Abstract:
With a forever incremental snapshot configuration and a typical caching policy (e.g., least recently used), a storage appliance may evict stable data blocks of an older snapshot, perhaps unchanged data blocks of the snapshot baseline. If stable data blocks have been evicted, restore of a recent snapshot will suffer the time penalty of downloading the stable blocks for restoring the recent snapshot. Creating synthetic baseline snapshots and refreshing eviction data of stable data blocks can avoid eviction of stable data blocks and reduce the risk of violating a recovery time objective.
Abstract:
Techniques are provided for incrementally restoring a virtual machine hosted by a computing environment. In response to receiving an indication that the virtual machine is to be incrementally restored, a snapshot of the virtual machine may be created while the virtual machine is shut down into an off state. The snapshot is transmitted to a storage environment as a common snapshot. The snapshot and the common snapshot are common snapshots comprising a same representation of the virtual machine. The common snapshot and a prior snapshot of the virtual machine are evaluated to identify a data difference of the virtual machine between the common snapshot and the prior snapshot. An incremental restore is performed of the virtual machine by transmitting the data difference from the storage environment to the computing environment to restore the virtual machine to a state represented by the prior snapshot.
Abstract:
A storage appliance arranges snapshot data and snapshot metadata into different structures, and arranges the snapshot metadata to facilitate efficient snapshot manipulation, which may be for snapshot management or snapshot restore. The storage appliance receives snapshots according to a forever incremental configuration and arranges snapshot metadata into different types of records. The storage appliance stores these records in key-value stores maintained for each defined data collection (e.g., volume). The storage appliance arranges the snapshot metadata into records for inode information, records for directory information, and records that map source descriptors of data blocks to snapshot file descriptors. The storage appliance uses a locally generated snapshot identifier as a key prefix for the records to conform to a sort constrain of the key-value store, which allows the efficiency of the key-value store to be leveraged. The snapshot metadata arrangement facilitates efficient snapshot restore, file restore, and snapshot reclamation.
Abstract:
A technique restores a file system of a storage input/output (I/O) stack to a deterministic point-in-time state in the event of failure (loss) of non-volatile random access memory (NVRAM) of a node. The technique enables restoration of the file system to a safepoint stored on storage devices, such solid state drives (SSD), of the node with minimum data and metadata loss. The safepoint is a point-in-time during execution of I/O requests (e.g., write operations) at which data and related metadata of the write operations prior to the point-in-time are safely persisted on SSD such that the metadata relating to an image of the file system on SSD (on-disk) is consistent and complete. Upon reboot after NVRAM loss, the technique identifies (i) the most recent safepoint, as well as (ii) the inflight writes that were persistently stored on disk after the most recent safepoint. The data and metadata of those inflight writes are then deleted to place the on-disk file system to its state at the most recent safepoint.
Abstract:
A N-way merge technique efficiently updates metadata in accordance with a N-way merge operation managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The metadata is embodied as mappings from logical block addresses (LBAs) of a logical unit (LUN) accessible by a host to durable extent keys, and is organized as a multi-level dense tree. The mappings are organized such that a higher level of the dense tree contains more recent mappings than a next lower level, i.e., the level immediately below. The N-way merge operation is an efficient (i.e., optimized) way of updating the volume metadata mappings of the dense tree by merging the mapping content of all three levels in a single iteration, as opposed to merging the content of the first level with the content of the second level in a first iteration of a two-way merge operation and then merging the results of the first iteration with the content of the third level in a second iteration of the operation.
Abstract:
With a forever incremental snapshot configuration and a typical caching policy (e.g., least recently used), a storage appliance may evict stable data blocks of an older snapshot, perhaps unchanged data blocks of the snapshot baseline. If stable data blocks have been evicted, restore of a recent snapshot will suffer the time penalty of downloading the stable blocks for restoring the recent snapshot. Creating synthetic baseline snapshots and refreshing eviction data of stable data blocks can avoid eviction of stable data blocks and reduce the risk of violating a recovery time objective.
Abstract:
A N-way merge technique efficiently updates metadata in accordance with a N-way merge operation managed by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The metadata is embodied as mappings from logical block addresses (LBAs) of a logical unit (LUN) accessible by a host to durable extent keys, and is organized as a multi-level dense tree. The mappings are organized such that a higher level of the dense tree contains more recent mappings than a next lower level, i.e., the level immediately below. The N-way merge operation is an efficient (i.e., optimized) way of updating the volume metadata mappings of the dense tree by merging the mapping content of all three levels in a single iteration, as opposed to merging the content of the first level with the content of the second level in a first iteration of a two-way merge operation and then merging the results of the first iteration with the content of the third level in a second iteration of the operation.
Abstract:
In one embodiment, as new blocks of data are written to storage devices of a storage system, fingerprints are generated for those new blocks and inserted as entries into a top level (L0) of a dense tree data structure. When L0 is filled, the contents from L0 may be merged with level 1 (L1). After the initial merge, new fingerprints are added to L0 until L0 fills up again, which triggers a new merge. Duplicate fingerprints in L0 and L1 are identified which, in turn, indicates duplicate data blocks. A post-processing deduplication operation is then performed to remove duplicate data blocks corresponding to the duplicate fingerprints. In a different embodiment, as new fingerprint entries are loaded into L0, those new fingerprints may be compared with existing fingerprints loaded into L0 and/or other levels to facilitate inline deduplication to identify duplicate fingerprints and subsequently perform the deduplication operation.
Abstract:
A technique preserves efficiency for replication of data between a source node of a source cluster (“source”) and a destination node of a destination cluster (“destination”) of a clustered network. Replication in the clustered network may be effected by leveraging global in-line deduplication at the source to identify and avoid copying duplicate data from the source to the destination. To ensure that the copy of the data on the destination is synchronized with the data received at the source, the source creates a snapshot of the data for use as a baseline copy at the destination. Thereafter, new data received at the source that differs from the baseline snapshot are transmitted and copied to the destination. In addition, the source and destination nodes negotiate to establish a mapping of name-to-data when transferring data (i.e., an extent) between the clusters. Illustratively, the name is an extent key for the extent, such that the negotiated mapping established by the source and destination is based on the extent key associated with the extent.
Abstract:
A technique improves efficiency of a copy-on-write (COW) operation used to create a snapshot and/or clone by a volume layer of a storage input/output (I/O) stack executing on one or more nodes of a cluster. The snapshot/clone may be represented as an independent volume, and embodied as a respective read-only copy (snapshot) or read-write copy (clone) of a parent volume. Volume metadata managed by the volume layer is organized as one or more multi-level dense tree metadata structures, wherein each level of the dense tree includes volume metadata entries for storing the metadata. The volume metadata entries may be organized as metadata pages having associated metadata page keys. Each metadata page is rendered distinct or “unique” from other metadata pages in an extent store layer of the storage I/O stack through the use of a multi-component uniqifier contained in a header of each metadata page. To improve the efficiency of the COW operation, the technique allows the use of reference count operations on the metadata page keys of the “unique” metadata pages so as to allow sharing of the metadata pages individually between the parent volume and the snapshot/clone.