302 results about "Object store" patented technology

A database system integrates in-database machine learning (ML) models with in-database large language models (LLMs) or other generative artificial intelligence (AI) models that enable new applications. The database system receives one or more inferences from an ML model and provides an inference input to a retrieval agent of an object store. One or more vector stores represent a plurality of reference documents using semantic encodings. The retrieval agent performs a similarity search of the one or more vector stores to retrieve a set of passages from the plurality of reference documents based on similarity of encodings of the inference input and encodings of passages in the plurality of reference documents. The database system generates a linguistic prompt for an LLM having a context including the inferences and passages and applies the LLM to the linguistic prompt to generate a natural language explanation of the one or more inferences.

Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

Techniques are described for enabling concurrent and non-blocking replication object deletion during cross-region replications. In some embodiments, in a target file system, a target replication pipeline as part of a cross-region replication, and a deletion pipeline operate in parallel. The deletion pipeline deletes processed objects reaching the last pipeline stage of the target replication pipeline after each checkpoint in the target replication pipeline. In some embodiments, after a non-recoverable failure during the cross-region replication, the cross-region replication can be restarted from the beginning (i.e., fresh restart) without waiting for its unused objects in the Object Store to be deleted by utilizing a generation number associated with each object to delete the unused objects in a background process while allowing deleting processed objects as normal for the freshly restarted cross-region replication.

Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

Embodiments are directed to a file system that include object stores. An object store for write requests may be provided. Write ahead log (WAL) entries that include data blocks may be generated. A WAL object may be generated based on the WAL entries and stored in the object store. An in-memory overlay may be updated to associate the data blocks with the WAL object. A checkpoint operation may be executed to: generate an index object that includes index entries that associate other data blocks with data objects stored in the object store; update the index object to include index entries that associate the data blocks with the WAL object; store the updated index object in the object store; update the in-memory overlay to remove the association of the data blocks and the WAL object and update the in memory WAL to remove records of successfully checkpointed WAL objects.

A system and method for cybersecurity inspection of private software registries is presented. The method includes: deploying an inspection broker in a computing environment, the inspection broker configured to communicate with a private registry of the computing environment; configuring the inspection broker to access the private registry for a list of objects stored in the private registry; selecting an object from the private registry for cybersecurity inspection; inspecting the object for a cybersecurity object in the computing environment; generating an inspection result based on detection of the cybersecurity object; sending the inspection result to an inspection environment, the inspection environment including a representation of the computing environment; and initiating a mitigation action based on the inspection result, the mitigation action generated in response to an instruction from the inspection environment.

The invention belongs to the technical field of distributed storage, and discloses a double-layer extensible cache system and method oriented to a separated memory, the system comprises at least one computing server CS and a memory resource pool formed by at least one memory server MS, and each CS and the memory resource pool are interconnected through RDMA; a cache CiCS used for sharing cache objects for all clients running in the CS is constructed in each CS, a cache CiMS used for storing the cache objects is constructed in the memory resource pool, and all the clients running in all the CSs can access all the cache objects stored in the CiMS; the CiCS can accelerate the access of the CiMS, and the CiMS can accelerate the access of the underlying storage system. In addition, the dynamic expansion and elasticity of the cache system are realized according to actual requirements, and the cache service does not need to be paused or the performance is not obviously degraded. According to the invention, the performance and the expansibility of the double-layer extensible cache of the separated memory are improved.

A method for providing access to objects associated with a particular client in a cloud storage system is disclosed. The method includes the steps of establishing a connection with a user, providing a client namespace associated with the client to the user, where the client namespace represents objects stored on the cloud storage system and objects stored on a private storage system apart from the cloud storage system, receiving a request from the user to access an object stored on the private storage system, and providing information to the user to facilitate access to the object stored on the private storage system by said user. Other systems and methods are also disclosed. Important advantages of the present invention are facilitated by separating the logic for user access (control plane) from the actual storage (Storage plane). Private file system access can still be managed from the cloud, while keeping the client data private.

Data storage operations, including content-indexing, containerized deduplication, and policy-driven storage, are performed within a cloud environment. The systems support a variety of clients and cloud storage sites that may connect to the system in a cloud environment that requires data transfer over wide area networks, such as the Internet, which may have appreciable latency and / or packet loss, using various network protocols, including HTTP and FTP. Methods are disclosed for content indexing data stored within a cloud environment to facilitate later searching, including collaborative searching. Methods are also disclosed for performing containerized deduplication to reduce the strain on a system namespace, effectuate cost savings, etc. Methods are disclosed for identifying suitable storage locations, including suitable cloud storage sites, for data files subject to a storage policy. Further, systems and methods for providing a cloud gateway and a scalable data object store within a cloud environment are disclosed, along with other features.

An intelligent assistant incorporating a Large Language Model (LLM) can transform a transcript containing communications regarding tasks into structured data. The transcript can be a meeting transcript or a transcript of a chatbot chat that was autonomously initiated by the intelligent assistant to obtain additional information regarding a task. With LLM assistance, the intelligent assistant transforms unstructured communication data from the transcript into structured data which is then assigned to relevant task objects stored in a database. Prior to processing a transcript, personal data therein can be sanitized, and the intelligent assistant can divide the transcript into smaller segments which each encapsulate a discussion of a different topic.

Techniques are provided for modifying a read path to process read operations during a storage operation, such as an operation to migrate objects storing data of a volume. The objects are stored across a storage tier and capacity tier of a source object store. As part of migrating the volume to a destination object store, the objects are migrated to the destination cluster. Directly copying the objects involves multiple read operations to the source object store and a write operation at the destination object store. The techniques provided herein improve the efficiency of the migration by initially sending metadata from the source object store to the destination object store for performing backend block copy operations to migrate the volume.

Techniques are provided for volume group backup, volume group restore, and volume group garbage collection for volume groups backed up to an object store. A volume group workflow is implemented to orchestrate individual consistent volume workflows that are separately and individually implemented by nodes hosting constituent volumes of a volume group. The volume group workflow and the individual consistent volume workflows are performed to back up the volume group to the object store, restore a volume group backup from the object store to a restore destination, and / or perform garbage collection on slots of objects storing data unique to a volume group backup to delete.

In some implementations, a storage node receives data processing instructions from a compute node of a network architecture. The storage node detects a Directed Acyclic Graph (DAG) within the data processing instructions. The DAG includes a plurality of data processing operations arranged within the DAG according to an execution. The data processing operations further include user-defined function (UDF) information associated with a UDF. The storage node may retrieve a first data object from an object store of the distributed storage node based on object keys information within the plurality of data processing operations. The storage node may execute the plurality of data processing operations using the retrieved first data object to generate a DAG execution result, the executing of the plurality of data processing operations based on the execution order. The storage node may communicate the DAG execution result to the compute node in response to the data processing instructions.

Managing access to stored objects includes receiving, by a storage OS in a computing system, an access key identifier (ID) and access key associated with a user of an object storage service (OSS); determining, by a directory service, whether the user is a member of a group authorized to access a storage object in at least one of a network accessible storage (NAS) volume and an OSS bucket, based at least in part on the access key ID; in response to the user being a group member, attempting to authenticate the user by the storage OS with the directory service based at least on the access key ID and the access key; and in response to the user being authenticated by the directory service, allowing, by the storage OS, access by the user to the storage object stored in at least one of the NAS volume and the OSS bucket.

A unified security agent manager plugin within a virtual machine compute instance manages at least one agent installed within the compute instance of a cloud environment. The plugin periodically receives agent inventory information, where the agent inventory information identifies (i) a plurality of platform types of the agent, and (ii) for each platform type, one or more deployable versions of the agent. The plugin selects a platform type from the plurality of platform types. The plugin compares the one or more deployable versions corresponding to the selected platform type with a version of the agent currently installed in the compute instance. If the version currently installed in the compute instance is older than the one or more deployable versions, the plugin fetches an agent object corresponding to a deployable version from an object storage repository, and updates the version currently installed in the compute instance to the fetched deployable version.

A system and method for implementing an objects browser service is disclosed. The system and method include receiving, from a web browser of a user device, a first API call to access a first object in a first object store hosted on a public cloud, in response to the first API call, making a second API call to the first object store to transmit the first object to the user device, receiving, from the web browser of the user device, a third API call to access a second object in a second object store hosted in an on-premises system, and, in response to the third API call, making a fourth API call to the second object store to transmit the second object to the user device.

In some examples, a first computing system receives a first metadata change made to metadata of a first instance of an object stored at a storage location of the first computing device. The first computing system associates, with the first metadata change, a time of the first metadata change. Based on receiving replication of a second instance of the object from a second computing system, the first computing system determines that a second metadata change was made to metadata of the second instance of the object. Further, the second instance of the object includes a time of the second metadata change. The first computing system at least one of: resolves a conflict between the first metadata change and the second metadata change based at least on comparing the times, or merges the first metadata change with the second metadata change into the metadata for the object.

The invention relates to the technical field of warehouse logistics, and discloses a carrying method and device and a warehousing system.The method comprises the steps that the cargo level of each stock object in a target container to be warehoused is determined; determining the container level of the target container based on the cargo level of each inventory object in the target container; based on the container level of the target container, under the condition that the target container meets a first preset condition, determining a storage area corresponding to the target container as a first inventory area; under the condition that the target container does not meet the first preset condition, determining a storage area corresponding to the target container as a second inventory area; the cargo level of the inventory objects stored in the first inventory area is higher than that of the inventory objects stored in the second inventory area. According to the embodiment of the invention, the warehouse-out efficiency and the working efficiency of the warehousing system can be improved.

An object-based data storage system implemented by a computer for storing data in a plurality of objects (16A, 16B, 25A, 25B). The data storage system comprises a storage medium (80) configured to store said plurality of objects. Each one of the plurality of objects comprises a plurality of fields including a data field (18) configured for storing said data therein and, a separate object ID attribute field (17) configured for storing identification information associated with the object. The information stored within the object ID attribute field of at least one (16A, 16B) of the plurality of objects comprises metadata other than identification information associated with the at least one object. A processor is configured to access the at least one object (16A, 16B) from amongst the plurality of objects stored within the storage medium at least to retrieve information stored within an object ID attribute field (17) hereof thereby to retrieve the metadata.

Disclosed is a show case capable of managing and displaying objects stored therein. A show case according to one aspect of the present disclosure is a show case having an accommodation space in which an object is stored, and includes: a body; a moving body configured to form the accommodation space together with the body and including a transparent window; a blowing part configured to circulate air in the accommodation space; a first illumination configured to illuminate an object placed on a bottom surface of the accommodation space; a second illumination configured to illuminate a rear surface of the accommodation space; an input part to which an image of the object accommodated in the accommodation space is input; and a controller configured to recommend a type of second illumination to a user depending on the image input to the input part.

Techniques are provided for on-demand serverless disaster recovery. A primary node may host a primary volume. Snapshots of the primary volume may be backed up to an object store. In response to failure, a secondary node and / or an on-demand volume may be created on-demand. The secondary node may provide clients with failover access to the on-demand volume while a restore process restores a snapshot of the primary volume to the on-demand volume. In some embodiments, there was no secondary node and / or on-demand volume while the primary node was operational. This conserves computing resources that would be wasted by otherwise hosting the secondary node and / or on-demand volume while clients were able to access the primary volume through the primary node. Modifications directed to the on-demand volume are incrementally backed up to the object store for subsequently restoring the primary volume after recovery.

Techniques are provided for migrating a volume utilizing an object copy work queue and an object copy driver module. Data of the volume is stored within objects stored across a storage tier and capacity tier of a source object store. As part of migrating the volume to a destination object store, the objects are migrated to the destination cluster. Directly copying the objects involves multiple read operations to the source object store and a write operation at the destination object store. The techniques provided herein improve the efficiency of the migration by initially sending metadata from the source object store to the destination object store for performing backend object copy operations to migrate the volume. This results in fewer operations and less network usage, thus improving the efficiency and cost of migrating the volume.

The present disclosure relates to data storage device (DSD) hardware, and more particularly to systems and methods for encrypting data stored on the DSD. The DSD includes a non-volatile storage medium for storing a plurality of file system data objects using block addressing. A device controller is integrated with the DSD and includes hardware circuitry configured to encrypt data to be stored on the storage medium. The controller receives a request for an encrypted file system data object from a host computer system, identifies a range of block ranges in which the requested encrypted file system data object is stored on the storage medium, and sends the file system data object stored in the identified block range to the host computer system in an encrypted form as stored on the storage medium.

Techniques are provided for performing a storage operation targeting objects stored across multiple storage tiers of a cloud storage environment. A volume may be backed up as objects stored across the multiple storage tiers of the cloud storage environment, such as a standard storage tier directly accessible to the storage operation, an archival storage tier not directly accessible to the storage operation, etc. The storage operation may target the objects, such as where the storage operation is a directory restore operation to restore a directory of the volume. The storage operation can be successfully implemented such as to restore the directory even though objects of the storage operation are stored across the multiple storage tiers of the cloud storage environment.

The invention discloses a data recovery method and device and computing equipment, and belongs to the technical field of data security. The method is applied to a storage system for storing data by adopting a block-level storage mode. The method comprises the following steps: determining a target object of which data needs to be recovered; determining a first storage address of a data block for storing the target object in the first snapshot according to the first mapping relation set; and recovering the data of the target object according to the data stored in the first storage address in the first snapshot. Wherein the target object is any semantic-level data, a data block of the target object stored in a block-level mode is stored in the storage system, and the first snapshot is obtained after snapshot operation is executed on the data of the storage system at the first time; the first mapping relation set comprises the corresponding relation between the object maintained by the storage system after the first time and the storage address of the data block of the object. By means of the method, data recovery with semantic-level data as granularity can be achieved.

Embodiments of the present disclosure provide for improved identification of ownership and / or ownership lineage for a data repository, such as a shared file drive. Ownership data and / or ownership lineage data is identified based on data associated with the data repository itself and / or file data objects stored thereon in conjunction with data from a user linkage database. In this regard, accurate identification of a particular owner or owner(s) of a data repository may be determined from the data repository, and the user linkage database may serve additional details of such owner(s), linkages to other user(s) and / or group(s) of users embodying owner(s), and / or the like. Identified ownership data and / or ownership lineage data may be used for a myriad of additional processes, such as to notify users, determine what data repositories to perform detailed, efficient scans of based on group membership of the owner of said data repositories, or the like.

A system stores multiple documents in a log-structured object store, each document associated with a sequence number and a document value. The log-structured object store includes multiple log segments, each storing documents within a defined sequence number range. A first log-structured merge-tree is maintained to map document keys to corresponding sequence numbers, while a second log-structured merge-tree maps sizes of stale documents to their sequence numbers. A ratio is determined between the size of stale documents and the total size of documents in at least one log segment. In response to the ratio exceeding a predetermined threshold, a compaction operation is initiated to delete stale documents and consolidate active documents into a reduced number of log segments using the reclaimed space. The first and second log-structured merge-trees are updated based on the compaction results to reflect the current state of the data.

Techniques are provided for a data format for efficient management of checkpoint support. The data format corresponds to a base metafile and a set of instance metafiles used to track storage operations such as a directory restore operation. The base metafile and the set of instance metafiles can be used to resume the storage operation from where the storage operation left off in the event of a failure. The base metafile and the set of instance metafiles can be used to track progress of the storage operation processing objects stored within an object store of a cloud storage environment.