A method of summarizing data files includes implementing, at a server, a storage event for a data file, analyzing the data file and creating a summary of the data file, and storing the summary linked to the data file.

In some embodiments, a computer system may buffer, in a local storage buffer, data to be stored at the cloud and upload the data to the cloud storage from the local storage buffer. Upon receipt of an acknowledgement, from the cloud storage, that the data was successfully uploaded, the computer system may delete the data from the local storage buffer. The computer system may provide a ghost file representation of the uploaded data through the computer system, through which the data uploaded to the cloud storage may be accessed. In some embodiments, the computer system may access multiple cloud storage accounts, each corresponding to a file folder on the computer system, allowing the user to easily access different cloud storage accounts. The computer system may recover data that was deleted from either local persistent storage or the cloud storage.

In some embodiments, a computer system may buffer, in a local storage buffer, data to be stored at the cloud and upload the data to the cloud storage from the local storage buffer. Upon receipt of an acknowledgement, from the cloud storage, that the data was successfully uploaded, the computer system may delete the data from the local storage buffer. The computer system may provide a ghost file representation of the uploaded data through the computer system, through which the data uploaded to the cloud storage may be accessed. In some embodiments, the computer system may access multiple cloud storage accounts, each corresponding to a file folder on the computer system, allowing the user to easily access different cloud storage accounts. The computer system may recover data that was deleted from either local persistent storage or the cloud storage.

Data transformation caching in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: identifying, in dependence upon one or more machine learning models to be executed on the GPU servers, one or more transformations to apply to a dataset; generating, in dependence upon the one or more transformations, a transformed dataset; storing, within one or more of the storage systems, the transformed dataset; receiving a plurality of requests to transmit the transformed dataset to one or more of the GPU servers; and responsive to each request, transmitting, from the one or more storage systems to the one or more GPU servers without re-performing the one or more transformations on the dataset, the transformed dataset.

Techniques for monitoring local and/or remote file systems by a synchronization component (e.g., client/server) of a cloud-based platform are disclosed. In some embodiments, a method of building synchronization events by a synchronization component (e.g., a synchronization server/client) includes obtaining a set of items that have been changed and their new states and retrieving last known states of the set of items that are stored in a reference snapshot inside a filesystem scanner. The method further includes generating differences between the new states and the last known states of the set of items as item changes and utilizing information provided by the item changes to translate the item changes into synchronization events for execution on the opposing file system. A method of handling failed synchronization events by a synchronization component of the cloud-based platform by collapsing a subsequent event with the failed synchronization event is also disclosed.

Techniques for monitoring local and/or remote file systems by a synchronization component (e.g., client/server) of a cloud-based platform are disclosed. In some embodiments, a method of building synchronization events by a synchronization component (e.g., a synchronization server/client) includes obtaining a set of items that have been changed and their new states and retrieving last known states of the set of items that are stored in a reference snapshot inside a filesystem scanner. The method further includes generating differences between the new states and the last known states of the set of items as item changes and utilizing information provided by the item changes to translate the item changes into synchronization events for execution on the opposing file system. A method of handling failed synchronization events by a synchronization component of the cloud-based platform by collapsing a subsequent event with the failed synchronization event is also disclosed.

Systems and methods are disclosed to implement a delta data collection technique for collecting machine characteristics data from client machines. In embodiments, the collected data is used by a machine assessment service to maintain a virtual representation of the client machine for assessments. To initialize the collection process, the client uploads an initial copy of the data in full. Subsequently, the client determines periodic deltas between a current baseline of the data and a last reported baseline, and the deltas are uploaded as patches. The machine assessment service then applies these patches to update the virtual representation of the client machine. In embodiments, to facilitate the generation or uploading of the patches, the client may generate the baselines in a different encoding format as used by the data. For example, baselines in the new encoding format may be more easily compared and manipulated during the patch generation process.

Systems and methods are disclosed to implement a delta data collection technique for collecting machine characteristics data from client machines. In embodiments, the collected data is used by a machine assessment service to maintain a virtual representation of the client machine for assessments. To initialize the collection process, the client uploads an initial copy of the data in full. Subsequently, the client determines periodic deltas between a current baseline of the data and a last reported baseline, and the deltas are uploaded as patches. The machine assessment service then applies these patches to update the virtual representation of the client machine. In embodiments, to facilitate the generation or uploading of the patches, the client may generate the baselines in a different encoding format as used by the data. For example, baselines in the new encoding format may be more easily compared and manipulated during the patch generation process.

Techniques for managing a file system involve in response to receiving, at a first backup device of the file system, a request for replicating data of the file system from the first backup device to a second backup device of the file system, determining a synchronization state between the first backup device and the file system, the second backup device being a backup device located downstream of the first backup device; creating, based on the synchronization state, a target snapshot associated with the file system; and causing the data to be replicated from the first backup device to the second backup device based on the target snapshot. Therefore, the data backup flexibility and accuracy of a file system can be significantly improved and therefore the reliability of the whole system may be enhanced.

Techniques for managing a file system involve in response to receiving, at a first backup device of the file system, a request for replicating data of the file system from the first backup device to a second backup device of the file system, determining a synchronization state between the first backup device and the file system, the second backup device being a backup device located downstream of the first backup device; creating, based on the synchronization state, a target snapshot associated with the file system; and causing the data to be replicated from the first backup device to the second backup device based on the target snapshot. Therefore, the data backup flexibility and accuracy of a file system can be significantly improved and therefore the reliability of the whole system may be enhanced.