An inter-volume copy time is to be accurately predicted. An operation management system is configured to perform operation management on a storage device including a plurality of resources and a plurality of volumes. In the storage device, IO processing and copy processing are performed between a plurality of volume groups in which the plurality of volumes are collected. The operation management system includes a processor, and the processor is configured to predict an inter-pool copy speed between the plurality of volume groups belonging to a same resource pool in the storage device, and predict an inter-volume copy time based on the predicted inter-pool copy speed.

Staging data on a storage element integrating fast durable storage and bulk durable storage, including: receiving, at a storage element integrating fast durable storage and bulk durable storage, a data storage operation from a host computer; storing data corresponding to the data storage operation within fast durable storage in accordance with a first data resiliency technique; and responsive to detecting a condition for transferring data between fast durable storage and bulk durable storage, transferring the data from fast durable storage to bulk durable storage in accordance with a second data resiliency technique.

Various implementations described herein are directed to technologies for providing error detection for a disk drive of a digital video recorder (DVR). Access data is measured according to a degree of usage of a disk drive of a DVR. The access data is stored. The stored access data is analyzed to detect performance degradation of the disk drive.

According to some aspects, a database system comprising a processor configured to execute a plurality of system components is provided. The plurality of system components may include an interface component configured to receive a write commit command and provide a write commit confirmation, a snapshot component configured to generate a plurality of snapshots of data stored in a data storage node of a plurality of data storage nodes and identify a committed snapshot representative of data that has been replicated on a majority of the plurality of data storage nodes, and a command processing component configured to modify a data element based on the write commit command, determine whether the majority of the plurality of storage nodes have replicated the modification using the committed snapshot, and generate the write commit confirmation responsive to a determination that the majority of the plurality of data storage nodes have replicated the modification.

Methods, apparatus, systems and articles of manufacture to improve performance data collection are disclosed. An example apparatus includes a performance data comparator of a source node to collect the performance data of an application of the source node from the host fabric interface at a polling frequency; an interface to transmit a write back instruction to the host fabric interface, the write back instruction to cause data to be written to a memory address location of memory of the source node to trigger a wake up mode; and a frequency selector to: start the polling frequency to a first polling frequency for a sleep mode; and increase the polling frequency to a second polling frequency in response to the data in the memory address location identifying the wake mode.

Differential health-check systems and accompanying methods provide health-checking and reporting of one or more information management systems in reference to a first time period before and a second time period after a triggering event. A triggering event may be an upgrade of at least part of the information management system, or a restore operation completed in the information management system for example following a disaster, or any number of other events, etc. The health-checking and reporting may comprise a comparison of one or more performance metrics of one or more components and/or operations of the information management system during the first and second time periods.

A system that provides services to clients may receive and service requests, various ones of which may require different amounts of work. The system may determine whether it is operating in an overloaded or underloaded state based on a current work throughput rate, a target work throughput rate, a maximum request rate, or an actual request rate, and may dynamically adjust the maximum request rate in response. For example, if the maximum request rate is being exceeded, the maximum request rate may be raised or lowered, dependent on the current work throughput rate. If the target or committed work throughput rate is being exceeded, but the maximum request rate is not being exceeded, a lower maximum request rate may be proposed. Adjustments to the maximum request rate may be made using multiple incremental adjustments. Service request tokens may be added to a leaky token bucket at the maximum request rate.

Embodiments of the present disclosure relate to throttling processing threads of a storage device. One or more input/output (I/O) workloads of a storage device can be monitored. One or more resources consumed by each thread of each storage device component to process each operation included in a workload can be analyzed. Based on the analysis, consumption of each resource consumed by each thread can be controlled.

Multiple data paths may be available to a data management system for transferring data between a primary storage device and a secondary storage device. The data management system may be able to gain operational advantages by performing load balancing across the multiple data paths. The system may use application layer characteristics of the data for transferring from a primary storage to a backup storage during data backup operation, and correspondingly from a secondary or backup storage system to a primary storage system during restoration.

A method of optimizing the scheduling of storage resource for a server used in cloud computing obtains a first input/output operations per seconds (IOPS) value of a virtual disk in an instance. A warning message is generated when the first IOPS value is larger than a predefined threshold value, which represents an overloaded state of the virtual disk. An predicted IOPS value is obtained and the predicted IOPS value is set as the maximum IOPS value for limiting the IOPS value of the virtual disk, thus other virtual disks are not affected by a virtual disk being overloaded, and storing efficiency of the server is improved. A server and a computer readable storage medium applying the method are also disclosed.