Abstract: A method of consolidating snapshots includes receiving a request to consolidate a first snapshot with a second snapshot into a third snapshot, the first and second snapshots stored in separate backup files, each backup file organized as a directory where data parts of the first and second snapshots can be hard linked to locations outside of the backup file, comparing the data parts of the first and second snapshots to determine if any second snapshot data part fully overlaps with any first snapshot data part, responsive to determining that a second snapshot data part fully overlaps with a first snapshot data part, hard linking the determined second snapshot data part into the third snapshot, and storing the third snapshot in the backup file.

Abstract: In some examples, a method comprises: receiving a request to read data within a specified range from a backup file storing at least one base snapshot and at least one incremental snapshot; looking up the specified range in range filters from the backup file, the range filters corresponding to snapshots stored in the backup file and each range filter comprising bits indicating whether data exists at respective ranges within the snapshot corresponding to the respective range filter; and in response to the looking up, reading the requested data from the looked-up range in the backup file.

Abstract: Techniques for backing a file system with a cloud-based object store are disclosed. In some embodiments, a computer system performs operations comprising: receiving, by a user space file system, a first request to write a first set of data to a file; based on the receiving of the first request to write the first set of data to the file, writing, by the user space file system, the first set of data to the file in a cloud-based key-value object store; receiving, by the user space file system, a second request to read a second set of data from the file; and based on the receiving of the second request to read the second set of data from the file, fetching, by the user space file system, the second set of data from the file in the cloud-based key-value object store.

Abstract: A computer-implemented method at a data management system comprises: generating, with one or more processors, a containerized runtime in a memory in communication with the one or more processors; instantiating, with the one or more processors, an app in the runtime; receiving, with the one or more processors, a request from the app for data; retrieving, with the one or more processors, a copy of the requested data from a data source; and transmitting, with the one or more processors, the data to the containerized runtime for the app to operate on.

Abstract: A computer-implemented method at a data management system comprises receiving, at the system, a write made to a virtual machine from a virtual machine host; computing, at the system, a fingerprint of the transmitted write; comparing, at the system, the computed fingerprint to malware fingerprints in a malware catalog; repeating the computing and comparing; and disabling the virtual machine if a number of matches from the comparing breaches a predetermined threshold over a predetermined amount of time.

Abstract: Portable ear-worn acoustic devices having a wingtip anchor for improved anchoring for active users and to accommodate a wide range of ear sizes and shapes are provided herein. Such acoustic devices an include an earbud device body and a wingtip anchor that extends from an outer face of the device body. The wingtip anchor can include a base portion and a protruding portion that extends upwards and is angled or curved inwardly so as to engage the upper concha of the ear. The wingtip anchor can be flexible so that engagement of a distal portion of the anchor exerts an inwardly directed spring force on the device body to maintain the earbud device body within the ear. Such acoustic devices can further include a multi-function button that is integrated with the wingtip anchor such that the base portion of the wingtip anchor is a faceplate for the multi-function button.

Abstract: In some examples, a method comprises: receiving a request to read data within a specified range from a backup file storing at least one base snapshot and at least one incremental snapshot; looking up the specified range in range filters from the backup file, the range filters corresponding to snapshots stored in the backup file and each range filter comprising bits indicating whether data exists at respective ranges within the snapshot corresponding to the respective range filter; and in response to the looking up, reading the requested data from the looked-up range in the backup file.

Abstract: A computer-implemented method at a data management system comprises: receiving, at a storage appliance from a server hosting a virtual machine, a write made to the virtual machine; computing, at the storage appliance, a fingerprint of the transmitted write; comparing, at the storage appliance, the computed fingerprint to malware fingerprints in a malware catalog; repeating the computing and comparing; and disabling the virtual machine if a number of matches from the comparing breaches a predetermined threshold over a predetermined amount of time.

Abstract: In some examples, a data management and storage (DMS) platform, comprises peer DMS nodes in a node cluster, a distributed data store comprising local and cloud storage, and at least one processor configured to perform operations in a method of creating a local consolidated patch file from a patch file chain stored in the cloud storage. The operations include, in a first dry-run phase, creating a logical patch file image of data blocks in one or more cloud patch files stored in the cloud storage; in a second data-transfer phase, downloading at least some of the data blocks from the cloud patch files identified by the logical patch file image, the second data-transfer phase comprising a coalescing operation to construct a set of coalesced reads of the data blocks; and creating and storing, in the local storage, the local consolidated patch file using the downloaded data blocks.

Abstract: In some examples, a data management system generates snapshots in a distributed file system based on a protocol or a user triggered event, The data management system identifies a snappable file in a distributed file system and a first data block in the snappable file, the first data block including data and attribute data. The system scans an index file to access the attribute data of the first data block and initiates construction of a patch file based on the accessed attribute data. The system repeats the scanning of the index file to access attribute data of at least a further second data block, the second data block including data and attribute data, and completes construction of the patch file based on the accessed attribute data of the first and second data blocks. The system generates conversion simulation information by collecting attribute data for all the data blocks of the constructed patch file, and writes the simulation information to a patch file image.

Abstract: In some examples, a data management and storage (DMS) platform comprises peer DMS nodes in a node cluster, a distributed data store comprising local and cloud storage, and at least one processor configured to perform operations in a method of creating a local consolidated patch file from a patch file chain stored in the cloud storage. Example operations comprise, in a first dry-run phase, creating a patch file image of data blocks in one or more cloud patch files stored in the cloud storage; in a second data-transfer phase, downloading at least some of the data blocks from the cloud patch files identified by the patch file image; and creating and storing, in the local storage, the local consolidated patch file using the downloaded data blocks.

Abstract: According to the embodiments provided herein, back contacts for photovoltaic devices can include one or more metal oxynitride layers.

Abstract: In some examples, a data management system processes snapshots of a distributed file system, the distributed file system having files, each file comprising multiple data chunks. The data management system performs operations including storing file-to-chunk mapping in file system metadata; creating, for each chunk, a chunk generation ID by associating each chunk with a file system generation ID; in a next-generation snapshot of the distributed file system, incrementing, for all chunks in the next-generation snapshot, the respective chunk generation IDs; and taking a snapshot of the file system metadata and storing an updated file-to-chunk mapping associated with the next-generation snapshot.

Abstract: A computer-implemented method at a data management system comprises: generating, with one or more processors, a containerized runtime in a memory in communication with the one or more processors; instantiating, with the one or more processors, an app in the runtime; receiving, with the one or more processors, a request from the app for data; retrieving, with the one or more processors, a copy of the requested data from a data source; and transmitting, with the one or more processors, the data to the containerized runtime for the app to operate on.

Abstract: A computer-implemented method at a data management system comprises: generating, with one or more processors, a containerized runtime in a memory in communication with the one or more processors; instantiating, with the one or more processors, an app in the runtime; receiving, with the one or more processors, a request from the app for data; retrieving, with the one or more processors, a copy of the requested data from a data source; and transmitting, with the one or more processors, the data to the containerized runtime for the app to operate on.

Abstract: A computer-implemented method at a data management system comprises: generating, with one or more processors, a containerized runtime in a memory in communication with the one or more processors; instantiating, with the one or more processors, an app in the runtime; receiving, with the one or more processors, a request from the app for data; retrieving, with the one or more processors, a copy of the requested data from a data source; and transmitting, with the one or more processors, the data to the containerized runtime for the app to operate on.