may include patches or hotfixes that can be applied to the information management system without removing user-access or stopping execution of the information management system. The systems may automatically update the information management system to address the errors. Alternatively, or in addition, the systems may alert a user, such as an administrator, of the existence of a solution to the error, and whether the solution may be applied without interrupting service or access to the information management system.

Abstract: The present inventors devised techniques and technologies that streamline the protection of data stored on shared file storage e.g., on file servers, network-attached storage (NAS), share drives, network shares, etc., in a data storage management system. Some embodiments feature a proxy-less backup configuration in which backup services hosts are assigned to perform a secondary copy job, at job runtime, based on host attributes relative to the data source. Some embodiments are configured to, at job runtime, automatically resolve data paths to the source data, and automatically mount the data paths, rather than requiring data paths to be expressly pre-administered on all possible candidate backup machines. Some embodiments automatically protect data from shared file storage that was not expressly given a backup plan (“undefined” data) by applying default preferences for protecting undefined data.

Abstract: 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.

Abstract: Artificial intelligence (AI), preferably a generative AI (Gen-AI) technology, powers an illustrative “dynamic API service” that interoperates with or within a data resiliency system that has well-defined API(s) for communicating with it. The illustrative dynamic API service is configured to recognize incoming information from an originator, which may arrive unstructured or in a format that is incompatible with the API(s). The illustrative dynamic API service interprets the incoming information, identifies pertinent components in the data resiliency system, issues API call(s) to the system components, and organizes response(s) to the originator. In some embodiments, the illustrative dynamic API service uses or incorporates Gen-AI technology to perform some of the disclosed features and functions. The Gen-AI training corpus preferably includes information extracted from the data resiliency system itself. The originator systems also may employ Gen-AI, and some embodiments function in an AI-to-AI configuration.

Abstract: An illustrative “dynamic API service” interoperates with a data storage management system that has well-defined API(s). The illustrative dynamic API service is configured to recognize information received from an originator, but the information arrives unstructured or is otherwise incompatible with the API(s). The illustrative dynamic API service interprets the incoming information, identifies pertinent system components in the system, issues API call(s) to the system components, and organizes appropriate response(s). Advantageously, the illustrative dynamic API service is configured to recognize information that is relevant to the data storage management system, and to ignore irrelevant information. Relevant incoming information may include malware alerts, information requests, backup prompts, restore requests, metadata queries, configuration prompts or queries, etc., without limitation.

Abstract: The disclosed approach works without the individualized credentials of failed machines when setting up recovery VMs in a cloud computing environment. Each recovery VMs is customized to properly correspond to the system state of its failed counterpart. An illustrative data storage management system recovers backup data and system states collected from the counterpart computing devices, custom-configures recovery VMs in the cloud computing environment, and injects the desired drivers into each recovery VM during an enhanced bare-metal restore process. The enhanced bare-metal restore process works without the failed computer's credentials. The system also restores the backed up data to recovery volumes attached to the recovery VMs. The present approach is both scalable and secure.