There is provided a method for managing a solid state storage system with hybrid storage technologies. The method includes monitoring one or more storage request streams to identify operating mode characteristics therein from among a set of possible operating mode characteristics. The set of possible operating mode characteristics correspond to a set of available operating modes of the hybrid storage technologies. The method further includes identifying a current operating mode from among the set of available operating modes responsive to the identified operating mode characteristics. The method also includes predicting a likely future operating mode responsive to variations in workload requirements to generate at least one future operating mode prediction. The method additionally includes controlling at least one of data placement, wear leveling, and garbage collection, responsive to the at least one future operating mode prediction.

In some examples, a system detects recovery, from an unavailable state, of a communication link between a first storage system that includes a first storage volume and a second storage system that includes a second storage volume that is to be a synchronized version of the first storage volume, where while the communication link is in the unavailable state the second storage volume is in an offline state and the first storage volume is in an online state. In response to detecting the recovery of the communication link, the system sends a first tracking metadata for the first storage volume from the first storage system to the second storage system, and in response to receipt of the first tracking metadata at the second storage system that maintains a second tracking metadata for the second storage volume, the system transitions the second storage volume from the offline state to a controlled online state, and initiates a synchronization process to synchronize the second storage volume with the first storage volume.

A system and method for offset protection data in a RAID array. A computer system comprises client computers and data storage arrays coupled to one another via a network. A data storage array utilizes solid-state drives and Flash memory cells for data storage. A storage controller within a data storage array is configured to store user data in a first page of a first storage device of the plurality of storage devices; generate intra-device protection data corresponding to the user data, and store the intra-device protection data at a first offset within the first page. The controller is further configured to generate inter-device protection data corresponding to the first page, and store the inter-device protection data at a second offset within a second page in a second storage device of the plurality of storage devices, wherein the first offset is different from the second offset.

A method for rebuilding data, comprising: obtaining, from a metadata node, a source file data layout for a source file and a target file data layout for a target file, wherein the source file is associated with a degraded mapped RAID group and the target file is associated with a new mapped RAID group; generating, by the client application node, a plurality of input/output (I/O) requests to read a portion of the data associated with the source file using the source file data layout; obtaining, in response to the plurality of I/O requests, the portion of the data associated with the source file; rebuilding a second portion of the data associated with source file using the portion of the data; and initiating, storage of at least the second portion of the data associated with the source file in the storage pool using the target file data layout.

Methods and systems are provided for rapid failure recovery for a distributed storage system for failures by one or more nodes.

Methods and systems for monitoring performance in a distributed storage system described. One example method includes identifying requests sent by clients to the distributed storage system, each request including request parameter values for request parameters; generating probe requests based on the identified requests, the probe requests including probe request parameter values for probe request parameter values, representing a statistical sample of the request parameters included in the identified requests; sending the generated probe requests to the distributed storage system over a network, wherein the distributed storage system is configured to perform preparations for servicing each probe request in response to receiving the probe request; receiving responses to the probe requests from the distributed storage system, and outputting at least one performance metric value measuring a current performance state of the distributed storage system based on the received responses.

A method for synchronous replication of stream data includes receiving a stream of data blocks for storage at a first storage location associated with a first geographical region and at a second storage location associated with a second geographical region. The method also includes synchronously writing the stream of data blocks to the first storage location and to the second storage location. While synchronously writing the stream of data blocks, the method includes determining an unrecoverable failure at the second storage location. The method also includes determining a failure point in the writing of the stream of data blocks that demarcates data blocks that were successfully written and not successfully written to the second storage location. The method also includes synchronously writing, starting at the failure point, the stream of data blocks to the first storage location and to a third storage location associated with a third geographical region.

Techniques are described herein for predicting disk drive failure using a machine learning model. The framework involves receiving disk drive sensor attributes as training data, preprocessing the training data to select a set of enhanced feature sequences, and using the enhanced feature sequences to train a machine learning model to predict disk drive failures from disk drive sensor monitoring data. Prior to the training phase, the RNN LSTM model is tuned using a set of predefined hyper-parameters. The preprocessing, which is performed during the training and evaluation phase as well as later during the prediction phase, involves using predefined values for a set of parameters to generate the set of enhanced sequences from raw sensor reading. The enhanced feature sequences are generated to maintain a desired healthy/failed disk ratio, and only use samples leading up to a last-valid-time sample in order to honor a pre-specified heads-up-period alert requirement.

Techniques are provided for enforcing policies at a sub-logical unit number (LUN) granularity, such as at a virtual disk or virtual machine granularity. A block range of a virtual disk of a virtual machine stored within a LUN is identified. A quality of service policy object is assigned to the block range to create a quality of service workload object. A target block range targeted by an operation is identified. A quality of service policy of the quality of service policy object is enforced upon the operation using the quality of service workload object based upon the target block range being within the block range of the virtual disk.

Technologies for providing shared memory for accelerator sleds includes an accelerator sled to receive, with a memory controller, a memory access request from an accelerator device to access a region of memory. The request is to identify the region of memory with a logical address. Additionally, the accelerator sled is to determine from a map of logical addresses and associated physical address, the physical address associated with the region of memory. In addition, the accelerator sled is to route the memory access request to a memory device associated with the determined physical address.