In an example, a method comprises generating, with a computing system-executed AI agent applying a machine learning model, based on a query associated with a user, an execution plan for a task to satisfy the query, wherein the execution plan includes actions to be performed with respect to a first data source system and a second data source system, and wherein the user has permission for each of the actions; invoking, by the AI agent, a first tool to perform a first action of the actions with respect to the first data source system, wherein the AI agent is trained to use the first tool; and invoking, by the AI agent, a second tool to perform a second action of the actions with respect to the second data source system, wherein the AI agent is trained to use the second tool.
Techniques are described for techniques for an actionable artificial intelligence bot based on data security correlations. An example method comprises determining, by a data platform implemented by a computing system, a plurality of tags for a snapshot executed by the data platform, detecting, by the data platform, an indication of a security breach relating to the snapshot, processing, by the data platform and using a machine learning model, a plurality of attributes of the security breach and the plurality of tags to identify a potential compromise of the snapshot, processing, by the data platform and using a large language model, at least the plurality of attributes to generate an actionable prompt including a natural language description of at least one security response, and outputting, by the data platform, the actionable prompt.
Techniques are disclosed for prefetching data using predictive analysis. An example method comprises storing, by a data platform implemented by a computing system, objects of a file system, wherein a first subset of the objects is stored to a first storage tier and a second subset of the objects is stored to a second storage tier, classifying objects into one or more classifications, storing a data access record for the objects, applying a machine learning model to generate a prediction of future data access to one or more objects of the second subset based on the one or more classifications and the data access record, wherein the prediction includes a predicted time for the future data access, and retrieving, based on the prediction, the one or more objects of the second subset from the second storage tier prior to the predicted time.
Techniques are described for protected data restoration using confidential computing. An example method comprises receiving, by a data platform implemented by a computing system, a request to restore an encrypted chunk of data, the encrypted chunk stored with first encrypted key data and second encrypted key data, receiving, by an enclave implemented in a trusted execution environment, first encrypted key data and second encrypted key data from the storage cluster, decrypting, by the enclave, the first encrypted key data to obtain the first key data and the second encrypted key data to obtain the second key data, generating, by the storage cluster, a derived data encryption key corresponding to the data encryption key based on the first key data and the second key data, and decrypting, by the storage cluster, the encrypted chunk with the derived data encryption key to generate a decrypted chunk.
Embodiments are disclosed that provide space reclamation in immutable deduplication systems, and can include selecting a unit of data of a backup image, determining whether a duplicate unit of data is stored in an existing data storage construct (the duplicate unit of data is a duplicate of the unit of data and the existing data storage construct is stored in immutable storage), and in response to a determination that the duplicate unit of data exists in the existing data storage construct, determining whether the existing data storage construct is designated as being available to be referenced, in response to the existing data storage construct being designated as being available to be referenced, updating a reference to the duplicate unit of data, and in response to the existing data storage construct being designated as being unavailable to be referenced, storing the unit of data in a new data storage construct.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
6.
ARTIFICIAL INTELLIGENCE CHATBOT FOR DATA PLATFORM SECURITY ANALYSIS
In general, techniques are described that enable a computing system to execute an artificial intelligence model for data security analysis. A computing system that includes a memory and processing circuitry may be configured to implement the techniques. The memory may store a query from an end user regarding security services provided by the data platform. The processing circuitry may parse the query to identify one or more intents, and process the one or more intents to retrieve data for formulating a natural language response to the query. The processing circuitry may also process, using a large language model, the intents and the data to generate the natural language response, and output the natural language response to a user interface for display to the end user.
Techniques are described for incrementally determining checksums for a snapshot. An example method comprises identifying, by a data platform implemented by a computing system, a plurality of leaf nodes and a plurality of intermediate nodes in tree data corresponding to a snapshot of a storage system at a particular time, wherein the intermediate nodes each comprise one or more pointers identifying one or more of the leaf nodes, and the leaf nodes each include an indication of file system data of the storage system. The method includes determining, by the data platform, a checksum for each of the leaf nodes, determining, by the data platform, a checksum for each intermediate node based on the checksum of the one or more leaf nodes identified by the pointers of the intermediate node; and storing, by the data platform, the checksum for each of the leaf nodes and each of the intermediate nodes.
Metadata associated with content stored in a corresponding primary storage system is received receiving from each secondary storage cluster of a plurality of different secondary storage clusters included in different storage domains. The metadata received from the plurality of different secondary storage clusters is stored and indexed together. A unified metadata search interface is provided for stored data of the corresponding primary storage systems and the plurality of different secondary storage clusters of the different storage domains.
G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
Embodiments are disclosed that provide space reclamation in immutable deduplication systems, and can include selecting a unit of data of a backup image, determining whether a duplicate unit of data is stored in an existing data storage construct (the duplicate unit of data is a duplicate of the unit of data and the existing data storage construct is stored in immutable storage), and in response to a determination that the duplicate unit of data exists in the existing data storage construct, determining whether the existing data storage construct is designated as being available to be referenced, in response to the existing data storage construct being designated as being available to be referenced, updating a reference to the duplicate unit of data, and in response to the existing data storage construct being designated as being unavailable to be referenced, storing the unit of data in a new data storage construct.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
The disclosed computer-implemented method for protecting data may include (i) detecting that a data storage protection protocol for backing up a virtual machine is switching from a hypervisor native snapshot solution to a continuous data protection solution, (ii) toggling, at a specific toggling time, an input/output tap to switch to the continuous data protection solution, (iii) capturing, at a specific snapshot time and in response to switching to the continuous data protection solution, an incremental snapshot that includes differences in the virtual machine between a last snapshot captured prior to the specific toggling time and the specific snapshot time, and (iv) generating a synthetic snapshot based on a combination of the incremental snapshot captured at the specific snapshot time and a set of at least one snapshot taken prior to the specific toggling time. Various other methods, systems, and computer-readable media are also disclosed.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
One or more objects associated with a source storage is determined to be archived to a remote storage. A corresponding minimum expiration time is stored in nodes of a tree data structure associated with an archive that represents the archived data associated with the source storage. At least a portion of the tree data structure associated with the archive is traversed to identify one or more nodes associated with one or more archived objects having a corresponding expiration time expiring before an expiration time associated with the archive.
Techniques are described for selectively extending a WORM lock expiration time for a chunkfile. An example method comprises identifying, by a data platform implemented by a computing system, a chunkfile that includes a chunk that matches data for an object of a file system; determining, by the data platform after identifying the chunkfile, whether to deduplicate the data for the object of the file system by adding a reference to the matching chunk, wherein determining whether to deduplicate the data comprises applying a policy to at least one of a property of the chunkfile or properties of one or more of a plurality of chunks included in the chunkfile; and in response to determining to not deduplicate the data for the object of the file system, causing a new chunk for the data for the object of the file system to be stored in a different, second chunkfile.
G06F 16/174 - Élimination de redondances par le système de fichiers
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
13.
Incrementally determining checksums for a snapshot
Techniques are described for incrementally determining checksums for a snapshot. An example method comprises identifying, by a data platform implemented by a computing system, a plurality of leaf nodes and a plurality of intermediate nodes in tree data corresponding to a snapshot of a storage system at a particular time, wherein the intermediate nodes each comprise one or more pointers identifying one or more of the leaf nodes, and the leaf nodes each include an indication of file system data of the storage system. The method includes determining, by the data platform, a checksum for each of the leaf nodes, determining, by the data platform, a checksum for each intermediate node based on the checksum of the one or more leaf nodes identified by the pointers of the intermediate node; and storing, by the data platform, the checksum for each of the leaf nodes and each of the intermediate nodes.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Computer hardware; computer servers; network servers; digital media servers; computer software for duplicating and storing data and for data recovery; computer software for use in data storage management; computer utility software; computer software for use in file, disk, data storage, and storage area network management; computer software for duplicating computer data, including files, databases, groupware and electronic mail systems, from one storage medium to another; computer software for use in disaster recovery; computer software for scheduling automated processes; computer software for replicating and archiving files from one data store to another; computer software for information management, identification, collection, preservation, processing, analysis, review, production and presentation of all electronically stored documents and data; computer software for document and electronic mail archiving, retention and retrieval; instruction manuals supplied as a unit with the foregoing; publications in electronic form, namely books, magazines, newsletters, workbooks, quick reference guides, technical reference materials, and conference materials downloadable from global computer networks, in the field of computers, computer software, computer peripherals, computer networks and data storage management Providing temporary use of non-downloadable software for data recovery, data storage management, disaster recovery, duplicating and storing data, file, disk, data storage, and storage area network management, scheduling automated processes, replicating and archiving files from one data store to another, information management, identification, collection, preservation, processing, analysis, review, production and presentation of electronically stored documents and data, and for email archiving, retention and retrieval; Software as a service (SaaS) featuring software for duplicating and storing data, for data recovery, and for data storage management; electronic data storage; electronic storage services for archiving electronic data; professional computer services, namely, analysis, design, management and monitoring of computer networks; technical support services, namely, troubleshooting of computer software problems; computer consulting services in the field of data storage, information management, computer networks, and data security; providing information in the field of information technology relating to communications devices, computers, computer hardware, computer software, computer peripherals, and computer networks; computer software installation services; computer software design for others; computer programming; notification and delivery of software updates
15.
FILE SYSTEM CHANGED BLOCK TRACKING FOR DATA PLATFORMS
A computing device comprising a storage device and processing circuitry may perform the techniques of this disclosure. The storage device may have a plurality of blocks forming a volume. The processing circuitry may obtain volume changed block tracking (CBT) information identifying one or more of the blocks storing updated data that has changed relative to a previous backup of the one or more blocks, and determine file mapping information identifying one or more blocks of the plurality of blocks that store file data associated with a file. The processing circuitry may also determine, based on the volume CBT information and the file mapping information, file system CBT information identifying whether at least one of the one or more blocks store file data associated with the file have changed, and initiate, based on the file system CBT information, a subsequent backup of at least a portion of the file data.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
Techniques are described for creating more efficient chunkfiles through the use of entropy metrics. In some examples, processing circuitry may determine an entropy value for each of a plurality of data chunks to obtain a corresponding plurality of entropy values. In some examples, processing circuitry may reorganize, based on the corresponding plurality of entropy values, the plurality of data chunks to obtain a reorganized plurality of data chunks. In some examples, processing circuitry may compress the reorganized plurality of data chunks to obtain a compressed chunkfile. In some examples, processing circuitry may store the compressed chunkfile superseding the plurality of data chunks.
A repository of replicated chunk files is analyzed to identify chunk files that meet at least a portion of combination criteria. Selected chunk files are associated together under a data protection grouping container. Erasure coding is applied to the data protection grouping container including by utilizing the selected chunk files as different data stripes of the erasure coding and generating one or more parity stripes based on the different data stripes.
Techniques are described for configuring a data platform to schedule workloads using backlog indicators. For instance, processing circuitry of a data platform may obtain a generic backlog indicator for workloads to execute via the data platform. Each of the workloads may specify one or more storage system maintenance operations. Processing circuitry may obtain a custom backlog indicator for at least a subset of the workloads. A priority manager may calculate a single weighted backlog indicator value for each of the workloads by applying configurable weights to the generic backlog indicators and the custom backlog indicators. The data platform may schedule the workloads for execution on the data platform based on the single weighted backlog indicator value calculated for each workload. In some examples, the data platform processes the workloads according to the scheduling.
An assigned subgroup that includes a plurality of entries is traversed by a prefetcher. It is determined that an expected number of entries associated with the assigned subgroup have been traversed. In response to determining that expected number of entries associated with the assigned subgroup have been traversed, it is determined that a last read entry associated with the assigned subgroup does not correspond to a last entry associated with the assigned subgroup. The prefetcher is preempted by stopping the prefetcher from obtaining a list of entries associated with a remaining portion of the assigned subgroup.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
20.
EXTENDING AN EXPIRATION TIME OF AN OBJECT ASSOCIATED WITH AN ARCHIVE
An amount of expiration time extension for one or more objects associated with a first archive of a first snapshot of a source storage is determined based at least in part on a second data management policy associated with a second archive and one or more dynamically determined metrics. The first archive that includes the one or more objects is caused to be stored to a remote storage. At least a portion of content of the first archive is referenced by data chunks stored in a first chunk object of the remote storage and the first archive is associated with a first data management policy. Based on the determined amount of expiration time extension, an expiration time for the one or more objects associated with the first archive is stored in an archive metadata of the one or more objects associated with the first archive.
Events from one or more primary systems associated with one or more tenants are received. The received events are stored in a message queue. At least a portion of the events in the message queue are ingested for organization and storage in a data store. One or more progress identifiers associated with ingesting of the events in the message queue are tracked. An event query is received from an external system. The event query is rewritten into a first component query for the data store and a second component query for the message queue based at least in part on a progress identifier. A result of the first component query and a result of the second component query are combined to determine a result of the event query.
Techniques are described for performing direct archive of data chunkfiles. A computing system comprising a storage device and processing circuitry having access to the storage device may be configured to perform various aspects of the techniques. The processing circuitry may be configured to predict an incoming data rate of native format to be archived to obtain a predicted incoming data rate for the native format data to be archived, and compare the predicted incoming data rate to a first threshold data rate. The processing circuitry may also be configured to, responsive to determining that the predicted incoming data rate exceeds a first threshold data rate, segment the native format data into chunks, and directly write the chunks to an archive storage system as a chunkfile.
Disclosed herein are methods, systems, and processes to perform cloud replication based on adaptive Quality of Service. A replication stream is monitored over a period of time. The replication stream includes write operations issued by an application, and is associated with preset parameters. Replication parameters applicable to the replication stream are determined. The replication parameters are configured to be used in a replication operation. The preset parameters and the replication parameters are stored.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
H04L 67/1095 - Réplication ou mise en miroir des données, p. ex. l’ordonnancement ou le transport pour la synchronisation des données entre les nœuds du réseau
Techniques are described for creating more efficient chunkfiles through the use of entropy metrics. In some examples, processing circuitry may determine an entropy value for each of a plurality of data chunks to obtain a corresponding plurality of entropy values. In some examples, processing circuitry may reorganize, based on the corresponding plurality of entropy values, the plurality of data chunks to obtain a reorganized plurality of data chunks. In some examples, processing circuitry may compress the reorganized plurality of data chunks to obtain a compressed chunkfile. In some examples, processing circuitry may store the compressed chunkfile superseding the plurality of data chunks.
Methods, computer program products, computer systems, and the like are disclosed that provide for improved deduplication performance using prefetched backup information. For example, such methods, computer program products, and computer systems can include generating new feature information for a new backup image, (for each existing backup image in a plurality of existing backup images) comparing the new feature information with existing feature information for the each existing backup image, identifying one or more existing backup images of the plurality of existing backup images, and prefetching the one or more existing backup images. The feature information is generated as an output of a machine learning process. The machine learning process receives at least a portion of data of the new backup image as an input. The one or more existing backup images are identified based, at least in part, on a result of the comparing.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 9/30 - Dispositions pour exécuter des instructions machines, p. ex. décodage d'instructions
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
A set of data changes to a storage associated with a source system is received. One or more data logs among a plurality of data logs stored in different nodes of a storage system is dynamically selected based at least in part on a dynamic analysis of metrics of the different nodes of the storage system. The at least one data change of the set of data changes are logged in the one or more selected data logs.
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
27.
PERFORMING A DATABASE BACKUP BASED ON AUTOMATICALLY DISCOVERED PROPERTIES
Properties of one or more databases of nodes of a database system are automatically discovered. The automatically discovered properties for at least one of the databases include a database architecture and a corresponding failover role for each of at least some of the nodes. Based at least in part on the discovered properties, a corresponding one of the nodes as a corresponding backup source node is selected for each of the one or more databases. One or more database backups are allowed to be performed via the one or more selected backup source nodes.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
28.
DATA RETRIEVAL USING EMBEDDINGS FOR DATA IN BACKUP SYSTEMS
In general, techniques for efficient data retrieval from a backup system are described. An example computing system includes one or more storage devices and processing circuitry having access to the one or more storage devices and configured to: process an input to generate a filter, wherein the input indicates a context for one or more queries; apply the filter to backup data to obtain filtered data from the backup data; generate an index of embeddings from the filtered data; process, based on the index of embeddings, a query to generate a response for the query; and output the response.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
A request to restore a specific backup instance is received. In response to the received request to restore the specific backup instance, a new reference backup instance based on the specific backup instance stored at the storage controlled by the backup system is created at a storage controlled by a backup system. Data associated with the specific backup instance is provided to a recipient system from the storage associated with a backup system. A constructive incremental backup snapshot of the recipient system is performed based on the new reference backup instance.
In general, techniques for efficient data retrieval from a backup system are described. An example computing system includes one or more storage devices and processing means having access to the one or more storage devices and configured to: process an input to generate a filter, wherein the input indicates a context for one or more queries: apply the filter to backup data to obtain filtered data from the backup data; generate an index of embeddings from the filtered data; process, based on the index of embeddings, a query; to generate a response for the query; and output the response.
Techniques are described for selectively extending a WORM lock expiration time for a chunkfile. An example method comprises identifying, by a data platform implemented by a computing system, a chunkfile that includes a chunk that matches data for an object of a file system; determining, by the data platform after identifying the chunkfile, whether to deduplicate the data for the object of the file system by adding a reference to the matching chunk, wherein determining whether to deduplicate the data comprises applying a policy to at least one of a property of the chunkfile or properties of one or more of a plurality of chunks included in the chunkfile; and in response to determining to not deduplicate the data for the object of the file system, causing a new chunk for the data for the object of the file system to be stored in a different, second chunkfile.
G06F 16/17 - Détails d’autres fonctions de systèmes de fichiers
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/174 - Élimination de redondances par le système de fichiers
32.
Performing a backup of an object based on an identifier associated with the object
Data associated with an object to be stored is received from a source system for a destination logical storage container selected among a plurality of destination logical storage containers. A total number of the destination logical storage containers allowed to be concurrently supported by the source system is limited. The selected destination logical storage container is shared by a plurality of objects of the source system. Based at least in part on an identifier associated with the object, a child logical storage container corresponding to the object is identified. The child logical storage container is different from the selected destination logical storage container. The data associated with the object received for the selected destination logical storage container is automatically stored in the identified child logical storage container.
G06F 11/00 - Détection d'erreursCorrection d'erreursContrôle de fonctionnement
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Hyperconverged infrastructure (HCI) data management platform comprising downloadable software for integrating computer servers, computer networks, and data storage into a single solution for purposes of data management and managing information technology infrastructure and applications; downloadable computer software, namely, a single data management computer software platform for managing data distributed across multiple locations, data centers, public clouds, private clouds and hybrid clouds; downloadable computer software analytics platform in the nature of downloadable cloud computing software for analyzing, visualizing, and manipulating large quantities of unstructured, structured, and semi-structured data distributed across multiple locations, data centers, public clouds, private clouds and hybrid clouds; downloadable computer software that enables management of distributed data sources in a single user interface; downloadable computer software for data management; downloadable computer software for data storage, data backup, data protection, data migration, data archival, data analytics, data searching, data indexing, data retrieval, data reporting, data deduplication, data redundancy and data recovery and replication; downloadable database management computer software for use in the field of enterprise data and information management; downloadable computer software for data disaster recovery and replication; downloadable computer software development tools; downloadable cloud-based software for data management; downloadable mobile application for data management in the nature of data storage, data backup, data protection, data migration, data archival, data analytics, data searching, data indexing, data retrieval, data notifications, data monitoring, data reporting, data deduplication, data redundancy and data recovery and replication; downloadable mobile application for data disaster recovery and replication; downloadable mobile application for managing and operating software in the fields of data security, compliance assessment, and cyber security. (1) Computer disaster recovery planning
(2) Software-as-a-service (SaaS) services featuring software for use in data management, data storage, data backup, data protection, data migration, data archival, data analytics, data searching, data indexing, data retrieval, data reporting, data deduplication, data redundancy and data recovery and replication; software-as-a-service (SaaS) services featuring software for use in data protection analysis for cybersecurity and computer security purposes; platform-as-a-service (PaaS) featuring a single computer software platform for managing data distributed across multiple locations, data centers, public clouds, private clouds and hybrid clouds; platform-as-a-service (PaaS) featuring computer software analytics platforms for analyzing, visualizing, and manipulating large quantities of data in a single user interface; providing temporary use of on-line non-downloadable software for use in data management, data storage, data backup, data protection, data migration, data archival, data analytics, data searching, data indexing, data retrieval, data reporting, data deduplication, data redundancy and data recovery and replication; electronic data storage for archiving electronic data; computer services, namely, computer security threat evaluation and analysis for protecting data to assure compliance with industry standards; platform-as-a-service (PaaS) featuring computer software platforms for use in data management and data protection; platform-as-a-service (PaaS) featuring computer software platforms for enabling data processing and data management; providing virtual computer systems and virtual computer environments through cloud computing on a subscription or pay-per-use basis; cloud computing featuring software for electronic data back-up, disaster data recovery, electronic storage for archiving electronic data, and computer security threat analysis for protecting data; cloud computing featuring software for use in computer software development.
34.
DISTRIBUTING OBJECTS ACROSS DEDUPLICATION DOMAINS BASED ON A STORAGE DISTRIBUTION MODE
A plurality of objects sharing one or more common attributes are identified. A storage distribution mode for the identified objects sharing the one or more common attributes is determined based at least in part on one or more optimization criteria. The storage distribution mode is caused to be implemented by one or more of a plurality of storage clusters.
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
35.
ADAPTIVELY PROVIDING UNCOMPRESSED AND COMPRESSED DATA CHUNKS
A selected data chunk associated with an object is determined to be sent to a destination. A chunk compression grouping storing the selected data chunk associated with the object is identified. The identified chunk compression grouping includes a plurality of data chunks compressed together. A data content version that includes the selected data chunk associated with the object to be provided to the destination is determined from a plurality of data content versions based at least in part a metric associated with the identified chunk compression grouping.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software for computer security, data
protection and data security; downloadable computer software
for detecting, preventing and managing malware, ransomware,
and other cyberattacks, data breaches, data exfiltration,
unauthorized access, unauthorized data movement and other
indicators of compromise; downloadable computer software for
recovery of lost, deleted or compromised data; downloadable
computer software for computer disaster recovery;
downloadable computer software for computer security threat
detection, analysis, prevention, integration of threat data,
and investigation and management of malware, ransomware, and
other cyberattacks, data breaches, data exfiltration,
unauthorized access, unauthorized data movement and other
indicators of compromise; downloadable computer software
featuring customizable computer security software for others
in the field of cybersecurity; downloadable computer
software for backup and recovery of digital and electronic
data; downloadable computer software featuring AI/ML-based
software for data classification and data forensics in the
field of cybersecurity; none of the aforementioned goods
used in relation to advertising, marketing, promotion or
ecommerce for others or for searchable computer database
software or data centers. Software as a service (SaaS) services featuring computer
security, data protection and data security software;
providing online non-downloadable software for computer
security, data protection and data security; software as a
service (SaaS) services featuring software for detecting,
preventing and managing malware, ransomware, and other
cyberattacks, data breaches, data exfiltration, unauthorized
access, unauthorized data movement and other indicators of
compromise; providing online non-downloadable software for
detecting, preventing and managing malware, ransomware, and
other cyberattacks, data breaches, data exfiltration,
unauthorized access, unauthorized data movement and other
indicators of compromise; software as a service (SaaS)
services featuring software for recovery of lost, deleted or
compromised data; providing online non-downloadable software
for recovery of lost, deleted or compromised data; software
as a service (SaaS) services featuring software for computer
disaster recovery; providing online non-downloadable
software for computer disaster recovery; software as a
service (SaaS) services featuring software for computer
security threat detection, analysis, prevention, integration
of threat data, and investigation and management of malware,
ransomware, and other cyberattacks, data breaches, data
exfiltration, unauthorized access, unauthorized data
movement and other indicators of compromise; providing
online non-downloadable software for computer security
threat detection, analysis, prevention, integration of
threat data, and investigation and management of malware,
ransomware, and other cyberattacks, data breaches, data
exfiltration, unauthorized access, unauthorized data
movement and other indicators of compromise; computer
security services, namely, identification of cyber threats
through multi-source threat intelligence and analysis,
development of Internet security programs for minimizing
risk of malware, ransomware, and other cyberattacks, data
breaches, data exfiltration, unauthorized access,
unauthorized data movement and other indicators of
compromise; software as a service (SaaS) services featuring
customizable computer security software for others in the
field of cybersecurity; providing online non-downloadable
software featuring customizable computer security software
for others in the field of cybersecurity; backup services
for computer hard drives, flash drives, and cloud-based
storage for recovering and restoring computer data; software
as a service (SaaS) services featuring software for backup
and recovery of digital and electronic data; providing
online non-downloadable software for backup and recovery of
digital and electronic data; computer security analysis
services, namely, analysis of secondary copies of data for
detecting malware, ransomware, and other cyberattacks, data
breaches, data exfiltration, unauthorized access,
unauthorized data movement and other indicators of
compromise; storage services, namely, cloud-based electronic
data storage; computer security monitoring services, namely,
monitoring of computer systems for detecting malware,
ransomware, and other cyberattacks, data breaches, data
exfiltration, unauthorized access, unauthorized data
movement and other indicators of compromise; computer
forensic services; providing online non-downloadable
cloud-based software for data classification and data
forensics in the field of cybersecurity; computer services,
namely, implementation of on-premise AI/ML-based software
for data classification and data forensics in the field of
cybersecurity; managed cybersecurity services, namely,
intrusion detection, intrusion prevention, cybersecurity
threat detection and prevention, namely, online scanning,
detecting, and management of malware, ransomware, and other
cyberattacks, data breaches, data exfiltration, unauthorized
access, unauthorized data movement and other indicators of
compromise for cybersecurity purposes; none of the
aforementioned services used in relation to advertising,
marketing, promotion or e-commerce services for others or
for searchable computer database software or data center
services.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Hyperconverged infrastructure (HCI) data management platform
comprising downloadable software for integrating computer
servers, computer networks, and data storage into a single
solution for purposes of data management and managing
information technology infrastructure and applications;
downloadable computer software, namely, a single data
management computer software platform for managing data
distributed across multiple locations, data centers, public
clouds, private clouds and hybrid clouds; downloadable
computer software analytics platform in the nature of
downloadable cloud computing software for analyzing,
visualizing, and manipulating large quantities of
unstructured, structured, and semi-structured data
distributed across multiple locations, data centers, public
clouds, private clouds and hybrid clouds; downloadable
computer software that enables management of distributed
data sources in a single user interface; downloadable
computer software for data management; downloadable computer
software for data storage, data backup, data protection,
data migration, data archival, data analytics, data
searching, data indexing, data retrieval, data reporting,
data deduplication, data redundancy and data recovery and
replication; downloadable database management computer
software for use in the field of enterprise data and
information management; downloadable computer software for
data disaster recovery and replication; downloadable
computer software development tools; downloadable
cloud-based software for data management; downloadable
mobile application for data management in the nature of data
storage, data backup, data protection, data migration, data
archival, data analytics, data searching, data indexing,
data retrieval, data notifications, data monitoring, data
reporting, data deduplication, data redundancy and data
recovery and replication; downloadable mobile application
for data disaster recovery and replication; downloadable
mobile application for managing and operating software in
the fields of data security, compliance assessment, and
cyber security. Software-as-a-service (saas) services featuring software for
use in data management, data storage, data backup, data
protection, data migration, data archival, data analytics,
data searching, data indexing, data retrieval, data
reporting, data deduplication, data redundancy and data
recovery and replication; software-as-a-service (saas)
services featuring software for use in data protection
analysis for cybersecurity and computer security purposes;
platform-as-a-service (paas) featuring a single computer
software platform for managing data distributed across
multiple locations, data centers, public clouds, private
clouds and hybrid clouds; platform-as-a-service (paas)
featuring computer software analytics platforms for
analyzing, visualizing, and manipulating large quantities of
data in a single user interface; providing temporary use of
on-line non-downloadable software for use in data
management, data storage, data backup, data protection, data
migration, data archival, data analytics, data searching,
data indexing, data retrieval, data reporting, data
deduplication, data redundancy and data recovery and
replication; electronic data storage for archiving
electronic data; computer services, namely, computer
security threat evaluation and analysis for protecting data
to assure compliance with industry standards;
platform-as-a-service (paas) featuring computer software
platforms for use in data management and data protection;
platform-as-a-service (paas) featuring computer software
platforms for enabling data processing and data management;
providing virtual computer systems and virtual computer
environments through cloud computing on a subscription or
pay-per-use basis; computer disaster recovery planning;
cloud computing featuring software for electronic data
back-up, disaster data recovery, electronic storage for
archiving electronic data, and computer security threat
analysis for protecting data; cloud computing featuring
software for use in computer software development.
An assigned subgroup that includes a plurality of entries is traversed by a prefetcher. It is determined that an expected number of entries associated with the assigned subgroup have been traversed. In response to determining that expected number of entries associated with the assigned subgroup have been traversed, it is determined that a last read entry associated with the assigned subgroup does not correspond to a last entry associated with the assigned subgroup. The prefetcher is preempted by stopping the prefetcher from obtaining a list of entries associated with a remaining portion of the assigned subgroup.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
39.
Using a stream of source system storage changes to update a continuous data protection-enabled hot standby
A remote data recovery system is determined to be unsuitable for communications. A stream of source system storage changes associated with an object is received at a backup system from a source system while the remote data recovery system is unsuitable for communications. The backup system is utilized to generate one or more reference restoration points based on the stream of source system storage changes associated with the object. The remote data recovery system is determined to be suitable for communications. In response to determining that the remote data recovery system is suitable for communications, a hot standby of the object hosted by the remote data recovery system is updated to a reference restoration point generated by the backup system prior to the remote data recovery system becoming suitable for communications.
G06F 12/00 - Accès à, adressage ou affectation dans des systèmes ou des architectures de mémoires
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
40.
Standbys for continuous data protection-enabled objects
A stream of data changes to content of an object associated with a source system is received. A hot standby version of at least a portion of the object maintained at a recovery system is updated by streaming the received stream of data changes to the recovery system. It is determined that a gap exists in the stream of data changes. In response to determining that the gap exists in the stream of data changes, a reference snapshot is requested from the source system. A current state of the hot standby version of at least the portion of the object maintained at the recovery system is caused to be updated to a state of the portion of the object associated with the reference snapshot.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 16/17 - Détails d’autres fonctions de systèmes de fichiers
G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
41.
PROVIDING A GRAPHICAL REPRESENTATION OF ANOMALOUS EVENTS
One or more event logs are received. The one or more event logs are analyzed using a plurality of models to detect one or more anomalous events. A graphical representation of risk entities associated with at least one of the one or more detected anomalous events is provided. A visual representation of automatically detected relationships between the risk entities associated with the at least one of the one or more detected anomalous events is provided in the graphical representation. Indications of measures of anomaly associated with detected anomalous events are provided for the associated risk entities.
G06F 21/62 - Protection de l’accès à des données via une plate-forme, p. ex. par clés ou règles de contrôle de l’accès
G06F 3/0482 - Interaction avec des listes d’éléments sélectionnables, p. ex. des menus
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
Maintenance is performed to determine one or more content files associated with a stored backup snapshot having a size that is greater than a threshold size. It is determined that the size of a content file of the one or more content files is greater than the threshold size. In response to determining that the size of the content file is greater than the threshold size, a new tree data structure is generated and a component file metadata structure corresponding to the content file is split into a plurality of component file metadata structures for the content file.
G06F 16/20 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données structurées, p. ex. de données relationnelles
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 16/13 - Structures d’accès aux fichiers, p. ex. indices distribués
G06F 16/14 - Détails de la recherche de fichiers basée sur les métadonnées des fichiers
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
A response communication that includes one or more data packets is received at a broker associated with a storage node of a plurality of storage nodes via a virtual network associated with the plurality of storage nodes of a storage system. The one or more data packets are provided, via the virtual network associated with the storage nodes, to a tenant communication component associated with an intended destination. A connection between the broker and the tenant communication component associated with the intended destination is terminated. A new connection between the intended destination and the tenant communication component associated with the intended destination is established. The new connection is associated with a virtual network associated with a storage tenant. The one or more data packets are sent to the intended destination via the virtual network associated with the storage tenant.
G06F 15/16 - Associations de plusieurs calculateurs numériques comportant chacun au moins une unité arithmétique, une unité programme et un registre, p. ex. pour le traitement simultané de plusieurs programmes
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
H04L 29/06 - Commande de la communication; Traitement de la communication caractérisés par un protocole
H04L 67/1017 - Sélection du serveur pour la répartition de charge basée sur un mécanisme à tour de rôle
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p. ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
H04L 69/22 - Analyse syntaxique ou évaluation d’en-têtes
File system data that was backed up from a source system to a storage system is determined to be archived. The storage system maintains a tree data structure that enables the backed up file system data to be located. A portion of the tree data structure and the file system data are serialized into a first flat set of data. A first data block associated with the first flat set of data includes a file offset to a first data block associated with a second flat set of data corresponding to a previous archive of the file system data. The first flat set of data is archived to an archival storage.
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/13 - Structures d’accès aux fichiers, p. ex. indices distribués
G06F 16/14 - Détails de la recherche de fichiers basée sur les métadonnées des fichiers
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
45.
Distributed journal for high performance continuous data protection
A set of data changes to a storage associated with a source system is received. for recording the received set of changes, one or more data logs among a plurality of data logs stored in different nodes of a storage system is dynamically selected based at least in part on a dynamic analysis of metrics of the different nodes of the storage system. The data changes are logged in the one or more selected data logs. A reference to a portion of the one or more selected data logs associated with storing the data changes is recorded in a locator register log.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
An indication to perform a backup of data stored in a persistent storage associated with a source system is received. In response to the indication to perform the backup, current execution information at least in part maintained in a volatile memory is captured. The captured current execution information is caused to be stored with backup data from the backup of the data stored in the persistent storage.
G06F 11/00 - Détection d'erreursCorrection d'erreursContrôle de fonctionnement
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/32 - Surveillance du fonctionnement avec indication visuelle du fonctionnement de la machine
A request associated with identifying a backup snapshot to restore among a plurality of backup snapshots is received. At least a first scanned backup snapshot of the plurality of backup snapshots was scanned for one or more vulnerabilities. In response to the request associated with identifying the backup snapshot to restore among the plurality of backup snapshots, a predetermined identification of one or more vulnerabilities of the first scanned backup snapshot is provided via a display interface. The predetermined identification indicates corresponding criticalities of the one or more vulnerabilities of the first scanned backup snapshot. A request to restore a scanned portion of the first scanned backup snapshot is received via the display interface. Data associated with the request to restore the scanned portion of the first scanned backup snapshot is provided.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
48.
Using a storage system to optimize and maintain the metadata associated with a plurality of small files
A size associated with a first content file is determined to be less than a threshold size. In response to determining that the size associated with the first content file is less than the threshold size, a combined metadata structure is updated at least in part by combining metadata of the first content file with metadata of a second content file in the combined metadata structure. A snapshot tree is updated to reference a first portion of the combined metadata structure corresponding to the first content file and to reference a second portion of the combined metadata structure corresponding to the second content file.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/16 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 16/90 - Détails des fonctions des bases de données indépendantes des types de données cherchés
G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
G06F 16/907 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement
G06F 16/908 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des métadonnées provenant automatiquement du contenu
G06F 16/909 - Recherche caractérisée par l’utilisation de métadonnées, p. ex. de métadonnées ne provenant pas du contenu ou de métadonnées générées manuellement utilisant des informations géographiques ou spatiales, p. ex. la localisation
G06F 16/951 - IndexationTechniques d’exploration du Web
49.
Generating standby cloud versions of a virtual machine
Contents of a full snapshot for storage in one or more cloud storage volumes are received. The contents of the full snapshot is stored in the one or more cloud storage volumes. A snapshot of a virtual machine data volume and a snapshot of a virtual machine boot volume are generated based on the contents of the full snapshot stored in the one or more cloud storage volumes. An image of the virtual machine boot volume is generated based on the snapshot of the virtual machine boot volume. The snapshot of the virtual machine data volume, the snapshot of the virtual machine boot volume, and the image of the virtual machine boot volume are stored in a cloud object storage.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 11/07 - Réaction à l'apparition d'un défaut, p. ex. tolérance de certains défauts
A specification of content to be stored in a cloud storage is received at a client-side component. A first portion of the content is divided into a plurality of data chunks. One or more data chunks of the plurality of data chunks that are to be sent via a network to be stored in the cloud storage are identified. It is determined whether a batch size of the one or more identified data chunks does not meets a threshold size. One or more data chunks of a second portion of the content that are to be stored in the cloud storage are identified. It is determined that a size of a second batch of data chunks that includes the one or more identified data chunks of the first portion of the content and the one or more identified data chunks of the second portion of the content does not meet the threshold size. It is determined that a batch period is greater than or equal to a batch threshold period. The second batch of data chunks is written to a storage of a cloud server included in a data plane.
An intermittent network connection between a source system and a destination system is established by establishing a first connection from a management resource to a first port of the destination system, causing a second port of the destination system to be enabled including by providing an instruction via the first connection to the first port of the destination system, establishing a second connection from the management resource to a first port of a source system, causing a second port of the source system to be enabled including by providing an instruction via the second connection to the first port of the source system, registering the destination system with the source system, and causing a third connection to be established between the second port of the source system and the second port of the destination system for transferring data from the source system to the destination system. In response to a determination that a communication session of the third connection has been completed, the intermittent network connection between the source system and the destination system is terminated.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
A backup of a current state of a storage is determined to be initiated. A previous state of the storage storing key-object entries is analyzed to identify parallelization partition identifiers. At least a portion of the partition identifiers is used as boundaries between subgroups of the key-object entries processed in parallel to perform the backup of the current state of the storage.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Hyperconverged infrastructure (HCI) data management platform comprising downloadable software for integrating computer servers, computer networks, and data storage into a single solution for purposes of data management and managing information technology infrastructure and applications; downloadable computer software, namely, a single data management computer software platform for managing data distributed across multiple locations, data centers, public clouds, private clouds and hybrid clouds; downloadable computer software analytics platform in the nature of downloadable cloud computing software for analyzing, visualizing, and manipulating large quantities of unstructured, structured, and semi-structured data distributed across multiple locations, data centers, public clouds, private clouds and hybrid clouds; downloadable computer software that enables management of distributed data sources in a single user interface; downloadable computer software for data management; downloadable computer software for data storage, data backup, data protection, data migration, data archival, data analytics, data searching, data indexing, data retrieval, data reporting, data deduplication, data redundancy and data recovery and replication; downloadable database management computer software for use in the field of enterprise data and information management; downloadable computer software for data disaster recovery and replication; downloadable computer software development tools; downloadable cloud-based software for data management; downloadable mobile application for data management in the nature of data storage, data backup, data protection, data migration, data archival, data analytics, data searching, data indexing, data retrieval, data notifications, data monitoring, data reporting, data deduplication, data redundancy and data recovery and replication; downloadable mobile application for data disaster recovery and replication; downloadable mobile application for managing and operating software in the fields of data security, compliance assessment, and cyber security. (1) Software-as-a-service (saas) services featuring software for use in data management, data storage, data backup, data protection, data migration, data archival, data analytics, data searching, data indexing, data retrieval, data reporting, data deduplication, data redundancy and data recovery and replication; software-as-a-service (saas) services featuring software for use in data protection analysis for cybersecurity and computer security purposes; platform-as-a-service (paas) featuring a single computer software platform for managing data distributed across multiple locations, data centers, public clouds, private clouds and hybrid clouds; platform-as-a-service (paas) featuring computer software analytics platforms for analyzing, visualizing, and manipulating large quantities of data in a single user interface; providing temporary use of on-line non-downloadable software for use in data management, data storage, data backup, data protection, data migration, data archival, data analytics, data searching, data indexing, data retrieval, data reporting, data deduplication, data redundancy and data recovery and replication; electronic data storage for archiving electronic data; computer services, namely, computer security threat evaluation and analysis for protecting data to assure compliance with industry standards; platform-as-a-service (paas) featuring computer software platforms for use in data management and data protection; platform-as-a-service (paas) featuring computer software platforms for enabling data processing and data management; providing virtual computer systems and virtual computer environments through cloud computing on a subscription or pay-per-use basis; computer disaster recovery planning; cloud computing featuring software for electronic data back-up, disaster data recovery, electronic storage for archiving electronic data, and computer security threat analysis for protecting data; cloud computing featuring software for use in computer software development.
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
(1) Software as a service (SaaS) services featuring computer security, data protection and data security software; providing online non-downloadable software for computer security, data protection and data security; software as a service (SaaS) services featuring software for detecting, preventing and managing malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; providing online non-downloadable software for detecting, preventing and managing malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; software as a service (SaaS) services featuring software for recovery of lost, deleted or compromised data; providing online non-downloadable software for recovery of lost, deleted or compromised data; software as a service (SaaS) services featuring software for computer disaster recovery; providing online non-downloadable software for computer disaster recovery; software as a service (SaaS) services featuring software for computer security threat detection, analysis, prevention, integration of threat data, and investigation and management of malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; providing online non-downloadable software for computer security threat detection, analysis, prevention, integration of threat data, and investigation and management of malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; computer security services, namely, identification of cyber threats through multi-source threat intelligence and analysis, development of Internet security programs for minimizing risk of malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; software as a service (SaaS) services featuring customizable computer security software for others in the field of cybersecurity; providing online non-downloadable software featuring customizable computer security software for others in the field of cybersecurity; backup services for computer hard drives, flash drives, and cloud-based storage for recovering and restoring computer data; software as a service (SaaS) services featuring software for backup and recovery of digital and electronic data; providing online non-downloadable software for backup and recovery of digital and electronic data; computer security analysis services, namely, analysis of secondary copies of data for detecting malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; storage services, namely, cloud-based electronic data storage; computer security monitoring services, namely, monitoring of computer systems for detecting malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; computer forensic services; providing online non-downloadable cloud-based software for data classification and data forensics in the field of cybersecurity; computer services, namely, implementation of on-premise AI/ML-based software for data classification and data forensics in the field of cybersecurity; managed cybersecurity services, namely, intrusion detection, intrusion prevention, cybersecurity threat detection and prevention, namely, online scanning, detecting, and management of malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise for cybersecurity purposes; none of the aforementioned services used in relation to advertising, marketing, promotion or e-commerce services for others or for searchable computer database software or data center services.
55.
Automatically implementing a specification of a data protection intent
A current configuration of one or more data management services is monitored. It is determined that the current configuration is insufficient to achieve a data protection intent indicated by a specification of the data protection intent. In response to determining that the current configuration is insufficient to achieve the data protection intent indicated by the specification of the data protection intent, the current configuration of the one or more data management services is modified in a manner to achieve the data protection intent indicated by the specification of the data protection intent.
G06F 11/00 - Détection d'erreursCorrection d'erreursContrôle de fonctionnement
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p. ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
Disclosed are techniques that provide for deduplication in an efficient and effective manner. For example, such methods, computer program products, and computer systems can include generating new feature information for one or more portions of a new backup image, generating first container range information by performing a container range calculation using the new feature information, generating existing feature information for one or more portions of an existing backup image, generating second container range information by performing the container range calculation using the existing feature information, determining a container range affinity between the first container range information and the second container range information, identifying at least one portion of the one or more portions of the existing backup image using a result of the determining, and prefetching the one or more fingerprints corresponding to the at least one portion of the one or more portions of the existing backup image.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
A backup of one or more objects is determined to be performed. Based on one or more conditions, a corresponding deduplication option among a plurality of deduplication options to utilize when backing up the one or more objects is selected. The one or more conditions at least include a condition based on a detected data change pattern. The plurality of deduplication options include a deduplication option associated with utilizing at least in part a plurality of variable-length data chunks for one or more mismatched ranges and/or one or more missing ranges associated with one of the one or more objects associated with the source system. A request to perform the backup of the one or more objects according to the corresponding selected deduplication option is provided to the source system. Backup data associated with the one or more objects is received and stored.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/174 - Élimination de redondances par le système de fichiers
A backup of one or more objects is determined to be performed. Based on one or more conditions, a corresponding deduplication option among a plurality of deduplication options to utilize when backing up the one or more objects is selected. The one or more conditions at least include a condition based on a detected data change pattern. The plurality of deduplication options include a deduplication option associated with utilizing at least in part a plurality of variable-length data chunks for one or more mismatch ranges and/or one or more missing ranges associated with one of the one or more objects associated with the source system. A request to perform the backup of the one or more objects according to the corresponding selected deduplication option is provided to the source system. Backup data associated with the one or more objects is received and stored.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 16/174 - Élimination de redondances par le système de fichiers
59.
Method and system for data consistency across failure and recovery of infrastructure
A method and system for data consistency across failure and recovery of infrastructure. In one embodiment of the method, copies of first data blocks stored in a source memory are sent to a target site via a data link. While sending one or more of the copies of the first data blocks to the target site, source hashes for second data blocks stored in the source memory are calculated, wherein the first data blocks are distinct from the second data blocks. While sending one or more of the copies of the first data blocks to the target site, target hashes of data blocks stored in a target memory of the target site are received. While sending one or more of the copies of the first data blocks to the target site, the source hashes are compared with the target hashes, respectively. After sending the first data blocks to the target site via the data link, copies of only those second data blocks are sent to the target site with source hashes that do not compare equally with respective target hashes.
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
60.
Methods and systems for data resynchronization in a replication environment
Methods, computer program products, computer systems, and the like are disclosed that provide for scalable deduplication in an efficient and effective manner. For example, such methods, computer program products, and computer systems can include determining, at a source site, whether metadata has been received from a target site, and, in response to a determination that the metadata has been received at the source site, retrieving the at least one unit of the source data from the source data store using the metadata and sending, from the source site, the at least one unit of source data to the target site.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
Data associated with a source system is ingested. After the data is ingested, a post-processing metadata conversion process is performed including by selecting an entry of a chunk metadata data structure and determining that a data chunk associated with the selected entry is not referenced by at least a threshold number of objects. In response to determining that the data chunk associated with the selected entry is not referenced by at least the threshold number of objects, metadata of a tree data structure node corresponding to a chunk identifier associated with the data chunk is updated to store a reference to a chunk file storing the data chunk and the selected entry is removed from the chunk metadata data structure.
File metadata structures of a file system are analyzed. At least one metadata element that is duplicated among the analyzed file metadata structures is identified. The at least one identified metadata element is deduplicated including by modifying at least one of the file metadata structures to reference a same instance of the identified metadata element that is referenced by another one of the file metadata structures.
A method and system for data consistency across failure and recovery of infrastructure. In one embodiment of the method, copies of first data blocks stored in a source memory are sent to a target site via a data link. While sending one or more of the copies of the first data blocks to the target site, source hashes for second data blocks stored in the source memory are calculated, wherein the first data blocks are distinct from the second data blocks. While sending one or more of the copies of the first data blocks to the target site, target hashes of data blocks stored in a target memory of the target site are received. While sending one or more of the copies of the first data blocks to the target site, the source hashes are compared with the target hashes, respectively. After sending the first data blocks to the target site via the data link, copies of only those second data blocks are sent to the target site with source hashes that do not compare equally with respective target hashes.
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
64.
Scaling virtualization resource units of applications
A request to launch an application that is comprised of a plurality of layers is received. Each layer of the plurality of layers of the application is comprised of one or more corresponding virtualization resource units. The one or more corresponding virtualization resource units at each of the plurality of layers of the application is expressed as a resource ratio. It is determined that a surplus of resources is available for one or more applications. In response to determining that the surplus of resources is available for one or more applications, a priority associated with the application is determined. A version of the application is launched based on the determined priority associated with the application. The launched version of the application maintains the resource ratio.
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
65.
Systems and methods for identifying possible leakage paths of sensitive information
A computer-implemented method for identifying possible leakage paths of sensitive information may include (i) discovering an original set of users having permission to read the sensitive information at an originating storage device in an originating location via an original set of information transfer paths and (ii) performing a security action. The security action may include (A) determining an additional set of information transfer paths having information transfer paths other than the information transfer paths already discovered, via which the original set of users can write the sensitive information and (B) identifying an additional set of users having permission to read the sensitive information via the additional set of information transfer paths.
G06F 21/34 - Authentification de l’utilisateur impliquant l’utilisation de dispositifs externes supplémentaires, p. ex. clés électroniques ou cartes à puce intelligentes
It is determined that an expiration date for an object associated with a first archive that includes a chunk object that includes a plurality of data chunks has expired. The first archive is stored in a first cloud performance storage class according to an archive tiering policy. It is determined that the archive tiering policy indicates migrating the plurality of data chunks included in the chunk object from the first cloud performance storage class to a second cloud performance storage class. In response to determining that the archive tiering policy indicates migrating the plurality of data chunks included in the chunk object from the first cloud performance storage class to the second cloud performance storage class, the plurality of data chunks included in the chunk object are migrated from the first cloud performance storage class to the second cloud performance storage class.
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/174 - Élimination de redondances par le système de fichiers
An archival storage of data backed up from a repository storage of a primary storage is maintained. Access to data stored in archival storage is limited by one or more access policies based on whether a corresponding data restore has been authorized. A request for specific data stored in the archival storage is received. The one or more access policies are automatically managed based on status and timing of one or more data restore authorizations for the specific data stored in the archival storage.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
68.
AUTOMATICALLY MANAGING ACCESS POLICIES FOR ARCHIVED OBJECTS
An archival storage of data backed up from a repository storage of a primary storage is maintained. Access to data stored in archival storage is limited by one or more access policies based on whether a corresponding data restore has been authorized. A request for specific data stored in the archival storage is received. The one or more access policies are automatically managed based on status and timing of one or more data restore authorizations for the specific data stored in the archival storage.
A request to restore a database to a particular point in time is received. It is determined that a closest preceding backup to the particular point in time is an incremental backup. One or more transaction log file segments needed to restore the database to the particular point in time are determined. An updated incremental backup is generated by applying the one or more determined transaction log file segments to the incremental backup. The updated incremental backup is restored to a primary system.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
70.
Making more active use of a secondary storage system
Backup data associated with a primary storage system is received. At least a view of the received backup data associated with the primary storage system is generated. The view of the of the received backup data associated with the primary storage system includes a tree data structure comprising a root node, a first plurality of child nodes, and a first plurality of leaf nodes. At least some of the first plurality of leaf nodes include corresponding pointers to a corresponding binary large object. A read request for data exposed by the view of the received backup data associated with the primary storage system is received from an external system. In response to receiving the read request, the view of the received backup data associated with the primary storage system is exposed to a requesting system utilizing a protocol associated with the external system.
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/20 - Détection ou correction d'erreur dans une donnée par redondance dans le matériel en utilisant un masquage actif du défaut, p. ex. en déconnectant les éléments défaillants ou en insérant des éléments de rechange
Methods, computer program products, computer systems, and the like are disclosed that provide for scalable deduplication. Such methods, computer program products, and computer systems can include, in response to receiving a request to perform a lookup operation, performing the lookup operation and, in response to the signature not being found, forwarding the request to a remote node. Further, in response to receiving an indication that the signature was not found at the remote node, processing the subunit of data as a unique subunit of data.
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
An indication that a virtual machine is starting is received. Requested data blocks associated with the virtual machine are identified. Based on identifiers of the requested data blocks, a trained learning model is used to predict one or more subsequent data blocks likely to be requested while the virtual machine is starting. The one or more subsequent data blocks are caused to be preloaded in a cache storage. It is determined that the one or more predicted subsequent data blocks are incorrect. It is determined that an end of a boot sequence associated with the virtual machine has been reached. In response to a determination that the end of the boot sequence associated with the virtual machine has been reached, the boot sequence associated with the virtual machine is used to update the trained learning model.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
G06F 12/0862 - Adressage d’un niveau de mémoire dans lequel l’accès aux données ou aux blocs de données désirés nécessite des moyens d’adressage associatif, p. ex. mémoires cache avec pré-lecture
Range information associated with one or more objects is received from a storage system. One or more missing ranges and/or one or more mismatched ranges associated with the one or more objects is determined based on the received range information. A plurality of data chunk identifiers associated with a plurality of variable-length data chunks included in the one or more determined ranges associated with the one or more objects is provided to the storage system. A response that is used to identify among the plurality of variable-length data chunks, one or more variable-length data chunks not already stored in a storage associated with the storage system is received from the storage system. Content of the identified one or more variable-length data chunks is provided to the storage system.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
74.
UTILIZING FIXED-SIZED AND VARIABLE-LENGTH DATA CHUNKS TO PERFORM SOURCE SIDE DEDUPLICATION
Range information associated with one or more objects is received from a storage system. One or more missing ranges and/or one or more mismatched ranges associated with the one or more objects is determined based on the received range information. A plurality of data chunk identifiers associated with a plurality of variable-length data chunks included in the one or more determined ranges associated with the one or more objects is provided to the storage system. A response that is used to identify among the plurality of variable-length data chunks, one or more variable-length data chunks not already stored in a storage associated with the storage system is received from the storage system. Content of the identified one or more variable-length data chunks is provided to the storage system.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 16/174 - Élimination de redondances par le système de fichiers
A plurality of different views of data associated with a storage domain stored on a deduplicated storage are traversed to determine data chunks belonging to each view of the plurality of different views of data associated with the storage domain. A request for a metric associated with disk space utilization of a group of one or more selected views of data associated with the first storage domain included in the plurality of different views of data associated with the first storage domain that are stored on the deduplicated storage is received. Data chunks belonging to the one or more selected views of data associated with the first storage domain of the group are identified. An incremental disk space utilization of the group is determined, including by determining a total size of the identified data chunks. The metric associated with disk space utilization is provided based on the determined incremental disk space utilization of the group.
The disclosed computer-implemented method for normalizing data store classification information may include (1) receiving, at the computing device, classification information from multiple data store content classification sources, (2) training a continuous bag of words (CBOW) classification model with the classification information, (3) receiving a classification tag from a data store for which respectively stored data is classified by one of the data store content classification sources, and (4) classifying, with the trained CBOW classification model, the received classification tag to a corresponding command tag, wherein the command tag represents a meaning of the classification tag. Various other methods, systems, and computer-readable media are also disclosed.
G06F 21/57 - Certification ou préservation de plates-formes informatiques fiables, p. ex. démarrages ou arrêts sécurisés, suivis de version, contrôles de logiciel système, mises à jour sécurisées ou évaluation de vulnérabilité
A plurality of data stripes and one or more parity stripes are generated using a plurality of data chunks stored in a write-ahead log based on an erasure coding configuration. The plurality of data stripes and the one or more parity stripes are stored on corresponding different storage devices. The plurality of data stripes and the one or more parity stripes are associated together under a data protection grouping container.
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 3/00 - Dispositions d'entrée pour le transfert de données destinées à être traitées sous une forme maniable par le calculateurDispositions de sortie pour le transfert de données de l'unité de traitement à l'unité de sortie, p. ex. dispositions d'interface
G06F 11/00 - Détection d'erreursCorrection d'erreursContrôle de fonctionnement
G06F 11/10 - Détection ou correction d'erreur par introduction de redondance dans la représentation des données, p. ex. en utilisant des codes de contrôle en ajoutant des chiffres binaires ou des symboles particuliers aux données exprimées suivant un code, p. ex. contrôle de parité, exclusion des 9 ou des 11
A request to restore a specific backup instance is received. In response to the received request to restore the specific backup instance, a new reference backup instance based on the specific backup instance stored at the storage controlled by the backup system is created at a storage controlled by a backup system. Data associated with the specific backup instance is provided to a recipient system from the storage associated with a backup system. A constructive incremental backup snapshot of the recipient system is performed based on the new reference backup instance.
Methods, computer program products, computer systems, and the like for improved performance, when backing up objects, are disclosed, which can include assigning a top-level entity to a backup host of a number of backup hosts and performing a backup operation on a number of objects. The objects are associated with the top-level entity. The backup operation is performed by the backup host. The backup operation includes determining whether one of the objects includes at least one new data segment or at least one modified data segment, and, in response to a determination that the object includes at least one new data segment or at least one modified data segment, writing information regarding the at least one new data segment or at least one modified data segment in a tracklog dedicated to the top-level entity.
G06F 11/00 - Détection d'erreursCorrection d'erreursContrôle de fonctionnement
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
80.
Multichannel virtual internet protocol address affinity
A plurality of virtual internet protocol addresses for a first single network interface card of a node of a storage cluster are provided to a client. A separate connection is established between the client and the node for each of the plurality of virtual internet protocol addresses. The separate connections are utilized together in parallel to transfer data between the client and the node.
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p. ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
H04L 61/4535 - Répertoires de réseauCorrespondance nom-adresse en utilisant une plate-forme d'échange d'adresses qui établit une session entre deux nœuds, p. ex. des serveurs de rendez-vous, des gardes-barrières de protocoles d'initiation de session [SIP] ou contrôleurs d’accès H.323
Disclosed are techniques that provide for deduplication in an efficient and effective manner. For example, such methods, computer program products, and computer systems can include retrieving container information for a first one or more containers of a plurality of containers of one or more backup images (where the one or more backup images were produced under an existing backup policy), generating pre-processed container information (where the generating the pre-processed container information comprises performing data pre-processing on the container information), determining a plurality of container ranges for the first one or more containers, generating container range affinity information for the one or more backup images (where the generating the container range affinity information comprises performing a container range operation using the plurality of container ranges, and storing the container range affinity information in a container range data structure.
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 9/30 - Dispositions pour exécuter des instructions machines, p. ex. décodage d'instructions
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 18/21 - Conception ou mise en place de systèmes ou de techniquesExtraction de caractéristiques dans l'espace des caractéristiquesSéparation aveugle de sources
A plurality of portions of a content file are stored. It is determined that the content file has a size that is greater than a threshold size. In response to determining that the content file has the size that is greater than the threshold size, a plurality of component file metadata structures are generated for each of the plurality of portions of the content file. A component file metadata structure of the plurality of component file metadata structures corresponds to one of the portions of the content file. Each of the plurality of component file metadata structures includes corresponding metadata that enables data chunks associated with a corresponding portion of the content file to be located.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 16/13 - Structures d’accès aux fichiers, p. ex. indices distribués
G06F 16/22 - IndexationStructures de données à cet effetStructures de stockage
83.
CONCURRENT ACCESS AND TRANSACTIONS IN A DISTRIBUTED FILE SYSTEM
An inode is associated with an incomplete file system operation to a file system object is determined based on an update intent stored in the inode. It is determined that a set of inodes is associated with the incomplete file system operation based on the update intent stored in the inode. The update intent indicates the set of inodes is associated with the incomplete file system operation. It is determined to complete the incomplete file system operation based on evaluating the set of inodes that is associated with the incomplete file system operation. Evaluating the set of inodes that is associated with the incomplete file system operation includes determining whether the set of inodes that is associated with the incomplete file system operation stores a corresponding update intent. The incomplete file system operation is completed based on the evaluation of the set of inodes that is associated with the incomplete file system operation
A cloud server component determines that a size of a first cloud storage element object is at least below a first threshold. In response to the first determination, a client-side component is requested to store additional data in the cloud storage element object including by having the client-side component update the first cloud storage element with an updated version that includes previously existing data of the first cloud storage element and the additional data. The first cloud storage element object is added to a set of one or more cloud storage element objects available for update. The client-side component is configured to generate an updated version of the first cloud storage element object that has a size that is greater than or equal to the first threshold.
One or more objects associated with a source storage is determined to be archived to a remote storage. A corresponding minimum expiration time is stored in nodes of a tree data structure associated with an archive that represents the archived data associated with the source storage. At least a portion of the tree data structure associated with the archive is traversed to identify one or more nodes associated with one or more archived objects having a corresponding expiration time expiring before an expiration time associated with the archive.
Data chunks sent to a content destination are tracked. It is determined whether content of a portion of an object to be sent to the content destination matches one of the data chunks previously sent to the content destination. In response to the determination that the portion of the object to be sent to the content destination matches one of the data chunks previously sent to the content destination, a source reference to the matching previously sent data chunk where the content destination can locally obtain the content for the portion of the object is provided to the content destination.
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p. ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
A request to perform a storage operation for a storage system is received. It is determined that the requested storage operation is associated with a policy that requires a quorum of approvals before being allowed to be performed. It is determined whether the quorum of approvals has been obtained. In response to a determination that the quorum of approvals has been obtained, a command to perform the requested operation is provided to the storage system.
A first fingerprint corresponding to a first chunk associated with a stream of data is generated. It is determined that the first fingerprint matches a second fingerprint of a plurality of fingerprints listed in at least one entry in a deduplication map associated with a plurality of storage systems. A first storage system of the plurality of storage systems is located at a first geographic location and a second storage system of the plurality of storage systems is located at a second geographic location. The first chunk corresponding to the second fingerprint is stored by at least the second storage system. In response to a determination that the first fingerprint matches the second fingerprint, it is determined to store at the first storage system a local copy of the first chunk based in part on one or more deduplication factors. In response to the determination that the one or more deduplication factors indicate to store the local copy of the first chunk, the local copy of the first chunk is stored at the first storage system.
Application-level data in a storage system are evaluated. For example, a backup analysis tool retrieves a backup object stored in the storage system. The backup analysis tool reconstructs an application object from the backup object. The backup analysis tool accesses the first application object according to a native application format associated with the first object.
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
An amount of expiration time extension for one or more objects associated with a first archive of a first snapshot of a source storage is determined based at least in part on a second data management policy associated with a second archive and one or more dynamically determined metrics. The first archive that includes the one or more objects is caused to be stored to a remote storage. At least a portion of content of the first archive is referenced by data chunks stored in a first chunk object of the remote storage and the first archive is associated with a first data management policy. Based on the determined amount of expiration time extension, an expiration time for the one or more objects associated with the first archive is stored in an archive metadata of the one or more objects associated with the first archive.
A repository of replicated chunk files is analyzed to identify chunk files that meet at least a portion of combination criteria. Selected chunk files are associated together under a data protection grouping container. Erasure coding is applied to the data protection grouping container including by utilizing the selected chunk files as different data stripes of the erasure coding and generating one or more parity stripes based on the different data stripes.
A reference snapshot of a storage is stored. Data changes that modify the storage are received. The data changes are captured by a write filter of the storage. The received data changes are logged. The data changes occurring after an instance time of the reference snapshot are applied to the reference snapshot to generate a first incremental snapshot corresponding to a first intermediate reference restoration point. The data changes occurring after an instance time of the first incremental snapshot are applied to the first incremental snapshot to generate a second incremental snapshot corresponding to a second intermediate reference restoration point.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 16/11 - Administration des systèmes de fichiers, p. ex. détails de l’archivage ou d’instantanés
G06F 16/17 - Détails d’autres fonctions de systèmes de fichiers
G06F 16/901 - IndexationStructures de données à cet effetStructures de stockage
93.
Providing a distributed and replicated data store in a heterogeneous cluster
A plurality of logical storage segments of storage drives of a plurality of storage nodes are identified. At least one of the storage nodes includes at least a first logical storage segment and a second logical storage segment included in the plurality of logical storage segments. A distributed and replicated data store using a portion of the plurality of logical storage segments that excludes at least the second logical storage segment is provided. An available storage capacity metric associated with the plurality of logical storage segments is determined to meet a first threshold. In response to the determination that the available storage capacity metric meets the first threshold, at least the second logical storage segment is dynamically deployed for use in providing the distributed and replicated data store in a manner that increases a storage capacity of the data store while maintaining a fault tolerance policy of the distributed and replicated data store.
Various systems and methods are provided in which a replication process is initiated between a primary site and a recovery site, each having plurality of gateway appliances. Replication loads are evaluated for each given gateway appliance of the plurality of gateway appliances. If a determination is made that at least one gateway appliance of the plurality of gateway appliances is not overloaded, the plurality of gateway appliances are sorted based on replication loads respectively associated with each gateway appliance, and a determination is made as to whether a relative difference in replication loads between a gateway appliance having a highest replication load and a gateway appliance having a lowest replication load exceeds a difference threshold to determine whether the replication workloads between the gateway appliances should be rebalanced.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 11/00 - Détection d'erreursCorrection d'erreursContrôle de fonctionnement
G06F 9/50 - Allocation de ressources, p. ex. de l'unité centrale de traitement [UCT]
G06F 3/06 - Entrée numérique à partir de, ou sortie numérique vers des supports d'enregistrement
G06F 9/48 - Lancement de programmes Commutation de programmes, p. ex. par interruption
G06F 16/27 - Réplication, distribution ou synchronisation de données entre bases de données ou dans un système de bases de données distribuéesArchitectures de systèmes de bases de données distribuées à cet effet
H04L 67/1095 - Réplication ou mise en miroir des données, p. ex. l’ordonnancement ou le transport pour la synchronisation des données entre les nœuds du réseau
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
95.
Deploying a cloud instance of a user virtual machine
An instruction to generate a cloud instantiation of a secondary storage system is provided. One or more secondary storage clusters are virtually rebuilt in the cloud instantiation of the secondary storage system. A new cloud instance of a user virtual machine is deployed based on at least a portion of data stored in the one or more rebuilt secondary storage clusters of the cloud instantiation of the secondary storage system. A version of at least the portion of the data of the one or more rebuilt secondary storage clusters is provided to a cloud deployment server.
G06F 9/455 - ÉmulationInterprétationSimulation de logiciel, p. ex. virtualisation ou émulation des moteurs d’exécution d’applications ou de systèmes d’exploitation
H04L 67/1097 - Protocoles dans lesquels une application est distribuée parmi les nœuds du réseau pour le stockage distribué de données dans des réseaux, p. ex. dispositions de transport pour le système de fichiers réseau [NFS], réseaux de stockage [SAN] ou stockage en réseau [NAS]
96.
Maintaining and updating a backup view of an application and its associated objects
A first backup of source data is performed. A second backup of the source data is determined to be performed at least in part by determining a plurality of objects that have changed since the first backup and determining a corresponding backup type for each of the plurality of objects that have changed since the first backup. Based on the determined corresponding backup types, a second backup of the source data is performed including by performing an incremental backup of a first portion of the plurality of objects that have changed since the first backup and a full backup of a second portion of the plurality of objects that have changed since the first backup.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
An identification of a primary snapshot created for a primary storage system is received. A first request for a first metadata of a first file directory structure object associated with the primary snapshot is issued. A second request for data content of the first file directory structure object associated with the primary snapshot is determined to be sent to a recipient device based on a received response to the first request. A third request for a second metadata of a second file directory structure object associated with the primary snapshot is determined to be sent to the recipient device. Timing and ordering of issuance of a plurality of requests that at least include the second request and the third request to the recipient device are managed based on a determined performance metric of the recipient device and corresponding relative impact to the performance metric of the recipient device.
G06F 11/14 - Détection ou correction d'erreur dans les données par redondance dans les opérations, p. ex. en utilisant différentes séquences d'opérations aboutissant au même résultat
G06F 11/34 - Enregistrement ou évaluation statistique de l'activité du calculateur, p. ex. des interruptions ou des opérations d'entrée–sortie
09 - Appareils et instruments scientifiques et électriques
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Downloadable computer software for computer security, data protection and data security; downloadable computer software for detecting, preventing and managing malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; downloadable computer software for recovery of lost, deleted or compromised data; downloadable computer software for disaster recovery; downloadable computer software for computer security threat detection, analysis, prevention, integration of threat data, and investigation and management of malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; downloadable computer software featuring customizable computer security software for others in the field of cybersecurity; downloadable computer software for backup and recovery of digital and electronic data; downloadable computer software featuring AI/ML-based software for data classification and data forensics in the field of cybersecurity; none of the aforementioned goods used in relation to advertising, marketing, promotion or ecommerce for others or for searchable computer database software or data centers. Software as a service (SaaS) services featuring computer security, data protection and data security software; providing non-downloadable software for computer security, data protection and data security; software as a service (SaaS) services featuring software for detecting, preventing and managing malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; providing non-downloadable software for detecting, preventing and managing malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; software as a service (SaaS) services featuring software for recovery of lost, deleted or compromised data; providing non-downloadable software for recovery of lost, deleted or compromised data; software as a service (SaaS) services featuring software for disaster recovery; providing non-downloadable software for disaster recovery; software as a service (SaaS) services featuring software for computer security threat detection, analysis, prevention, integration of threat data, and investigation and management of malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; providing non-downloadable software for computer security threat detection, analysis, prevention, integration of threat data, and investigation and management of malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; computer security services, namely, identification of cyber threats through multi-source threat intelligence and analysis, development of mitigation strategies to minimize risk of malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; software as a service (SaaS) services featuring customizable computer security software for others in the field of cybersecurity; providing non-downloadable software featuring customizable computer security software for others in the field of cybersecurity; backup services for computer hard drives, flash drives, and cloud-based storage for recovering and restoring computer data; software as a service (SaaS) services featuring software for backup and recovery of digital and electronic data; providing non-downloadable software for backup and recovery of digital and electronic data; computer security analysis services, namely, analysis of secondary copies of data for detecting malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; storage services, namely, cloud-based electronic data storage; computer security monitoring services, namely, monitoring of computer systems for detecting malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise; computer forensic services; providing non-downloadable cloud-based and on-premise AI/ML-based software for data classification and data forensics in the field of cybersecurity; managed cybersecurity services in the fields of intrusion detection, intrusion prevention, cybersecurity threat detection and prevention, namely, online scanning, detecting, and management of malware, ransomware, and other cyberattacks, data breaches, data exfiltration, unauthorized access, unauthorized data movement and other indicators of compromise for cybersecurity purposes; none of the aforementioned services used in relation to advertising, marketing, promotion or e-commerce services for others or for searchable computer database software or data center services.
99.
Method and system for improving efficiency in the management of data references
Methods, computer program products, and computer systems for the management of data references in an efficient and effective manner are disclosed. Such methods, computer program products, and computer systems include receiving a change tracking stream at the computer system, identifying a data object group, and performing a deduplication management operation on the data object group. The change tracking stream is received from a client computing system. The change tracking stream identifies one or more changes made to a plurality of data objects of the client computing system. The identifying is based, at least in part, on at least a portion of the change tracking stream. The data object group represents the plurality of data objects.
G06F 16/00 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet
G06F 16/215 - Amélioration de la qualité des donnéesNettoyage des données, p. ex. déduplication, suppression des entrées non valides ou correction des erreurs typographiques
A selected data chunk associated with an object is determined to be sent to a destination. A chunk compression grouping storing the selected data chunk associated with the object is identified. The identified chunk compression grouping includes a plurality of data chunks compressed together. A data content version that includes the selected data chunk associated with the object to be provided to the destination is determined from a plurality of data content versions based at least in part on a metric associated with the identified chunk compression grouping.
