Abstract: A data management system may support techniques for immutable storage of snapshot data entities, which may each include data corresponding to one or more snapshots, in a cloud environment. The data management system may determine respective retention periods and respective immutability periods for the snapshot data entities. The data management system may extend the respective immutability period for a first snapshot data entity based on the respective retention period for the first snapshot data entity being greater than or equal to a threshold duration. Additionally or alternatively, the data management system may maintain (refrain from extending) the respective immutability period for a second snapshot data entity based at least in part on the respective retention period for the second snapshot data entity being less than the threshold duration.

Abstract: Methods, systems, and devices for data management are described. A data management system may configure backup and recovery resources for tenant of the data management system. The data management system may receive an indication to create a set of subtenants within the resources configured for the tenant. The data management system may assign a first subset of resources configured for the tenant, and the first subset may be different from a second subset configured for a second subtenant. The data management system may activate a first backup procedure for the first subtenant. The first backup procedure may be configured to backup a first data source associated with the first subtenant of the tenant using the first subset of the set of backup and recovery resources, and the first backup procedure may be separate from a second backup procedure for a second data source associated with the second subtenant.

Abstract: Methods, systems, and devices for data management are described. A data enrichment service supported by a data management system (DMS) may receive, from a first application in a destination computing environment of the DMS, a set of enrichment definitions for metadata synchronization between the first application and a second application in a source computing environment of the DMS. A change data capture (CDC) service supported by the DMS may generate a set of data records that correspond to metadata changes associated with the second application. The data enrichment service may transform the set of data records by using data enrichment components to modify the set of data records according to the set of enrichment definitions provided by the first application. The data enrichment components may be dynamically partitioned into groups that execute in parallel. The second application may push the enriched data records to the first application in real-time.

Abstract: A data management system (DMS) may use a staggered full snapshot rollout approach to obtain full snapshots of multiple computing objects. The DMS may identify that a quantity of the multiple objects scheduled for full backups by the DMS exceeds a threshold quantity. The DMS may initiate, at a first time, and based on the quantity of objects exceeding the threshold quantity, a first set of full snapshots corresponding to a first subset of objects included in the multiple objects. The DMS may initiate, at a second time subsequent to the first time, a second set of full snapshots corresponding to a second subset of objects included in the multiple objects. The second subset of objects may be different than the first subset of objects. The DMS may continue to obtain full snapshots of respective subsets of the multiple objects until all of the scheduled full snapshots are obtained.

Abstract: Methods, systems, and devices for data management are described. A backup cluster may store incremental or base snapshots of computing objects. When a snapshot expires, a data management system (DMS) that manages the backup cluster may in some cases merge or consolidate the expired snapshot with a non-expired snapshot to create a new merged snapshot. In some cases, however, consolidation may be deferred until a chain of multiple expired snapshots satisfies one or more heuristic thresholds, to conserve resources. Example heuristic thresholds may be a length of the chain, an amount of space reclaimable by consolidating the snapshots, an age of the expired snapshots in the chain of incremental snapshots, or an amount of free space on the backup cluster.

Abstract: Methods, systems, and devices for data management are described. A data management system (DMS) may support backup and recovery of a filesystem. The DMS may, as part of the backup, obtain a snapshot of the filesystem. The DMS may mount the snapshot within a user space of a node of the DMS. The user space may be isolated from other processes that execute on the node of the DMS. The DMS may generate, within the user space based on the mounted snapshot, index files that index the filesystem. In response to a subsequent request to access one or more files, the DMS may retrieve the one or more files from the snapshot mounted in the user space based on the index files.

Abstract: A virtual machine management system may support backup and recovery for virtual machines that support various applications. The virtual machine management system may process a backup snapshot of the virtual machine to identify security risks in the virtual machine. A cloud platform may communicate with the virtual machine management system to support backup processing. The cloud platform may identify security configuration information and transmit such information and transmit indications of the information to the virtual machine management system. The cloud platform may receive an indication of one or more security risks and generate notifications that indicate the security risks.

Abstract: In some examples, a method of performing a backup of a group of relational databases comprises identifying database files to be fetched in the group of relational databases; grouping the identified database files into batches; based on configuration parameters of the identified database files, identifying, among the batches, a sub-set of batches of database files that are eligible to be fetched in parallel for the backup; configuring a single fetch call to a call stack to fetch the sub-set of eligible batches; and determining a push or pull model for the configured single fetch call based at least in part on feedback from a most resource-constrained element in the call stack.

Abstract: Techniques for data management are described. A monotonically increasing time source that indicates an elapsed time since a reference event may be activated. Multiple snapshots of a computing object may be generated in accordance with a schedule for backing up the computing object, where the schedule may include a retention duration for retaining snapshots. Based on generating the snapshots, timestamps for the snapshots may be stored, where the timestamps may indicate respective values of the monotonically increasing time source. As part of an expiration job, a reference value of the monotonically increasing time source may be identified based on the retention duration and a current value indicated by the monotonically increasing time source. Also, a snapshot of the snapshots may be expired based on a timestamp of the snapshot corresponding to a value of the monotonically increasing time source that is less than the reference value.

Abstract: Methods, systems, and devices for data management are described. A first data source may be identified to move from a source cloud deployment (that operates in accordance with a first release cadence for updating database schema) to a destination cloud deployment (that operates in accordance with second, different release cadence for updating database schema). The first source database is then migrated from the source cloud deployment to an intermediate cloud deployment hosted on the source cloud deployments that allows the schema of the first data source to remain unchanged for a duration of time that the first data source is hosted on the intermediate cloud deployment. The database schema associated with the first data source is then updated to an updated (most recent) database schema in accordance with the second release cadence of the destination cloud deployment, and migrated from the intermediate cloud deployment to the destination cloud deployment.

Abstract: Methods, systems, and devices for data management are described. A data management system (DMS) may obtain metadata associated with a snapshot stored by the DMS and including information associated with data paths in the snapshot. The DMS may scan an index registry for identifiers of the data paths to determine whether the index registry includes namespace and hierarchical index information that map the data paths to path identifiers and to descendent data paths within the snapshot, respectively. The DMS may generate term and count index information based on the metadata. The term and count index information may map terms to data paths that include the terms and numerical values associated with the terms, respectively. The DMS may store, in the index registry, the term and count index information with an identifier of a corresponding index group. The namespace and hierarchical index information may be common to multiple index groups.

Abstract: Methods, systems, and devices for data management are described. A data management system (DMS) may receive an indication of a storage configuration for an object storage location within a cloud environment. The DMS may generate a snapshot of a computing system in accordance with a backup policy associated with the computing system. The DMS may cause one or more data objects corresponding to the snapshot to be stored in the object storage location within the cloud environment in accordance with the storage configuration. The DMS may apply immutable object locks to the one or more data objects within the object storage location. The DMS may execute, in accordance with the backup policy associated with the computing system, one or more jobs that cause the respective immutable object locks for the one or more data objects to be extended one or more times during a retention period for the snapshot.

Abstract: During a backup a procedure, a first storage entity may backup a set of database logs from a second storage entity and metadata associated with the set of database logs may be stored in a log deletion table. In accordance with a user configuration of the second storage entity and the backup procedure, a first command to delete one or more database logs of the set from the second storage entity may be transmitted to the second storage entity. The log deletion table may be updated based on a query of second storage entity about whether the one or more database logs were deleted from the second storage entity in response to the first command. Based on the updated log deletion table, a second command may be transmitted to the second storage entity to delete database logs that were not deleted in response to the first command.

Abstract: Methods, systems, and devices for data management are described. A database instance associated with managing data of one or more users may be generated. In the database instance, a table of a database for a user of the one or more users may be generated. The table may be configured to store metadata for managing data of the user and may include a partitioning category. Based on generating the table, a file that indicates a policy for partitioning the table and for retaining partitions in the table may be identified. The policy may be based on a data retention policy associated with the data of the user. Based on identifying the file, partitions for the table may be generated in accordance with the partitioning category and the file, and based on generating the partitions, one or more partitions of the partitions may be deleted in accordance with the file.

Abstract: An in-place data recovery method and system include receiving a user request to restore a virtual machine to a version corresponding to a first point in time, identifying a first snapshot of the virtual machine based on the user request, generating a second snapshot of the virtual machine, identifying a second data block in the second snapshot that includes modified data derived from data content of a first data block in the first snapshot, generating reverse incremental backup data including the first data block, and restoring the virtual machine in-place based on the reverse incremental backup data.

Abstract: A method for transferring virtual machines across hypervisors is described. According to the method, a data management system may interface with a first hypervisor platform and a second hypervisor platform. The data management system may obtain a snapshot of a first virtual machine executing on the first hypervisor platform. The snapshot may include data and metadata associated with the first virtual machine in a first format that is supported by the first hypervisor platform. The data management system may extract the data and the metadata from the snapshot of the first virtual machine and convert the data and the metadata from the first format to a second format that is supported by the second hypervisor platform. The data management system may transfer the data and the metadata in the second format to a second virtual machine executing on the second hypervisor platform.

Abstract: Techniques for database management are described. A database management system may transmit a request for a data management system of a database to provide a set of metadata attributes for structured data within the database, and may receive a set of metadata attributes for the structured data within the database. The data management system may perform a pattern matching procedure to evaluate the set of metadata attributes for the structured data within the database against one or more patterns associated with a data type to determine one or more locations within the database that include structured data of the data type. Based on the pattern matching procedure, the data management system may output an indication that the one or more locations within the database include structured data of the data type.

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: Methods and systems for recovering databases and other applications with reduced downtime using recoverable chains are described. When protecting or backing up a database, an integrated data management and storage system may capture snapshots of the database at a snapshot frequency (e.g., at 15 minute intervals) and acquire database transaction logs that include data changes of the database at a frequency that is greater than the snapshot frequency. The integrated data management and storage system may generate a particular point in time version of the database by identifying a recoverable chain that comprises a combination of one or more database snapshots including the snapshot closest to the recovery point and one or more database transaction logs.

Abstract: In some examples, a cluster comprises peer nodes and a distributed data store implemented across the peer nodes, a method of remote linking of data objects for data transfer between a first node cluster and a second node cluster among the peer nodes, the method comprising: creating a data object group including multiple remote data objects, wherein a plurality of remote data objects in the data object group represent a same first virtual machine and are registrable on at least the first and second node clusters of the peer DMS nodes; creating or identifying remote links to a plurality of the remote data objects in the data object group; designating a member of the data object group as an active member of the group; and assigning a task to the active member to be completed using remote links.