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.
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.
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 21/78 - Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer to assure secure storage of data
3.
SYNTHESIZING A RESTORE IMAGE FROM ONE OR MORE SECONDARY COPIES TO FACILITATE DATA RESTORE OPERATIONS TO A FILE SERVER
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.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 3/06 - Digital input from, or digital output to, record carriers
4.
ANALYSIS OF BACKUP COPIES TO IDENTIFY MALWARE-ENCRYPTED PRIMARY DATA
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.
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.
H04L 41/046 - Network management architectures or arrangements comprising network management agents or mobile agents therefor
H04L 41/0895 - Configuration of virtualised networks or elements, e.g. virtualised network function or OpenFlow elements
H04L 41/40 - Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using virtualisation of network functions or resources, e.g. SDN or NFV entities
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
H04L 67/568 - Storing data temporarily at an intermediate stage, e.g. caching
6.
EFFICIENT COLLECTION AND REPORTING OF OPERATION-RELATED METRIC DATA IN A CLOUD ENVIRONMENT
The present application discloses an efficient system and method for collecting, managing, and reporting operation-level metrics of data interactions with cloud storage. A media agent is configured to collect data about operations performed on cloud storage. The system is configured to capture, process, and report detailed metrics with enhanced efficiency and granularity. The media agent accumulates this data in a cache memory. In a predefined cycle, the collected data from the cache is transferred to a local file. The system further integrates the data with job-related data stored at a management database. By correlating the metrics data with this job-related information, the system can produce detailed reports that offer insights into usage patterns, efficiency, and performance across different tenants.
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.
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.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/176 - Support for shared access to filesFile sharing support
Because Kubernetes clusters can be ephemeral, backing up in-cluster data to storage outside the cluster is important. Prior art solutions used the cluster's API server, which facilitates communications with the cluster control plane, to transfer backup data through the API server. However, the API server as a data transfer node has resiliency weaknesses and can slow down backup job performance. The present solution provides a more streamlined and scalable approach, which circumvents the API server and additionally includes more robust error checking, log capture, and realtime job monitoring to provide improved data protection resilience. The disclosed approach employs a “sponsor” data agent outside the cluster and temporarily deploys a specialized backup resource within the cluster during a backup job, such as a lightweight Kubernetes File Client and/or an enhanced File System Data Agent, both of which present substantial performance and resiliency advantages over the API server.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 21/64 - Protecting data integrity, e.g. using checksums, certificates or signatures
10.
KUBERNETES DATA PROTECTION USING A CONTAINERIZED FILE SYSTEM DATA AGENT
Because Kubernetes clusters can be ephemeral, backing up in-cluster data to storage outside the cluster is important. Prior art solutions used the cluster's API server, which facilitates communications with the cluster control plane, to transfer backup data through the API server. However, the API server as a data transfer node has resiliency weaknesses and can slow down backup job performance. The present solution provides a more streamlined and scalable approach, which circumvents the API server and additionally includes more robust error checking, log capture, and realtime job monitoring to provide improved data protection resilience. The disclosed approach employs a “sponsor” data agent outside the cluster and temporarily deploys a specialized backup resource within the cluster during a backup job, such as an enhanced File System Data Agent and/or a lightweight Kubernetes File Client, both of which present substantial performance and resiliency advantages over the API server.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 21/64 - Protecting data integrity, e.g. using checksums, certificates or signatures
A data storage environment can include one or more virtual machines instantiated on a host computing device. Based on physical location data of the one or more virtual machines received from the host computing device, a storage manager can control the performance of a secondary copy operation on one or more storage units that store virtual machine data associated with the one or more virtual machines and/or the performance of a secondary copy operation on the one or more virtual machines.
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
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. When the enhanced bare-metal restore process completes, each cloud-based recovery VM presents a user interface that, for the first time after the computing device has failed, asks for the individualized credentials of the failed machine.
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
Techniques are disclosed relating to providing fast access to restored data in a cloud storage environment. A computing system stores multiple sets of incremental backup data that reflect changes in data being backed up between backup intervals and metadata that indicates which set of incremental backup data stores a given object. The computing system generates an endpoint for a requesting computing system, where the endpoint supports requests for restored backup data and data responses. In response to a request from the requesting computing system via the endpoint, the computing system queries the metadata based on the request and stores metadata retrieved from the query in a key/value store using object identification information as key data and the retrieved metadata as value data. The computing system provides requested data according to a lazy loading technique, including providing requested data via the endpoint based on the metadata in the key/value store.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
14.
CLOUD-BASED SECURE OPERATION OF A RECOVERY STORAGE MANAGER
A secure data storage management “recovery system” operates in a cloud computing environment that is apart from a source system and source data being protected. A “recovery manager” in the cloud computing environment is responsible for restoring secondary copies that were generated by the source system. The recovery manager gains knowledge (metadata) about the secondary copies by restoring, for its own use, a management database of, and backed up by, the source system. The recovery manager initiates out-of-place restores of the secondary copies to “recovery clients” in the recovery cloud. The recovery system restores, to the recovery cloud, secondary copies from any cloud platform and/or from non-cloud data centers, including secondary copies stored locally, off-cloud by the source system. The recovery manager comprises new features that enforce its isolation from the source system and they act to protect the integrity of the secondary copies generated by the source system.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
09 - Scientific and electric apparatus and instruments
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Business management and consultation in the field of data centers, data processing services, data management, data protection, data security, data resilience, data recovery, and cybersecurity; Business management and consultation in the field of deployment and configuration of computer applications, hardware, and software for data management, data protection, data security, data resilience, computer disaster data recovery, and performance management for physical, virtual, cloud, and hybrid computing environments Downloadable computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Downloadable computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Downloadable computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Recorded computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Recorded computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Recorded computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Downloadable computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data, each while using artificial intelligence; Downloadable computer software for deploying and configuring data storage management and storage area networks, data communications, backing up and restoring computer data, data resilience, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals, each while using artificial intelligence; Downloadable computer software for cloud computing, artificial intelligence, data sharing, data security, data resilience, and access, administration and management of computer applications and computer hardware, and computer application distribution; Downloadable computer software for use in data backup, data protection, data replication, data resilience, computer disaster recovery; Downloadable computer software for data backup, data protection, data replication, data resilience, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Downloadable computer software for use in automation and monitoring of physical and virtual computers with artificial intelligence; Recorded computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data, each while using artificial intelligence; Recorded computer software for deploying and configuring data storage management and storage area networks, data communications, backing up and restoring computer data, data resilience, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals, each while using artificial intelligence; Recorded computer software for cloud computing, artificial intelligence, data sharing, data security, data resilience, and access, administration and management of computer applications and computer hardware, and computer application distribution; Recorded computer software for use in data backup, data protection, data replication, data resilience, computer disaster recovery; Recorded computer software for data backup, data protection, data replication, data resilience, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Recorded computer software for use in automation and monitoring of physical and virtual computers with artificial intelligence; Downloadable chatbot software using artificial intelligence (AI) for data management, data protection, data security, data resilience, and data recovery; Downloadable computer software using artificial intelligence (AI) for deployment and configuration of computer applications, hardware, and software for data management, data protection, data security, data resilience, computer disaster data recovery, and performance management for physical, virtual, cloud, and hybrid computing environments; Recorded computer software for deployment and configuration of computer applications, hardware, and software for data management, data protection, data security, data resilience, computer disaster data recovery, and performance management for physical, virtual, cloud, and hybrid computing environments Entertainment services, namely, providing podcasts in the field of technology, computer software, cybersecurity, cloud computing, artificial intelligence, computer data storage, data storage management, data resilience, disaster recovery, and computer networks; Entertainment services, namely, providing video podcasts in the field of technology, computer software, cybersecurity, cloud computing, artificial intelligence, computer data storage, data storage management, data resilience, disaster recovery, and computer networks; Educational services, namely, conducting workshops, seminars, and training sessions in the field of computer software, computer networks, artificial intelligence, computer data storage, data resilience, and data storage management and distribution of educational materials in connection therewith; On-line journals, namely, blogs featuring technology, computer software, cybersecurity, cloud computing, artificial intelligence, computer data storage, data storage management, data resilience, disaster recovery, and computer networks; Providing on-line videos featuring technology, computer software, cybersecurity, cloud computing, artificial intelligence, computer data storage, data storage management, data resilience, disaster recovery, and computer networks, not downloadable Providing information relating to computer technology via a website; Integration of computer systems and networks; Electronic data storage; Temporary electronic storage of information and data; Technical support, namely, providing computer facilities for the electronic storage of digital data; Technical support services, namely, remote and on-site infrastructure management services for monitoring, administration and management of public and private cloud computing IT and application systems; Computer security services, namely, enforcing, restricting and controlling access privileges of users of computing resources for cloud, mobile or network resources based on assigned credentials; Computer services, namely, integration of private and public cloud computing environments; Computer services, namely, cloud hosting provider services; Technological planning and consulting services in the field of cloud computing technology, infrastructure-as-a-service (IAAS) cloud computing technology, software-as-a-service (SAAS) cloud computing technology, and platform-as-a-service (PAAS) cloud computing technology; Providing virtual computer systems and virtual computer environments through cloud computing; Application service provider (ASP), namely, hosting computer software applications of others; Technical consulting services in the fields of datacenter architecture, public and private cloud computing solutions, and evaluation and implementation of internet technology and services; Computer services, namely, creating computer network-based indexes of information, websites and resources; Creating and designing website based indexes of information for others using information technology; Computer services, namely, on-site management of information technology (IT) systems of others; Computer services, namely, remote and on-site management of the information technology (IT) cloud computing systems of others; Monitoring of computer systems by remote access to ensure proper functioning; Remote computer backup services; Data security consultancy; Technology consultation in the field of cybersecurity; Consulting services in the field of cloud computing; Providing a website featuring on-line non-downloadable software that enables users to download information about data management software and data resilience in the nature of software documentation, company-produced informational material, and information regarding technical issues, and that deploys and configures computer applications, hardware, and software for data management, data protection, data security, data resilience, computer disaster data recovery, and performance management for physical, virtual, cloud, and hybrid computing environments; Cloud computing featuring software for use in creating web-based applications relating to deploying and configuring data management, data storage and backup, data resilience, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, artificial intelligence, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Providing temporary use of on-line non-downloadable software and applications for data management, data protection, data security, data resilience, and data recovery; Providing temporary use of online non-downloadable chatbot software for data management, data protection, data security, data resilience, and data recovery; Providing temporary use of on-line non-downloadable software and applications for data backup, data protection, data replication, data resilience, computer disaster recovery and performance management in data centers, virtual machines, servers, desktops, and virtualization performance management; Providing temporary use of on-line non-downloadable software and applications for use in automation and monitoring of physical and virtual computers; Providing temporary use of on-line non-downloadable software and applications for use in deploying and configuring data backup, data protection, data replication, data resilience, and computer disaster recovery, data security, cybersecurity, and monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments
41 - Education, entertainment, sporting and cultural services
Goods & Services
Conducting, arranging and organizing trade shows and trade fairs for commercial and advertising purposes; Arranging and conducting trade show exhibitions in the field of information technology, computer software, cybersecurity, cloud computing, computer data storage, computer data storage management, disaster recovery, information governance, systems architecture, and computer networks; Conducting virtual trade show exhibitions online in the field of information technology, computer software, cybersecurity, cloud computing, computer data storage, computer data storage management, disaster recovery, information governance, systems architecture, and computer networks; On-line business networking services Entertainment services, namely, providing podcasts in the field of information technology, computer software, cybersecurity, cloud computing, computer data storage, computer data storage management, disaster recovery, information governance, systems architecture, and computer networks; Entertainment services, namely, providing video podcasts in the field of information technology, computer software, cybersecurity, cloud computing, computer data storage, computer data storage management, disaster recovery, information governance, systems architecture, and computer networks; On-line journals, namely, blogs featuring information technology, computer software, cybersecurity, cloud computing, computer data storage, computer data storage management, disaster recovery, information governance, systems architecture, and computer networks; Providing on-line videos featuring information technology, computer software, cybersecurity, cloud computing, computer data storage, computer data storage management, disaster recovery, information governance, systems architecture, and computer networks, not downloadable; Educational services, namely, conducting workshops, seminars, conferences, classes, meetings, and training sessions in the field of information technology, computer software, cybersecurity, cloud computing, computer data storage, computer data storage management, disaster recovery, information governance, systems architecture, and computer networks, and distribution of educational materials in connection therewith; Arranging and conducting of business conferences in the field of information technology, computer software, cybersecurity, cloud computing, computer data storage, computer data storage management, disaster recovery, information governance, systems architecture, and computer networks
17.
Protection of virtual private cloud configurations
The methods and systems described herein provide a solution for protecting configuration data associated with a virtual private cloud. Network configurations, accounts, and/or security data may be collected from the host of the virtual private network using APIs provided by the host. The point-in-time configuration information of a VPC can be used in disaster recovery, migration to a new VPC host, or manage VPC configurations across accounts and regions. During a backup operation of a computing resource within a VPC, one or more processes requests security, network, and/or gateway configuration information from the VPC host. This information may be collected and requested for the entire VPC topology. The VPC configuration information, in the format/output received from the VPC host, is then backed up and stored with the backup of that computing resource in secondary storage.
G06F 12/00 - Accessing, addressing or allocating within memory systems or architectures
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
09 - Scientific and electric apparatus and instruments
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Downloadable computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Downloadable computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Downloadable computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Downloadable computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Downloadable computer software for use in data backup, data protection, data replication, computer disaster recovery; Downloadable computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Downloadable computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Downloadable computer software for use in automation and monitoring of physical and virtual computers; Recorded computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Recorded computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Recorded computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Recorded computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Recorded computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Recorded computer software for use in data backup, data protection, data replication, computer disaster recovery; Recorded computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Recorded computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Recorded computer software for use in automation and monitoring of physical and virtual computers Entertainment services, namely, providing podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Entertainment services, namely, providing video podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Educational services, namely, conducting workshops, seminars, and training sessions in the field of computer software, computer networks, computer data storage, and data storage management and distribution of educational materials in connection therewith; On-line journals, namely, blogs featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Providing on-line videos featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks, not downloadable Providing information relating to computer technology via a website; Integration of computer systems and networks; Consulting services in the field of cloud computing; Electronic data storage; Temporary electronic storage of information and data; Technical support, namely, providing computer facilities for the electronic storage of digital data; Providing a website featuring on-line non-downloadable software that enables users to download information about data management software in the nature of software documentation, company-produced informational material, and information regarding technical issues; Technical support services, namely, remote and on-site infrastructure management services for monitoring, administration and management of public and private cloud computing IT and application systems; Computer security services, namely, enforcing, restricting and controlling access privileges of users of computing resources for cloud, mobile or network resources based on assigned credentials; Providing temporary use of on-line non-downloadable cloud computing software for use in data backup, data protection, data replication, and computer disaster recovery, data security, cybersecurity, and monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Providing temporary use of on-line non-downloadable cloud computing software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, desktops, and virtualization performance management; Providing temporary use of on-line non-downloadable cloud computing software for use in automation and monitoring of physical and virtual computers; Computer services, namely, integration of private and public cloud computing environments; Computer services, namely, cloud hosting provider services; Technological planning and consulting services in the field of cloud computing technology, infrastructure-as-a-service (IAAS) cloud computing technology, software-as-a-service (SAAS) cloud computing technology, and platform-as-a-service (PAAS) cloud computing technology; Providing virtual computer systems and virtual computer environments through cloud computing; Application service provider (ASP), namely, hosting computer software applications of others; Technical consulting services in the fields of datacenter architecture, public and private cloud computing solutions, and evaluation and implementation of internet technology and services; Cloud computing featuring software for use in creating web-based applications relating to data management, data storage and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Computer services, namely, creating computer network-based indexes of information, websites and resources; Creating and designing website based indexes of information for others using information technology; Computer services, namely, on-site management of information technology (IT) systems of others; Computer services, namely, remote and on-site management of the information technology (IT) cloud computing systems of others; Monitoring of computer systems by remote access to ensure proper functioning; Remote computer backup services; Data security consultancy; Technology consultation in the field of cybersecurity
19.
HOLISTIC PROTECTION OF CLOUD-BASED SERVERLESS APPLICATIONS
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. The orchestration function coordinates restore and migration operations, including any cloud-to-cloud or cloud-to/from-non-cloud conversions that might be necessary to activate the application in a different computing environment.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
H04L 67/51 - Discovery or management thereof, e.g. service location protocol [SLP] or web services
20.
Protection Groups for Backing up Cloud-Based Key-Value Stores
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.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
21.
ADAPTIVE DATA PROTECTION FOR A MULTI-NODE DATA CLUSTER
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.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
22.
FILE INDEXING FOR VIRTUAL MACHINE BACKUPS IN A DATA STORAGE MANAGEMENT SYSTEM
An illustrative file indexing approach enhances what was previously possible with hypervisor-free live browsing of virtual machine (VM) block-level backup copies. Capabilities are described for indexing files discovered in VM block-level backup copies, including file content. The illustrative file indexing functionality activates a live-browse session to discover files present within VM block-level backup copies and indexes file names and directory structures as created by an original source VM, resulting in an illustrative file index. The illustrative file indexing functionality optionally indexes file contents within VM block-level backup copies, resulting in an illustrative content index. The file index and content index are retained in persistent data structure(s) stored apart from the VM block-level backup copies. The indexes are searchable without mounting or live-browsing the VM block-level backup copies. In some embodiments the file index and the content index are consolidated. An enhanced storage manager is also disclosed.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
23.
MEDIA AGENT STATE MANAGEMENT BASED ON PERFORMANCE TRENDING ANALYSIS
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.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 3/06 - Digital input from, or digital output to, record carriers
09 - Scientific and electric apparatus and instruments
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Downloadable computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Downloadable computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Downloadable computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Downloadable computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Downloadable computer software for use in data backup, data protection, data replication, computer disaster recovery; Downloadable computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Downloadable computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Downloadable computer software for use in automation and monitoring of physical and virtual computers; Recorded computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Recorded computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Recorded computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Recorded computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Recorded computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Recorded computer software for use in data backup, data protection, data replication, computer disaster recovery; Recorded computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Recorded computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Recorded computer software for use in automation and monitoring of physical and virtual computers Entertainment services, namely, providing podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Entertainment services, namely, providing video podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Educational services, namely, conducting workshops, seminars, and training sessions in the field of computer software, computer networks, computer data storage, and data storage management and distribution of educational materials in connection therewith; On-line journals, namely, blogs featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Providing on-line videos featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks, not downloadable Providing information relating to computer technology via a website; Integration of computer systems and networks; Consulting services in the field of cloud computing; Electronic data storage; Temporary electronic storage of information and data; Technical support, namely, providing computer facilities for the electronic storage of digital data; Providing a website featuring on-line non-downloadable software that enables users to download information about data management software in the nature of software documentation, company-produced informational material, and information regarding technical issues; Technical support services, namely, remote and on-site infrastructure management services for monitoring, administration and management of public and private cloud computing IT and application systems; Computer security services, namely, enforcing, restricting and controlling access privileges of users of computing resources for cloud, mobile or network resources based on assigned credentials; Providing temporary use of on-line non-downloadable cloud computing software for use in data backup, data protection, data replication, and computer disaster recovery, data security, cybersecurity, and monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Providing temporary use of on-line non-downloadable cloud computing software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, desktops, and virtualization performance management; Providing temporary use of on-line non-downloadable cloud computing software for use in automation and monitoring of physical and virtual computers; Computer services, namely, integration of private and public cloud computing environments; Computer services, namely, cloud hosting provider services; Technological planning and consulting services in the field of cloud computing technology, infrastructure-as-a-service (IAAS) cloud computing technology, software-as-a-service (SAAS) cloud computing technology, and platform-as-a-service (PAAS) cloud computing technology; Providing virtual computer systems and virtual computer environments through cloud computing; Application service provider (ASP), namely, hosting computer software applications of others; Technical consulting services in the fields of datacenter architecture, public and private cloud computing solutions, and evaluation and implementation of internet technology and services; Cloud computing featuring software for use in creating web-based applications relating to data management, data storage and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Computer services, namely, creating computer network-based indexes of information, websites and resources; Creating and designing website based indexes of information for others using information technology; Computer services, namely, on-site management of information technology (IT) systems of others; Computer services, namely, remote management of the information technology (IT) systems of others; Monitoring of computer systems by remote access to ensure proper functioning; Remote computer backup services; Data security consultancy; Technology consultation in the field of cybersecurity
09 - Scientific and electric apparatus and instruments
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Business management and consultation in the field of data centers, data processing services, and cybersecurity Downloadable computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Downloadable computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Downloadable computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Downloadable computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Downloadable computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Downloadable computer software for use in data backup, data protection, data replication, computer disaster recovery; Downloadable computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Downloadable computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Downloadable computer software for use in automation and monitoring of physical and virtual computers; Recorded computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Recorded computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Recorded computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Recorded computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Recorded computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Recorded computer software for use in data backup, data protection, data replication, computer disaster recovery; Recorded computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Recorded computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Recorded computer software for use in automation and monitoring of physical and virtual computers Entertainment services, namely, providing podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Entertainment services, namely, providing video podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Educational services, namely, conducting workshops, seminars, and training sessions in the field of computer software, computer networks, computer data storage, and data storage management and distribution of educational materials in connection therewith; On-line journals, namely, blogs featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Providing on-line videos featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks, not downloadable Providing information relating to computer technology via a website; Integration of computer systems and networks; Consulting services in the field of cloud computing; Electronic data storage; Temporary electronic storage of information and data; Technical support, namely, providing computer facilities for the electronic storage of digital data; Providing a website featuring on-line non-downloadable software that enables users to download information about data management software in the nature of software documentation, company-produced informational material, and information regarding technical issues; Technical support services, namely, remote and on-site infrastructure management services for monitoring, administration and management of public and private cloud computing IT and application systems; Computer security services, namely, enforcing, restricting and controlling access privileges of users of computing resources for cloud, mobile or network resources based on assigned credentials; Providing temporary use of on-line non-downloadable cloud computing software for use in data backup, data protection, data replication, and computer disaster recovery, data security, cybersecurity, and monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Providing temporary use of on-line non-downloadable cloud computing software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, desktops, and virtualization performance management; Providing temporary use of on-line non-downloadable cloud computing software for use in automation and monitoring of physical and virtual computers; Computer services, namely, integration of private and public cloud computing environments; Computer services, namely, cloud hosting provider services; Technological planning and consulting services in the field of cloud computing technology, infrastructure-as-a-service (IAAS) cloud computing technology, software-as-a-service (SAAS) cloud computing technology, and platform-as-a-service (PAAS) cloud computing technology; Providing virtual computer systems and virtual computer environments through cloud computing; Application service provider (ASP), namely, hosting computer software applications of others; Technical consulting services in the fields of datacenter architecture, public and private cloud computing solutions, and evaluation and implementation of internet technology and services; Cloud computing featuring software for use in creating web-based applications relating to data management, data storage and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Computer services, namely, creating computer network-based indexes of information, websites and resources; Creating and designing website based indexes of information for others using information technology; Computer services, namely, on-site management of information technology (IT) systems of others; Computer services, namely, remote management of the information technology (IT) systems of others; Monitoring of computer systems by remote access to ensure proper functioning; Remote computer backup services; Data security consultancy; Technology consultation in the field of cybersecurity
09 - Scientific and electric apparatus and instruments
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Downloadable computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Downloadable computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Downloadable computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Downloadable computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Downloadable computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Downloadable computer software for use in data backup, data protection, data replication, computer disaster recovery; Downloadable computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Downloadable computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Downloadable computer software for use in automation and monitoring of physical and virtual computers; Recorded computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Recorded computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Recorded computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Recorded computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Recorded computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Recorded computer software for use in data backup, data protection, data replication, computer disaster recovery; Recorded computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Recorded computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Recorded computer software for use in automation and monitoring of physical and virtual computers Entertainment services, namely, providing podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Entertainment services, namely, providing video podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Educational services, namely, conducting workshops, seminars, and training sessions in the field of computer software, computer networks, computer data storage, and data storage management and distribution of educational materials in connection therewith; On-line journals, namely, blogs featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Providing on-line videos featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks, not downloadable Providing information relating to computer technology via a website; Integration of computer systems and networks; Consulting services in the field of cloud computing; Electronic data storage; Temporary electronic storage of information and data; Technical support, namely, providing computer facilities for the electronic storage of digital data; Providing a website featuring on-line non-downloadable software that enables users to download information about data management software in the nature of software documentation, company-produced informational material, and information regarding technical issues; Technical support services, namely, remote and on-site infrastructure management services for monitoring, administration and management of public and private cloud computing IT and application systems; Computer security services, namely, enforcing, restricting and controlling access privileges of users of computing resources for cloud, mobile or network resources based on assigned credentials; Providing temporary use of on-line non-downloadable cloud computing software for use in data backup, data protection, data replication, and computer disaster recovery, data security, cybersecurity, and monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Providing temporary use of on-line non-downloadable cloud computing software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, desktops, and virtualization performance management; Providing temporary use of on-line non-downloadable cloud computing software for use in automation and monitoring of physical and virtual computers; Computer services, namely, integration of private and public cloud computing environments; Computer services, namely, cloud hosting provider services; Technological planning and consulting services in the field of cloud computing technology, infrastructure-as-a-service (IAAS) cloud computing technology, software-as-a-service (SAAS) cloud computing technology, and platform-as-a-service (PAAS) cloud computing technology; Providing virtual computer systems and virtual computer environments through cloud computing; Application service provider (ASP), namely, hosting computer software applications of others; Technical consulting services in the fields of datacenter architecture, public and private cloud computing solutions, and evaluation and implementation of internet technology and services; Cloud computing featuring software for use in creating web-based applications relating to data management, data storage and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Computer services, namely, creating computer network-based indexes of information, websites and resources; Creating and designing website based indexes of information for others using information technology; Computer services, namely, on-site management of information technology (IT) systems of others; Computer services, namely, remote and on-site management of the information technology (IT) cloud computing systems of others; Monitoring of computer systems by remote access to ensure proper functioning; Remote computer backup services; Data security consultancy; Technology consultation in the field of cybersecurity
09 - Scientific and electric apparatus and instruments
41 - Education, entertainment, sporting and cultural services
42 - Scientific, technological and industrial services, research and design
Goods & Services
Business management and consultation in the field of data centers, data processing services, and cybersecurity Downloadable computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Downloadable computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Downloadable computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Downloadable computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Downloadable computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Downloadable computer software for use in data backup, data protection, data replication, computer disaster recovery; Downloadable computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Downloadable computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Downloadable computer software for use in automation and monitoring of physical and virtual computers; Recorded computer software for information, document and data storage, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Recorded computer software for data storage management and storage area networks, data communications, backing up and restoring computer data, computer disaster recovery, removable storage media management, enterprise data and information management, searching enterprise data, generating reports from databases, replicating and archiving files from one data store to another, developing data analysis applications and data analysis computer software, monitoring, analyzing, reporting and solving performance and data availability issues of application software, databases, network, storage, computer hardware, and computer peripherals; Recorded computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage resources; Recorded computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Recorded computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Recorded computer software for use in data backup, data protection, data replication, computer disaster recovery; Recorded computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Recorded computer software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, and desktops; Recorded computer software for use in automation and monitoring of physical and virtual computers Entertainment services, namely, providing podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Entertainment services, namely, providing video podcasts in the field of technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Educational services, namely, conducting workshops, seminars, and training sessions in the field of computer software, computer networks, computer data storage, and data storage management and distribution of educational materials in connection therewith; On-line journals, namely, blogs featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks; Providing on-line videos featuring technology, computer software, cybersecurity, cloud computing, computer data storage, data storage management, disaster recovery, and computer networks, not downloadable Providing information relating to computer technology via a website; Integration of computer systems and networks; Consulting services in the field of cloud computing; Electronic data storage; Temporary electronic storage of information and data; Technical support, namely, providing computer facilities for the electronic storage of digital data; Providing a website featuring on-line non-downloadable software that enables users to download information about data management software in the nature of software documentation, company-produced informational material, and information regarding technical issues; Technical support services, namely, remote and on-site infrastructure management services for monitoring, administration and management of public and private cloud computing IT and application systems; Computer security services, namely, enforcing, restricting and controlling access privileges of users of computing resources for cloud, mobile or network resources based on assigned credentials; Providing temporary use of on-line non-downloadable cloud computing software for use in data backup, data protection, data replication, and computer disaster recovery, data security, cybersecurity, and monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Providing temporary use of on-line non-downloadable cloud computing software for data backup, data protection, data replication, computer disaster recovery and performance management in data centers, virtual machines, servers, desktops, and virtualization performance management; Providing temporary use of on-line non-downloadable cloud computing software for use in automation and monitoring of physical and virtual computers; Computer services, namely, integration of private and public cloud computing environments; Computer services, namely, cloud hosting provider services; Technological planning and consulting services in the field of cloud computing technology, infrastructure-as-a-service (IAAS) cloud computing technology, software-as-a-service (SAAS) cloud computing technology, and platform-as-a-service (PAAS) cloud computing technology; Providing virtual computer systems and virtual computer environments through cloud computing; Application service provider (ASP), namely, hosting computer software applications of others; Technical consulting services in the fields of datacenter architecture, public and private cloud computing solutions, and evaluation and implementation of internet technology and services; Cloud computing featuring software for use in creating web-based applications relating to data management, data storage and backup, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; Computer services, namely, creating computer network-based indexes of information, websites and resources; Creating and designing website based indexes of information for others using information technology; Computer services, namely, on-site management of information technology (IT) systems of others; Computer services, namely, remote management of the information technology (IT) systems of others; Monitoring of computer systems by remote access to ensure proper functioning; Remote computer backup services; Data security consultancy; Technology consultation in the field of cybersecurity
28.
ARTIFICIAL INTELLIGENCE-BASED APPLICATION PROGRAMMING INTERFACE (API) SERVICE FOR A DATA RESILIENCY SYSTEM
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.
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. In some embodiments, the illustrative dynamic API service uses or incorporates generative artificial intelligence (Gen-AI) to perform some of the disclosed functions. The originator systems also may employ Gen-AI.
This application relates to ransomware detection and data pruning management. Ransomware typically involves an I/O heavy process of encrypting data files and/or deleting or renaming the original files. Thus, ransomware attacks may be detected by analyzing the I/O activity in a given file system. In some embodiments, a software module running on a client machine manages copying, archiving, migrating, and/or replicating of primary data and restoring and/or pruning secondary data (e.g., backup copies of the primary data). When a potential ransomware attack is detected, the software module is immediately stopped so that the software module does not prune any data that may need to be restored. Upon receiving user input that indicates that the client machine is not under a ransomware attack, the software module is allowed to resume its operations, including pruning of the secondary data.
The disclosed cyber threat detection and deception system leverages metadata information collected by the data storage management system. Using the metadata collected by the data storage management system, the cyber threat detection and deception system analyzes that metadata to detect any anomalies. Once suspicious or abnormal behavior is detected in an asset, the cyber threat detection and deception system creates and deploys a cyber deception plan for that asset. The cyber deception plan is implemented by way of deploying sensors or emulation traps in any number of cyber-threat appliances within the data network. Lures or tokens are configured and deployed on the suspected assets themselves to redirect attackers to the emulation traps.
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.
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
33.
PROTECTING CRITICAL INFORMATION OF AN APPLICATION ORCHESTRATOR DEPLOYMENT, SUCH AS AN ETCD DATA STORE IN A KUBERNETES CLUSTER
Protecting configuration data in a clustered container system may include, in some embodiments, protecting an ETCD data store in a Kubernetes cluster. A data storage management system addresses the unique needs of protecting an ETCD data store of a target Kubernetes cluster, as well as protecting non-ETCD data payloads. The illustrative data storage management system defines ETCD as a unique kind of workload. ETCD protection is integrated within the data storage management system, which automatically creates data structures and resources within the system for, and provides special-purpose features to protect, ETCD contents and associated security certificates. One of the special-purpose features deploys a temporary data transfer agent within the target Kubernetes cluster to safeguard an ETCD snapshot and transmit its contents, along with the security certificates, to a backup infrastructure that operates outside of the target Kubernetes cluster. The backup infrastructure comprises components deployed by the data storage management system.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
34.
DATA PROTECTION COMPONENT SCALING IN A CLOUD-BASED DATA STORAGE SYSTEM
Systems described herein may dynamically add one or more proxy agents to a cloud data storage system to process an information management job, such as restore job. Upon completion of the job or at some other appropriate interval, the system can power down and decommission the proxy agents and/or the virtual machines on which the proxies reside according to a cleanup schedule (e.g., at hourly or minute intervals). The system takes into account currently existing proxies or virtual machines when processing a restore request to determine the need for new proxies to service the restore request. In this manner the system can save costs and computing resources through efficient virtual machine deployment and retirement.
A storage manager for an information management system determines whether one or more predetermined conditions have been met for transferring metadata of previously performed backup jobs stored in a first management database. A backup job may correspond to a backup operation of a primary storage device of a first client computing device. In response to a determination that one or more of the predetermined conditions have been met, the storage manager may transfer metadata for a second plurality of backup jobs to a second management database of a recovery manager. The recovery manager may receive a request to restore data to the primary storage device of the first client computing device based on the metadata of the second plurality of backup jobs. A media agent managed by the recovery manager may then restore the requested data to the primary storage device of the first client computing device.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/21 - Design, administration or maintenance of databases
36.
ADAPTIVE RATE THROTTLING FOR CLOUD-BASED SERVICE REQUESTS
Some service providers (e.g., Microsoft's Office 365 services) throttle application or service requests an organization, a user, or device can request from a specific application or a suite of applications/services. This throttling can significantly impact performance for, not only the requesting user/device, but also for other tenants associated with that organization. To limit this imposed external throttling, an intelligent internal adaptive throttling or rate limiting may be implemented. In an embodiment, the system monitors throttling imposed by the service provider. Using this information, the system determines an optimal rate of calls that can made for that service to maximize throughput and performance. The system continuously monitors the throttling and in response dynamically modifies the internal target rate.
H04L 47/12 - Avoiding congestionRecovering from congestion
H04L 47/2475 - Traffic characterised by specific attributes, e.g. priority or QoS for supporting traffic characterised by the type of applications
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
An information management system can detect instances in which data is being stored in a non-standard file path and can alert the user of the client computing device, modify the storage policy to include the non-standard file path, and/or initiate a secondary copy operation to prevent data loss of the data stored in the non-standard file path. For example, a client computing device may execute a filter driver that monitors interactions with files in the file system. The filter driver can identify any non-standard file paths not subject to a storage policy that include files in which interactions occurred. For a non-standard file path, the filter driver can determine whether the frequency of interaction with files in the non-standard file path satisfies a threshold frequency. If the threshold is satisfied, then the filter driver may determine that the files should be subject to the storage policy and take appropriate action.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/17 - Details of further file system functions
G06F 21/64 - Protecting data integrity, e.g. using checksums, certificates or signatures
38.
CLOUD-BASED AIR-GAPPED DATA STORAGE MANAGEMENT SYSTEM
An illustrative cloud-based air-gapped data storage management (destination) system obtains authorized access to other (source) systems' backup copies, replicates those copies within the destination system, parses supplemental metadata included in the source backup copies, and integrates the replica copies into the destination system as though natively created there. Replica copies are integrated as backup copies without first restoring the source backup copies to a native data format. The source system lacks knowledge of or connectivity with the destination system, thus maintaining an “air gap” between the systems. The destination system preferably operates in a cloud computing environment. The destination system uses supplemental metadata from the replica copies to re-create or mimic the source's computing environment and to restore backed up data from the replica copies. The destination system also operates as an autonomous analytics engine, applying value-added services to backed up data pulled from source system(s).
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
39.
MOBILE CONTROL APPLICATION FOR MANAGING AN INFORMATION MANAGEMENT SYSTEM
A control application facilitates interactions with, and configurations of, the information management system that manages one or more client computing devices of an information management system. The control application may be implemented using a variety of modules that allow a user to interact with the information management system services in various ways. Using the control application, a user may view a backup status of the information management system, and view the backup status of specific client computing devices that are managed by the information management system. The user may also search for various entities and/or objects within the information management system using the control application. In addition, a user may view the status of one or more backup jobs configured within the information management system, as well as backup plans that have been established for one or more of the client computing devices.
In order to avoid writing duplicates of blocks of data into a storage platform, any virtual disk within the storage platform may have a de-duplication feature enabled. Or, all virtual disks have this feature enabled. For virtual disks with de-duplication enabled, a unique message digest is calculated for every block of data written to that virtual disk. Upon a write, these message digests are consulted in order to determine if a particular block of data has already been written, if so, it is not written again, and if not, it is written. All de-duplication virtual disks are written to a single system virtual disk within the storage platform. De-duplication occurs over the entire storage platform and over all its virtual disks because all message digests are consulted before a write is performed for any virtual disk. A read for a de-duplication virtual desk reads from the system virtual disk.
An information management system includes a storage manager for managing backup and/or restore operations for one or more client computing devices. The storage manager may be in communication with a resource administrator of a computing resource cluster, wherein the resource administrator instantiates one or more computing pods using the computing resource cluster. The resource administrator may receive a request for computing resources from the storage manager and provision the computing pods based on the request. The resource administrator may then select a pre-configured container image from one or more pre-configured container images based on the computing resource request, wherein the pre-configured container image configures a computing pod to create secondary copies of primary data from a particular primary data source of the information management system. The resource administrator may then communicate a message to the storage manager informing the storage of the availability of the provisioned computing pods.
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.
An information management system according to certain aspects is provided to perform archiving based on third-party application rules and third-party metadata. The system may include a third-party archiving data agent that can access archiving rules and/or metadata of a third-party application. The third-party archiving data agent may be a data agent that can access archiving rules and/or metadata of a third-party application, and can include or be in the form of a plug-in for a particular third-party application. The third-party archiving data agent can decide whether to archive a file associated with a third-party application by checking the third-party metadata associated with the file and determining whether the metadata meets the third-party archiving rules. The system can perform the archiving on behalf of the third-party application, and in certain embodiments, notify the third-party application that the archiving has been completed.
Live mounting a virtual machine (VM) causes the VM to run off a backup copy or snapshot previously taken of a “live” production VM. The live-mounted VM is generally intended for temporary use such as to validate the integrity and contents of the backup copy for disaster recovery validation, or to access some contents of the backup copy from the live-mounted VM without restoring all backed up files. These uses contemplate that changes occurring during live mount are not preserved after the live-mounted VM expires or is taken down. Thus, live mounting a VM is not a restore operation and usually does not involve access to every block of data in the backup copy. However, live mounting provides live VM service in the cloud sooner than waiting for all of the backup copy/snapshot to be restored.
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
According to certain aspects, a system includes a client device that includes a virtual machine (VM) executed by a hypervisor, a driver located within the hypervisor, and a data agent. The VM may include a virtual hard disk file and a change block bitmap file. According to some embodiments the driver intercepts write operations generated by the VM to store data in a sector, determines an identity of the sector based on the intercepted write operation, determines an entry in the change block file that corresponds with the first sector, and modifies the entry in the change block file to indicate that data in that sector has changed. The data agent may generate an incremental backup of the VM based on the change block file in response to an instruction from a storage manager, where the incremental backup includes the data in the sector where data was modified.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
During a data protection operation, a data storage system can collect computing attributes associated with hosting of an application generating data being backed up and may also obtain information relating to physical characteristics of the computing device hosting the application and the data. At the time of migration to a cloud, the system can use the collected attributes and/or information to provision cloud resources. The cloud storage system may accept provisioning requests, and may provide several templates which each specify a cloud resource that can be provisioned upon request. The system may compare the collected attributes with the attributes of the available templates to determine the best match. Then, the system may issue a provisioning request to the cloud provider according to the best-matched template. After provisioning the resources, the system may restore backup data of the application to the cloud storage system to migrate the data.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
G06F 16/21 - Design, administration or maintenance of databases
An information management system according to certain aspects may be configured to generate a snapshot of data relating to a plurality of applications. The system may include a plurality of data agents, wherein each data agent is associated with at least one of a plurality of applications, and data generated by the plurality of applications is stored in a logical volume in primary storage. The system may also include a snapshot manager configured to detect the plurality of applications; check with the plurality of data agents whether the associated applications are in consistent states; obtain a snapshot of the logical volume in response to receiving notifications from the plurality of data agents that the associated applications are in consistent states; and generate mapping information between a particular one of the plurality of applications and a portion of the snapshot relating to the particular one of the plurality of applications.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
A streamlined approach analyzes block-level backups of VM virtual disks and creates both coarse and fine indexes of backed up VM data files in the block-level backups. The indexes (collectively the “content index”) enable granular searching by filename, by file attributes (metadata), and/or by file contents, and further enable granular live browsing of backed up VM files. Thus, by using the illustrative data storage management system, ordinary block-level backups of virtual disks are “opened to view” through indexing. Any block-level copies can be indexed according to the illustrative embodiments, including file system block-level copies. The indexing occurs offline in an illustrative data storage management system, after VM virtual disks are backed up into block-level backup copies, and therefore the indexing does not cut into the source VM's performance. The disclosed approach is widely applicable to VMs executing in cloud computing environments and/or in non-cloud data centers. The illustrative content indexing is accomplished without restoring the VM data files being indexed to a staging location.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 16/13 - File access structures, e.g. distributed indices
49.
CLOUD-BASED DESTINATION FOR BLOCK-LEVEL DATA REPLICATION PROCESSING
Systems and methods disclosed herein improve on current technology for block-level data replication to cloud computing environments. A new system architecture deploys one or more replication tail proxies in a cloud computing environment, locally (at the cloud) tracks replicated data and determines which replicated data meet criteria for reconstructing a desired point-in-time in the cloud, and persists data blocks received at the replication tail proxy until they are processed as recovery points. The disclosed approach presents resiliency and performance advantages. First, the resiliency of block-level data replication to cloud is improved by deploying the replication tail proxy in the destination cloud. Second, a Recovery Time Objective (RTO) is reduced by enabling faster cloud deployment of virtual machines for disaster recovery, failover, and/or test purposes based on the replicated data.
A disclosed framework enables virtually any aggressive Recovery Point Objective (RPO) to be enforced for a production database, without limitation on type of database management system (DBMS) or size of the production database. The framework overcomes technological barriers of the prior art, such as bottlenecks presented by a storage manager computer that traditionally managed database backups. To avoid the bottlenecks, an illustrative data storage management system does not engage the storage manager computer in storage operations that could impact the database RPO. Certain components are added and enhanced to autonomously capture database transaction logs, which are stored securely and persistently away from the DBMS. In a separate and less frequent operation, and with involvement of the storage manager computer, the illustrative system generates secondary copies in their final form. Meanwhile, temporary backup files can be used in restore operations without first being converted into secondary copies.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
51.
DISTRIBUTED DATA STORAGE SYSTEM USING ERASURE CODING ON STORAGE NODES FEWER THAN DATA PLUS PARITY FRAGMENTS
A distributed data storage system using erasure coding (EC) provides advantages of EC data storage while retaining high resiliency for EC data storage architectures having fewer data storage nodes than the number of EC data-plus-parity fragments. An illustrative embodiment is a three-node data storage system with EC 4+2. Incoming data is temporarily replicated to ameliorate the effects of certain storage node outages or fatal disk failures, so that read and write operations can continue from/to the storage system. The system is equipped to automatically heal failed EC write attempts in a manner transparent to users and/or applications: when all storage nodes are operational, the distributed data storage system automatically converts the temporarily replicated data to EC storage and reclaims storage space previously used by the temporarily replicated data. Individual hardware failures are healed through migration techniques that reconstruct and re-fragment data blocks according to the governing EC scheme.
A “backup services container” comprises “backup toolkits,” which include scripts for accessing containerized applications plus enabling utilities/environments for executing the scripts. The backup services container is added to Kubernetes pods comprising containerized applications without changing other pod containers. For maximum value and advantage, the backup services container is “over-equipped” with toolkits. The backup services container selects and applies a suitable backup toolkit to a containerized application to ready it for a pending backup. Interoperability with a proprietary data storage management system provides features that are not possible with third-party backup systems. Some embodiments include one or more components of the proprietary data storage management within the illustrative backup services container. Some embodiments include one or more components of the proprietary data storage management system in a backup services pod configured in a Kubernetes node. All configurations and embodiments are suitable for cloud and/or non-cloud computing environments.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
53.
RESTORING VIRTUAL MACHINE DATA TO CLOUD USING A VIRTUAL SERVER CLOUD FILE SYSTEM
Uploads of restored virtual machine (“VM”) data to cloud storage, e.g., VM restore-to-cloud operations, are performed without having to write whole restored virtual disk files to a proxy server before the virtual disk data begins uploading to cloud. Restored data blocks from a backup source are locally cached, staged for efficiency, and asynchronously uploaded to the cloud page-by-page without tapping mass storage resources on the proxy. Downloads of VM data from cloud storage, e.g., VM backup-from-cloud, are performed without having to download a virtual disk file in its entirety to the proxy server before the backup operation begins generating a backup copy. This speeds up “pulling” VM data from the cloud by pre-fetching and locally caching downloaded data blocks. The cached data blocks are processed for backup and stored page-by-page directly into a secondary copy of the cloud VM virtual-disk file without tapping mass storage resource at the proxy.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 11/16 - Error detection or correction of the data by redundancy in hardware
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
An improved information management system that implements a staging area or cache to temporarily store primary data in a native format before the primary data is converted into secondary copies in a secondary format is described herein. For example, the improved information management system can include various media agents that each include one or more high speed drives. When a client computing device provides primary data for conversion into secondary copies, the primary data can initially be stored in the native format in the high speed drive(s). If the client computing device then submits a request for the primary data, the media agent can simply retrieve the primary data from the high speed drive(s) and transmit the primary data to the client computing device. Because the primary data is already in the native format, no conversion operations are performed by the media agent, thereby reducing the restore delay.
H04L 67/5683 - Storage of data provided by user terminals, i.e. reverse caching
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
H04L 67/565 - Conversion or adaptation of application format or content
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Providing data center management in the nature of management of data processing services including cyber resilience, back-up and disaster recovery, and rebuild of cloud computing services, resources, dynamic and distributed cloud applications and data, and configurations; business management and administration of data centers including cloud environments, configurations, dynamic and distributed cloud applications and data, and dependencies Downloadable and recorded computer software for information, document and data storage, cyber resilience, back-up, and retrieval, namely, to access, retrieve, manage, and recover data stored on magnetic disk, on tape, in the cloud, and by other forms of electronic storage of data; Downloadable and recorded computer software for use in data storage management and storage area networks; downloadable computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; Downloadable and recorded computer software for data and storage management, namely, to back-up, retrieve, recover, replicate, migrate, archive and manage cloud resources; Downloadable and recorded computer software for use in searching enterprise data; Downloadable and recorded computer software for use in developing data analysis applications and data analysis computer software; Downloadable and recorded computer software for use in the field of enterprise data and information management; downloadable computer software for use in cyber resilience, data backup, data protection, data replication, and computer disaster recovery of cloud services and resources including dynamic and distributed cloud applications and data; downloadable computer software for data backup, data protection, data replication, computer disaster recovery and performance management in cloud applications, data centers, virtual machines, servers, and desktops; Downloadable and recorded computer software for replicating and archiving files from one data store to another; Downloadable and recorded computer software for use in removable storage media management; Downloadable and recorded computer software for use in computer disaster recovery and rebuilding of cloud services and resources including dynamic and distributed cloud applications and data; Downloadable and recorded computer software for use in data communications; Downloadable and recorded computer software for monitoring, analyzing, reporting and solving performance and data availability issues of dynamic and distributed cloud applications and data, software, databases, network, storage, computer hardware, and computer peripherals; downloadable computer software for use in automation and monitoring of physical and virtual computers; Downloadable and recorded computer software for generating reports from databases including reports on discovery and mapping of connected cloud resources and reports on data recovery tests and compliance; Downloadable and recorded computer software for connecting to and use of a remote computer network, a remote computer and mobile devices; Downloadable and recorded computer software for backing up and restoring computer data including cloud configurations, resources, dynamic and distributed cloud applications and data, and dependencies; Downloadable and recorded computer software for cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution Computer monitoring services which tracks software performance and processes, sends out historical reports and alerts, and providing back-up of cloud-based computer programs, applications, data, and facilities; application service provider (ASP), namely, hosting computer software applications of others; technical consulting services in the fields of datacenter architecture, public and private cloud computing solutions, and evaluation and implementation of internet technology and services; electronic data storage; computer security services, namely, enforcing, restricting and controlling access privileges of users of computing resources for cloud, mobile or network resources based on assigned credentials; technical support services, namely, remote and on-site infrastructure management services for monitoring, administration and management of public and private cloud computing IT and application systems; providing a web-based system and online portal for others featuring technology that enables users to download information about cloud data management software in the nature of software documentation, company-produced informational material, and information regarding technical issues; Consulting services in the field of cloud computing technology, infrastructure-as-a-service (IAAS) cloud computing technology, software-as-a-service (SAAS) cloud computing technology, and platform-as-a-service (PAAS) cloud computing technology related to discovery and mapping of connected cloud resources and backing up, restoring, and rebuilding computer data including dynamic and distributed cloud applications, cloud configurations, resources, and dependencies; cloud computing featuring software for use in creating web-based applications relating to data management, data storage and backup, cyber resilience, recovery and rebuilding of distributed cloud applications and data, database management, virtualization, networking, collaboration, remote access, remote support, cloud computing, data sharing, data security, and access, administration and management of computer applications and computer hardware, and computer application distribution; technical support, namely, providing computer facilities for the electronic storage of digital data; providing temporary use of online non-downloadable computer software for cyber resilience, data backup, data protection, data replication, computer disaster recovery and performance management in cloud data centers, virtual machines, servers, desktops, and virtualization performance management including rebuilding dynamic and distributed cloud applications and data; computer services, namely, cloud hosting provider services; integration of computer systems and networks; consulting services in the field of cloud computing, cyber resilience, and data back-up and retrieval; providing temporary use of online non-downloadable computer software for use in monitoring computer performance, computer configuration, and change management for physical, virtual, cloud, and hybrid computer environments; providing temporary use of online non-downloadable computer software for use in automation and monitoring of physical and virtual computers including cloud applications, resources, services, configurations, and environments; computer security services, namely, enforcing, restricting and controlling access privileges of users of computing resources for cloud resources based on assigned credentials; Providing temporary use of online non-downloadable computer software for use in data backup, cyber resilience, data protection, data replication, rebuilding, and computer disaster recovery of cloud services and resources including dynamic and distributed cloud applications and data; computer services, namely, creating cloud-based indexes of information for others using information technology; data center management services, namely, providing on-site management of information technology systems of others, providing remote management of information technology systems of others, monitoring of computer systems by remote access to ensure proper functioning, and remote computer backup services; temporary electronic storage of information and data; Providing virtual computer systems and virtual computer environments through cloud computing; Computer services, namely, integration of private and public cloud computing environments including dynamic and distributed cloud applications and data
56.
HYPERVISOR-INDEPENDENT REFERENCE COPIES OF VIRTUAL MACHINE PAYLOAD DATA
Hypervisor-independent reference copies of virtual machine payload data based on block-level pseudo-mount infrastructure and techniques are generated and stored in an illustrative data storage management system. An illustrative hypervisor-independent reference copy includes one or more virtual-machine payload data files that originated from a first virtual machine. The hypervisor-independent virtual-machine-payload reference copy is governed by a distinct reference copy policy that controls retention, storage, tiering, scheduling, etc. for the reference copy, independently of how the illustrative system treats other virtual machine payload data files originating from the same virtual machine.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
Recovery points can be used for replicating a virtual machine and reverting the virtual machine to a different state. A filter driver can monitor and capture input/output commands between a virtual machine and a virtual machine disk. The captured input/output commands can be used to create a recovery point. The recovery point can be associated with a bitmap that may be used to identify data blocks that have been modified between two versions of the virtual machine. Using this bitmap, a virtual machine may be reverted or restored to a different state by replacing modified data blocks and without replacing the entire virtual machine disk.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
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.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
A system and method of deployment of malware detection traps by at least one processor may include performing a first interrogation of a first Network Asset (NA) of a specific NA family; determining, based on the interrogation, a value of one or more first NA property data elements of the first NA; obtaining one or more second NA property data elements corresponding to the specific NA family; integrating the one or more first NA property data elements and the one or more second NA property data elements to generate a template data element, corresponding to the specific NA family; producing, from the template data element, a malware detection trap module; and deploying, on one or more computing devices of a computer network, one or more instantiations of the malware detection trap module as decoys of the first NA.
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
G06F 21/51 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems at application loading time, e.g. accepting, rejecting, starting or inhibiting executable software based on integrity or source reliability
G06F 21/55 - Detecting local intrusion or implementing counter-measures
G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities
60.
DISTRIBUTED ARCHITECTURE FOR INFORMATION MANAGEMENT SERVICES IN CLOUD ENVIRONMENTS
Distributed architecture for executing information management services using shared platform microservices, containerization techniques, and regional core services. This architecture decentralizes the traditional model by segmenting the various functions of the centralized control and information manager into modular cloud microservices. This modularization not only enhances system flexibility but also allows for a more dynamic configuration, with certain elements being deployable as containers. The resilient architecture leverages the inherent scalability and adaptability of cloud technology.
A hosting service enables streamlined scaling of features that relate to data storage management. The scaling is powered by deployment of microservices, each one directed to a discrete feature of a data storage management system. In addition to scaling on demand, the disclosed hosting service provides additional value-added features, such as streamlining intra-system handling, auditing, and reporting of logs generated by microservices; standardizing exception handling; mediating port assignments for co-located microservices to avoid collisions; streamlining formats for inter-microservice communications; streamlining local database access; etc. Advantageously, the disclosed solution off-loads the storage manager, and additionally improves system performance by scaling various functions and by streamlining interoperability among components. Furthermore, the disclosed solution also enables the hosting service in general, and each discrete microservice in particular, to be enhanced, deployed, and scaled separately and asynchronously from each other and from the storage manager.
An improved system architecture for scaling deployments of data management-as-a-service (DMaaS) distributes “job manager” functionality so that a large-scale data storage management system may be deployed in a cloud computing environment as DMaaS without experiencing performance bottlenecks that slow down core data protection operations at scale. The disclosed solution creates an infrastructure where job manager features run on any number of distinct machines or compute resources that act as local job managers. In the illustrative DMaaS, any number of components that scale horizontally (“the distributed components”) carry job management responsibility for storage management operations such as backup jobs, auxiliary copy jobs, archive jobs, etc. These distributed components are configured to perform locally as job managers and to see each storage management job through from beginning to end without centralized control. These distributed components or local job managers also maintain, collect, and locally store job metadata.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
63.
SCALED DEPLOYMENT OF DATA PROTECTION RESOURCES FOR DATA ORIGINATING IN AN APPLICATION ORCHESTRATOR
Data protection resources are automatically scaled to the needs of data source(s) in an application orchestrator computing environment, such as a cluster in a Kubernetes deployment. The approach is adaptable to data sources in production clusters or application suites that are not application orchestrator deployments, such as a cloud-based database-as-a-service (DBaaS). A data storage management system protects cluster-based data with an elastic number of data protection resources (e.g., data agents, media agents), which are deployed on demand. The number of data protection resources deployed for a particular job are appropriate to the workload(s) at present and depend on a variety of scaling factors. In some embodiments, data protection resources are deployed within the same cluster as the data sources. In other embodiments, a separate infrastructure cluster provides the data protection resources on demand, and connects to any number and types of data sources, whether cloud-based or otherwise, without limitation.
A distributed data storage system comprises features for integration with application orchestrators such as Kubernetes, and includes a proprietary Container Storage Interface (CSI) driver. Features include setting snapshot scheduling and retention policies, and a “container data mover” that replicates data from a source to a distinct destination distributed data storage system. The migration may be configured one-to-one, one-to-many, unidirectional, and/or bi-directional. Metadata-based snapshots and metadata-based changed block tracking identify payload data to move from source to destination within application orchestrator frameworks at both ends. Payload data is migrated from source to destination using different techniques than those used for migrating metadata, e.g., kernel-to-kernel for copying payload data versus ordinary metadata writes. An illustrative barrier logic ensures that the migration follows a controlled progression of operations.
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.
G06F 15/173 - Interprocessor communication using an interconnection network, e.g. matrix, shuffle, pyramid, star or snowflake
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
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.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
A data storage management system is enhanced to accommodate, and moreover to optimize, the storing and retention of deduplicated secondary copies at write-once read-many (WORM) enabled storage platforms. Enhancements include without limitation: user interface (UI) options to enable WORM functionality for secondary storage, whether used for deduplicated or non-deduplicated secondary copies; enhancements to secondary copy (e.g., deduplication copy, backup) operations; and pruning changes. The storage manager is generally responsible for managing the creation, tracking, and deletion of secondary copies, with and without deduplication. Media agents that store secondary copies to and prune them from the WORM-enabled storage platforms also are enhanced for communicating and interoperating with both bucket-level and object-level WORM-enabled storage platforms to implement the features disclosed herein.
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.
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
G06F 3/06 - Digital input from, or digital output to, record carriers
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
A method for automatically encrypting files is disclosed. In some cases, the method may be performed by computer hardware comprising one or more processors. The method can include detecting access to a first file, which may be stored in a primary storage system. Further, the method can include determining whether the access comprises a write access. In response to determining that the access comprises a write access, the method can include accessing file metadata associated with the first file and accessing a set of encryption rules. In addition, the method can include determining whether the file metadata satisfies the set of encryption rules. In response to determining that the file metadata satisfies the set of encryption rules, the method can include encrypting the first file to obtain a first encrypted file and modifying an extension of the first encrypted file to include an encryption extension.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 21/70 - Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer
G06F 21/78 - Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer to assure secure storage of data
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. When the enhanced bare-metal restore process completes, each cloud-based recovery VM presents a user interface that, for the first time after the computing device has failed, asks for the individualized credentials of the failed machine.
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
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.
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
An information management system includes one or more client computing devices in communication with a storage manager and a secondary storage computing device. The storage manager manages the primary data of the one or more client computing devices and the secondary storage computing device manages secondary copies of the primary data of the one or more client computing devices. Each client computing device may be configured with a ransomware protection monitoring application that monitors for changes in their primary data. The ransomware protection monitoring application may input the changes detected in the primary data into a machine-learning classifier, where the classifier generates an output indicative of whether a client computing device has been affected by malware and/or ransomware. Using a virtual machine host, a virtual machine copy of an affected client computing device may be instantiated using a secondary copy of primary data of the affected client computing device.
G06F 21/55 - Detecting local intrusion or implementing counter-measures
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 21/54 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by adding security routines or objects to programs
G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G06F 21/78 - Protecting specific internal or peripheral components, in which the protection of a component leads to protection of the entire computer to assure secure storage of data
After completion of a backup job, the illustrative system performs a threat analysis of the freshly generated backup copies. Each copy is restored at a secure storage area. The system scans the restored data using, preferably, a signature-based malware scanning engine. If the scan finds malware infection or some other unsafe condition, a tracking index is updated to indicate that the copy is unsafe, and the secondary copy is quarantined. The quarantine prevents the copy from being restored to the production environment, and from acting as a source for other copies. The system iterates, scanning preceding versions of the copy, updating the index, and quarantining, until a clean or uninfected copy is found. The clean copy is so indexed. Responsive to a restore request, the illustrative system automatically restores the clean copy and skips over the infected copy/copies, preferably without asking the requesting user for input or approval.
The disclosed data storage management system enables data owners to model the costs and attributes of archiving their data and to readily capture and implement one or more resultant archiving plans. Modeling enables data owners to make informed choices about cost profiles before data is actually archived. Archiving plans devised according to these choices are intended to save on data storage costs and provide a compliance-ready data archive in cloud storage repository(ies). Armed with archiving simulations supplied by the illustrative data storage management system, a data owner may control data placement to predict costs, free up primary storage, and move inactive data to less expensive archive storage. Preferably, the disclosed system is implemented as a software-as-a-service (SaaS) solution, and the accompanying archive storage is implemented as a cloud storage service, but the invention is not limited to SaaS or to cloud-based data archives.
Certain embodiments described herein relate to an improved disk usage growth prediction system. In some embodiments, one or more components in an information management system can determine usage status data of a given storage device, perform a validation check on the usage status data using multiple prediction models, compare validation results of the multiple prediction models to identify the best performing prediction model, generate a disk usage growth prediction using the identified prediction model, and adjust the available space of the storage device according to the disk usage growth prediction.
The disclosed enhancements optimize the use of the live browse cache and pseudo-disk storage areas, improving metadata handling so that it can be used more effectively to speed up live browse and file indexing of backup copies in a data storage management system. The enhancements operate granularly to identify within each extent being backed up smaller sectors that comprise metadata. The disclosed approach pre-fetches the metadata of the backup copy before allowing the file scan of the file indexing and/or the live browse operation to proceed. The backup operation, the file indexing operation, and the live browse operation are enhanced to handle the more granular metadata sectors without changing the granularity of the full extents generated and stored in the backup.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 3/06 - Digital input from, or digital output to, record carriers
77.
MIGRATING ERASURE-CODED DATA FRAGMENTS WITHIN A GROWING DISTRIBUTED DATA STORAGE SYSTEM WITH AT LEAST DATA PLUS PARITY NODES
A distributed data storage system that employs erasure coding grows from fewer than data-plus-parity (D+P) storage service nodes to at least D+P nodes. The system detects an increase in the number of available storage service nodes, i.e., at least D+P; analyzes how storage for each virtual disk is distributed among storage containers in the existing (pre-growth) nodes; identifies containers that are co-hosted on the same node; and, on a node-by-node basis, migrates data fragments from a co-hosted storage container to a corresponding new container that is configured on another node. For each virtual disk in the illustrative system, the migration causes containers, including the erasure-coded data fragments they host, to be re-distributed so that the containers for a virtual disk are NOT doubled up or co-hosted on the same node. The disclosed computer-implemented process for re-distributing erasure-coded data fragments operates organically, without requiring the system to restart or reboot.
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.
This application describes a process where a system receives a cloning request to replicate the functionality of a primary computing device onto a virtual machine. Initially, the system generates or identifies a non-production, point-in-time copy of the primary device's data and metadata. Utilizing this copy, it assesses the primary device's current configuration and resource usage metrics. Subsequently, it identifies an appropriate hosting destination for the virtual machine, equipped with necessary hardware processors. The process further involves defining an optimal configuration for the virtual machine, which may be distinct from the original device, based on various parameters. The virtual machine is then provisioned at the chosen location according to this tailored configuration. The system ensures the virtual machine has access to the original device's data and metadata through specially provisioned virtual disks. Additionally, it implements specific information management policies on the virtual disks' data and metadata to maintain integrity and security.
H04L 41/0816 - Configuration setting characterised by the conditions triggering a change of settings the condition being an adaptation, e.g. in response to network events
G06F 9/48 - Program initiatingProgram switching, e.g. by interrupt
G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
G06F 15/177 - Initialisation or configuration control
H04L 67/00 - Network arrangements or protocols for supporting network services or applications
H04L 67/06 - Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
80.
Synthesizing a restore image from one or more secondary copies to facilitate data restore operations to a file server
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.
G06F 7/00 - Methods or arrangements for processing data by operating upon the order or content of the data handled
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
Virtual machine (VM) proliferation may be reduced through the use of Virtual Server Agents (VSAs) assigned to a group of VM hosts that may determine the availability of a VM to perform a task. Tasks may be assigned to existing VMs instead of creating a new VM to perform the task. Furthermore, a VSA coordinator may determine a grouping of VMs or VM hosts based on one or more factors associated with the VMs or the VM hosts, such as VM type or geographical location of the VM hosts. The VSA coordinator may also assign one or more VSAs to facilitate managing the group of VM hosts. In some embodiments, the VSA coordinators may facilitate load balancing of VSAs during operation, such as during a backup operation, a restore operation, or any other operation between a primary storage system and a secondary storage system.
A data storage environment can include one or more virtual machines instantiated on a host computing device. Based on physical location data of the one or more virtual machines received from the host computing device, a storage manager can control the performance of a secondary copy operation on one or more storage units that store virtual machine data associated with the one or more virtual machines and/or the performance of a secondary copy operation on the one or more virtual machines.
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 3/06 - Digital input from, or digital output to, record carriers
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/11 - File system administration, e.g. details of archiving or snapshots
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.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 3/06 - Digital input from, or digital output to, record carriers
84.
Cache management for faster live browsing and file indexing of backup copies, including block-level backup copies of virtual machines and/or file systems
An illustrative approach accelerates file indexing operations for block-level backup copies in a data storage management system. A cache storage area is maintained for locally storing and serving key data blocks, thus relying less on retrieving data on demand from the backup copy. File indexing operations are used for populating the cache storage area for speedier retrieval during subsequent live browsing of the same backup copy, and vice versa. The key data blocks cached while file indexing and/or live browsing an earlier backup copy help to pre-fetch corresponding data blocks of later backup copies, thus producing a beneficial learning cycle. The approach is especially beneficial for cloud and tape backup media, and is available for a variety of data sources and backup copies, including block-level backup copies of virtual machines (VMs) and block-level backup copies of file systems, including UNIX-based and Windows-based operating systems and corresponding file systems.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/13 - File access structures, e.g. distributed indices
G06F 16/172 - Caching, prefetching or hoarding of files
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
85.
GRAPHICAL REPRESENTATION OF AN INFORMATION MANAGEMENT SYSTEM
Systems and methods are described herein for graphically representing an information management system based on the characteristics of within the system. The systems and methods interface with various components of the system (e.g., administrative components, index components, and so on) to identify data having certain characteristics (e.g., personal data), and generate or render information (e.g., a heat map or other visual display) that represents areas or locations within the system storing the data. Thus, the systems and methods, in some embodiments, generate or create a data-specific view into the information management system.
A client machine writes to and reads from a virtual disk on a remote storage platform. Metadata is generated and stored in replicas on different metadata nodes of the storage platform. A modified log-structured merge tree is used to store and compact string-sorted tables of metadata. During file storage and compaction, a consistent file identification scheme is used across all metadata nodes. A fingerprint file is calculated for each SST (metadata) file on disk that includes hash values corresponding to regions of the SST file. To synchronize, the fingerprint files of two SST files are compared, and if any hash values are missing from a fingerprint file, then the key-value-timestamp triples corresponding to these missing hash values are sent to the SST file that is missing them. The SST file is compacted with the missing triples to create a new version of the SST file. The synchronization is bi-directional.
G06F 7/00 - Methods or arrangements for processing data by operating upon the order or content of the data handled
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/13 - File access structures, e.g. distributed indices
G06F 16/178 - Techniques for file synchronisation in file systems
G06F 16/2457 - Query processing with adaptation to user needs
G06F 16/2458 - Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
G06F 17/00 - Digital computing or data processing equipment or methods, specially adapted for specific functions
G06F 16/27 - Replication, distribution or synchronisation of data between databases or within a distributed database systemDistributed database system architectures therefor
87.
Analysis of backup copies to identify malware-encrypted primary data
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.
A streamlined approach enables customers to retain management control over their data in a database-as-a-service (“DBaaS”) setting, by providing managed backup copies outside cloud service providers' sphere of control. An illustrative data storage management system provides control over performing backup operations to generate managed backup copies, storing managed backup copies, recovering managed backup copies in whole or in part, migrating managed backup copies, and migrating DBaaS instances. Management control also extends to choices of where to store the managed backup copies, whether on the same cloud computing platform as the source DBaaS, on a different cloud computing platform, and/or in a non-cloud data center.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
G06F 16/21 - Design, administration or maintenance of databases
G06F 16/28 - Databases characterised by their database models, e.g. relational or object models
H04L 67/10 - Protocols in which an application is distributed across nodes in the network
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.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/176 - Support for shared access to filesFile sharing support
A data storage management system comprises features for initiating failover orchestration jobs that invoke recovery resources on demand in a cloud computing environment. Backed up data that is stored persistently in the cloud computing environment may be rapidly restored within the cloud computing environment for use in disaster recovery and/or in test and verification scenarios. This approach may be contrasted to systems where a failover system is “always on” at the failover destination, such as having failover resources always up and running in the cloud computing environment. Such resources typically include a failover virtual machine (VM), a virtual machine datastore for the restored data, and one or more computing resources for restoring an auxiliary copy to the VM's datastore. The cloud-based failover resources are deactivated or taken down once the failover event ends.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
91.
Incrementally accumulating in-process performance data into a data stream in a secondary copy operation
Each data stream in a backup job is individually tracked by data agent(s) and media agent(s) in its path, generating performance data packets in-process and merging them into the processed data stream. The data stream thus incrementally accumulates performance data packets from any number of successive backup processes. The in-process tracking also captures hierarchical relationships among backup processes and in-process subtending tasks, so that the resulting performance report can depict parent and child operations. The hierarchical relationships are embedded into the performance data packets and may be analyzed by parsing the data stream. The media agent transfers the data packets belonging to the secondary copy to secondary storage. The media agent analyzes the performance data packets in the data stream and generates a performance report, which covers the data stream from source to destination, based on the accumulated information carried by the performance data packets. The media agent illustratively stores the performance report locally as a flat file.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
H04L 43/08 - Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
G06F 11/20 - Error detection or correction of the data by redundancy in hardware using active fault-masking, e.g. by switching out faulty elements or by switching in spare elements
A method and system for communicating with IoT devices to gather information related to device failure or error(s) is disclosed. The system makes a copy of at least a portion of the device's non-volatile memory and/or receives IoT device data (e.g., sensor data and/or log files etc.) from an IoT device that recently failed. The system determines which log files and/or sensor data, for example, the IoT device created before and/or after a failure. After gathering this information, the system stores the information in a database, sends it to the IoT device manufacturer, for further analysis and diagnostics to troubleshoot the failure and send a fix or software update to the IoT device.
G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
93.
Continuously run log backup with minimal configuration and resource usage from the source machine
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.
An information management security health monitoring system is provided herein that can monitor the security health of one or more information management systems, identify any security 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 security issue(s). For example, the information management cell health monitoring system receives security data and security policies, and/or similar data from an information management cell(s) via a network. The system analyzes the received information to identify any issues. If an issue is detected, the information management security health monitoring system retrieves workflows and determines whether any of the workflows can be used to resolve the detected issue. The information management security health monitoring system transmits a workflow that resolves the detected issue to the information management system for execution.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
Data recovery from a cyber-attack is expedited based on data storage management integration with cyber threat deception. A cyber threat detection and deception system analyzes a “deposit” placed by an attacker at a deception trap, identifies distinguishing attributes of the deposit, and determines which subset of real data assets may be at risk, preferably based on subnet/VLAN proximity to the attacker's deposit. By focusing immediate attention on the subset of at-risk assets, a data storage management system shortens the amount of time needed to identify safe copies and components and to prepare them for recovery. Storage operations involving the at-risk assets are suspended and users are not shown at-risk assets and cannot invoke recovery or copy operations for them. Without the focus on at-risk assets provided by the cyber threat detection and deception system, the data storage management system would take much longer to navigate its backup data stores.
09 - Scientific and electric apparatus and instruments
42 - Scientific, technological and industrial services, research and design
Goods & Services
Electronic data transmission; Electronic transmission of messages and data; Encrypted electronic transmission and delivery of recovered data Computer storage devices, namely, high-speed storage subsystems for storage and backup of electronic data either locally or via a telecommunications network; Downloadable computer application software for creating data files for use in virtual environments; Downloadable computer software for creating searchable databases of information and data; Downloadable data compression software; Downloadable file sharing software; Downloadable software for data being electronic storage of data, and data storage, back-up, resilience, retrieval, and recovery; Downloadable software for cyber recovery and disaster recovery of data Computer disaster recovery planning; Computer monitoring service which tracks application software performance, performs periodic maintenance and provides reports and alerts concerning such performance; Computer security threat analysis for protecting data; Computer services, namely, data recovery services; Data migration services; Data security consultancy; Electronic data back-up services; Temporary electronic storage of data; Off-site data backup; Providing temporary use of on-line non-downloadable software for data in the nature of temporary electronic storage of data, and data storage, back-up, resilience, retrieval, and recovery; Providing temporary use of on-line non-downloadable software for cyber recovery and disaster recovery of data; Recovery of computer data; Remote online backup of computer data; Technical support services, namely, installation, administration, and troubleshooting of web and database applications; Technical support, namely, providing computer facilities for the electronic storage of digital data; Providing temporary use of online non-downloadable file sharing software; Temporary electronic storage of information and data
97.
DATA STORAGE MANAGEMENT SYSTEM INTEGRATING CYBER THREAT DECEPTION
A cyber threat detection and deception system interoperates synergistically with a data storage management system. As a proxy for identifying crown jewels among many and diverse data assets in a network, the illustrative cyber threat detection and deception system uses service level information obtained from the data storage management system, e.g., RPO, RTO, append-only secondary storage, synthetic-full frequency, etc. The cyber threat detection and deception system emulates proprietary protocols used by storage management technologies such as the data storage management system, etc. By creating emulation traps and an emulation lexicon of these storage-related protocols, the illustrative cyber threat detection and deception system can create and execute cyber deception plans for the proprietary storage management assets. Synergistically, the illustrative data storage management system is configured to respond to alerts and react to other information received from the cyber threat detection and deception system by taking certain corrective and/or protective actions.
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.
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.
H04L 67/1095 - Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
H04L 41/046 - Network management architectures or arrangements comprising network management agents or mobile agents therefor
H04L 67/1097 - Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
H04L 67/568 - Storing data temporarily at an intermediate stage, e.g. caching
100.
Management database long-term archiving to a recovery manager
A storage manager for an information management system determines whether one or more predetermined conditions have been met for transferring metadata of previously performed backup jobs stored in a first management database. A backup job may correspond to a backup operation of a primary storage device of a first client computing device. In response to a determination that one or more of the predetermined conditions have been met, the storage manager may transfer metadata for a second plurality of backup jobs to a second management database of a recovery manager. The recovery manager may receive a request to restore data to the primary storage device of the first client computing device based on the metadata of the second plurality of backup jobs. A media agent managed by the recovery manager may then restore the requested data to the primary storage device of the first client computing device.
G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result
G06F 16/21 - Design, administration or maintenance of databases
