Abstract: An example method of restoring a database includes obtaining information about backup data of a database from a source storage separate from a compute infrastructure. The information includes a list of data blocks of a file, transferring the data blocks on the list from the source storage to a local storage on the compute infrastructure, and tracking which data blocks of the file have been transferred from the source storage to the local storage concurrently when transferring the data blocks.

Abstract: Methods and systems for improving data back-up, recovery, and search across different cloud-based applications, services, and platforms are described. A data management and storage system may direct compute and storage resources within a customer's cloud-based data storage account to back-up and restore data while the customer retains full control of their data. The data management and storage system may direct the compute and storage resources within the customer's cloud-based data storage account to generate and store secondary layers that are used for generating search indexes, to generate and store shared space layers and user specific layers to facilitate the deduplication of email attachments and text blocks, to perform a controlled restoration of email snapshots such that sensitive information (e.g., restricted keywords) located within stored snapshots remains protected, and to detect and preserve emails that were received or transmitted and then deleted between two consecutive snapshots.

Abstract: Techniques for proactive risk reduction for data management are disclosed. In some embodiments, a computer system performs operations comprising: identifying a risk to one or more physical machines of a data management system based on risk event data indicating one or more risk events associated with a geographic area and a geographical location of the one or more physical machines of the data management system; generating a remediation recommendation comprising a data management action configured to remedy the identified risk; causing the remediation recommendation for the identified risk to be displayed along with a selectable user interface element; receiving an indication of a request to perform the data management action based on a user selection of the selectable user interface element; and performing the data management action based on the receiving of the indication of the request to perform the data management action of the remediation recommendation.

Abstract: A data management and storage (DMS) cluster of peer DMS nodes manages migration of an application between a primary compute infrastructure and a secondary compute infrastructure. The secondary compute infrastructure may be a failover environment for the primary compute infrastructure. Primary snapshots of virtual machines of the application in the primary compute infrastructure are generated, and provided to the secondary compute infrastructure. During a failover, the primary snapshots are deployed in the secondary compute infrastructure as virtual machines. Secondary snapshots of the virtual machines are generated, where the secondary snapshots are incremental snapshots of the primary snapshots. In failback, the secondary snapshots are provided to the primary compute infrastructure, where they are combined with the primary snapshots into construct a current state of the application, and the application is deployed in the current state by deploying virtual machines on the primary compute infrastructure.

Abstract: Example embodiments relate generally to systems and methods for continuous data protection (CDP) and more specifically to an input and output (I/O) filtering framework and log management system to seek a near-zero recovery point objective (RPO).

Abstract: Example embodiments relate generally to systems and methods for continuous data protection (CDP) and more specifically to an input and output (I/O) filtering framework and log management system to seek a near-zero recovery point objective (RPO).

Abstract: A data management and storage (DMS) cluster of peer DMS nodes manages data of an application distributed across a set of machines of a compute infrastructure. A DMS node associates a set of machines with the application, and generates data fetch jobs for the set of machines for execution by multiple peer DMS nodes. The DMS node determining whether each of the data fetch jobs for the set of machines is ready for execution by the peer DMS nodes. In response to determining that each of the data fetch jobs is ready for execution, the peer DMS nodes execute the data fetch jobs to generate snapshots of the set of machines. The snapshots may be full or incremental snapshots, and collectively form a snapshot of the application.

Abstract: An automated system monitors network traffic to determine dependencies between different machines. These dependencies can be used to automatically develop a recovery plan for the machines, for example restoring servers in a certain order. This approach can also automatically adjust the recovery plan for changes in system configuration, for example as different servers come online or are taken offline or change their roles.

Abstract: Methods and systems for automatically upgrading or synchronizing a remote data management agent running on a remote host machine (e.g., a hardware server) to a particular version that is in-sync with a corresponding version used by a cluster of data storage nodes controlling the remote data management agent are described. The remote agent may be initially installed on the remote host and subsequent updates to the remote agent may be performed using the remote agent itself without requiring intervention by the remote host. The remote agent may comprise a backup agent and a bootstrap agent that are each exposed in different network ports or associated with different port numbers or networking addresses. The backup agent may perform data backup related tasks for backing up files stored on the remote host and the bootstrap agent may perform upgrade related tasks for upgrading the backup agent.

Abstract: Systems and methods to manage software vulnerabilities are described. The system retrieves a snapshot image of a production machine from a database. The snapshot image is associated with a recovery point identifier. The recovery point identifier identifies a first recovery point from multiple recovery points respectively corresponding to a plurality of snapshot images of the production machine. The snapshot image includes a first virtual machine that includes software information. The system processes the software information to identify first patch information associated with a first software module. Finally, the system pushes patch information to the production machine based on the processing of the software information.

Abstract: In some examples, a computer-implemented method of providing a calendar view interface in a client device includes receiving a request for a calendar view interface from the client device, determining a period of time to be presented in the calendar view interface, generating a calendar view interface for the period of time including an indicator for each day of the time period, retrieving snapshot information for the period of time, and generating a snapshot indicator for each day within the time period based on the snapshot information.

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: 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 data management and storage (DMS) cluster of peer DMS nodes manages data of a compute infrastructure by generating snapshots of partitions of a fileset of the compute infrastructure and providing a passthrough for storing the snapshots in a data storage separate from the DMS cluster, such as a cloud computing system. In one approach, the DMS nodes determine partitions of a fileset using fileset metadata, generates snapshots of the partitions, and stores the snapshots in the data storage. Each DMS node may include a local storage which is used to facilitate creation of a snapshot of a partition. The snapshot may be removed from the local storage after being sent to the data storage. Rather than storing the snapshot, the DMS cluster stores fileset metadata that is referenced to retrieve the snapshot from the data storage. The snapshot is deployed to retrieve a file stored in the partition.

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: Systems and methods to utilize a tablespace to export to a native database recovery environment are described. The system receives file information and script information at a source host that operates in a native database recovery environment. The file information and the script information are received from a backup host that utilizes foreign snapshot files and foreign incremental files for storing the file information. The file information includes native snapshot files and native incremental files. The script information includes one or more scripts that execute, at the source host, to perform operations comprising: mounting the directories; opening an auxiliary database; restoring a tablespace in the auxiliary database; recovering the tablespace in the auxiliary database based on the native incremental files; exporting the tablespace metadata information from the auxiliary database; recovering the tablespace in the database based on the tablespace metadata information; and unmounting the directories.

Abstract: Example embodiments relate generally to systems and methods for continuous data protection (CDP) and more specifically to an input and output (I/O) filtering framework and log management system to seek a near-zero recovery point objective (RPO).

Abstract: A streaming distributed decentralized database task system can perform multiple tasks of parallel jobs on clusters of nodes without overloading the clusters' computational resources, such as disk, memory, processors, and network bandwidth. A cluster master can manage a job and add items to node queues. A node manager accepts or rejects queue items based on streaming task limits that are applied at the node level.

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.