G06F11/3034

Method, Apparatus, and Device for Updating Hard Disk Prediction Model, and Medium
20230004824 · 2023-01-05 ·

A method, apparatus, and device for updating a hard disk prediction model, and a storage medium. The method comprises: acquiring first sample data used to update a hard disk prediction model, and determining, according to the first sample data, a target decision tree requiring updating in the hard disk prediction model; selecting second sample data from the first sample data according to a preset selection rule; determining, according to the second sample data, a target leaf node requiring updating in the target decision tree; and splitting the target leaf node according to a splitting rule of the hard disk prediction model so as to update the target decision tree. The entire updating process is simple, and a new hard disk prediction model need not be re-established, thereby reducing the time used for updating. Moreover, the accuracy of hard disk fault prediction is improved, and user requirements are better met.

DISK USAGE GROWTH PREDICTION SYSTEM

Certain embodiments described herein relate to an improved disk usage growth prediction system. In some embodiments, one or more components in an information management system can determine usage status data of a given storage device, perform a validation check on the usage status data using multiple prediction models, compare validation results of the multiple prediction models to identify the best performing prediction model, generate a disk usage growth prediction using the identified prediction model, and adjust the available space of the storage device according to the disk usage growth prediction.

Failure Prediction Using Informational Logs and Golden Signals

Embodiments relate to a computer platform to support processing of informational logs and corresponding performance data to detect and mitigate occurrence of anomalous behavior. Metrics are extracted from the informational logs and correlated with performance data, and in an exemplary embodiment golden signal metrics. A window or block of the logs is classified as potential candidates or indicators of anomalous behavior, which in an embodiment is indicative of potential failure or service outage. A control signal is dynamically issued to an operatively coupled device associated with the window or block of logs. The control signal is configured to selectively control a state of a physical device or process controlled by software, with the control directed at mitigating or eliminating the effect(s) of the anomalous behavior.

Configurable NVM set to tradeoff between performance and user space
11567862 · 2023-01-31 · ·

An embodiment of an electronic apparatus may include one or more substrates, and logic coupled to the one or more substrates, the logic to determine a set of requirements for a persistent storage media based on input from an agent, dedicate one or more banks of the persistent storage media to the agent based on the set of requirements, and configure at least one of the dedicated one or more banks of the persistent storage media at a program mode width which is narrower than a native maximum program mode width for the persistent storage media. Other embodiments are disclosed and claimed.

Balancing Data Transfer Amongst Paths Between A Host and A Storage System
20230236767 · 2023-07-27 ·

Managing input/output (‘I/O’) queues in a data storage system, including: receiving, by a host that is coupled to a plurality of storage devices via a storage network, a plurality of I/O operations to be serviced by a target storage device; determining, for each of a plurality of paths between the host and the target storage device, a data transfer maximum associated with the path; determining, for one or more of the plurality of paths, a cumulative amount of data to be transferred by I/O operations pending on the path; and selecting a target path for transmitting one or more of the plurality of I/O operations to the target storage device in dependence upon the cumulative amount of data to be transferred by I/O operations pending on the path and the data transfer maximum associated with the path.

Low-latency direct cloud access with file system hierarchies and semantics

Techniques described herein relate to systems and methods of data storage, and more particularly to providing layering of file system functionality on an object interface. In certain embodiments, file system functionality may be layered on cloud object interfaces to provide cloud-based storage while allowing for functionality expected from a legacy applications. For instance, POSIX interfaces and semantics may be layered on cloud-based storage, while providing access to data in a manner consistent with file-based access with data organization in name hierarchies. Various embodiments also may provide for memory mapping of data so that memory map changes are reflected in persistent storage while ensuring consistency between memory map changes and writes. For example, by transforming a ZFS file system disk-based storage into ZFS cloud-based storage, the ZFS file system gains the elastic nature of cloud storage.

System and method for identifying SSDs with lowest tail latencies

A storage device is disclosed. The storage device may include storage to store data and a controller to manage reading data from and writing data to the storage. The controller may also include a receiver to receive a plurality of requests, information determination logic to determine information about the plurality of requests, storage for the information about a plurality of requests, and sharing logic to share the information with a management controller.

Data flow management in a heterogeneous memory device using a thermal profile

A computer-implemented method, a computer program product, and a computer system for data flow management in a heterogeneous memory device. A media controller redirects traffic from first non-volatile memory (NVM) to second NVM, in response to an instantaneous temperature of the first NVM reaches a first predetermined temperature at which redirecting the traffic is started. The media controller throttles to reduce the traffic to the second NVM, in response to determining that the instantaneous temperature is higher than a second predetermined temperature at which throttling is started. The media controller redirects the traffic back to the first NVM, in response to determining that the instantaneous temperature is not higher than the second predetermined temperature and lower than a third predetermined temperature at which throttling is ended. The first NVM is thermally sensitive, while the second NVM is thermally tolerant.

Adaptive, proactive raid rebuild

A data storage system includes a plurality of storage devices organized as a redundant array of inexpensive disks (RAID) storage array and a RAID controller. The RAID controller monitors the plurality of storage devices in the RAID storage array. The RAID controller also detects that a host read request of a host has a latency exceeding a latency threshold. Based on the monitoring, the RAID controller determines whether a proactive rebuild of a data requested by the host read request in absence of a data error would likely be beneficial to performance. Based on determining that a proactive rebuild of the data requested by the host read request would likely be beneficial to performance, the RAID controller initiates the proactive rebuild of the data and sends the requested data to the host.

Pause and resume in database system workload capture and replay
11709752 · 2023-07-25 · ·

Methods, systems, and computer-readable storage media for receiving a capture file, the capture file holding data representative of a workload executed in a source database system, processing the capture file to provide a replay file, the replay file being in a format that is executable by a replayer to replay the workload in a target database system, the workload including a set of requests represented within the replay file, providing a set of tags associated with the replay file, the set of tags including one or more tags, each tag associated with a request in the set of requests, and during replay of the workload in the target database system: pausing replay of the workload in response to a tag, executing a request associated with the tag, providing replay results specific to the request, and selectively resuming replay of the workload in the target database system.