Dell Products Inc.

Changyue Dai

Chi Chen

Hailan Dong

En Shi

An apparatus comprises a processing device configured to detect a request for an updated snapshot schedule for an information technology asset, and to determine a current state of the information technology asset comprising a set of snapshot parameters of a current snapshot schedule and one or more performance metric values. The processing device is also configured to generate, utilizing a reinforcement learning framework, an updated parameter value for at least one of the snapshot parameters based at least in part on the current state. The processing device is further configured to monitor performance of the information technology asset utilizing the updated snapshot schedule comprising the updated parameter value for the at least one snapshot parameter, and to update the reinforcement learning framework based at least in part on a subsequent state of the information technology asset determined while monitoring performance of the information technology asset utilizing the updated snapshot schedule.

Generating parameter values for snapshot schedules utilizing a reinforcement learning framework

Techniques for storage testing involve: acquiring a first state of a storage system including first input/output (IO) load information; taking a first action based on the first state, the first action causing the first IO load information to be changed to second IO load information; updating the first action to be a reserved action for the first state if it is obtained based on the second IO load information that the storage system reaches a preset condition; and obtaining an action combination of a plurality of IO load information changes based on a plurality of reserved actions corresponding to a plurality of states, wherein the plurality of states include the first state. Accordingly, the most effective load combination change mode for the storage system can be found automatically and more accurately, so as to find more vulnerabilities of the storage system, thereby improving the efficiency of storage system testing.

Method and electronic device for storage testing

An apparatus comprises a processing device configured to determine, based on monitoring input/output (IO) operations, an IO activity level and a given IO pattern of a given storage object for a designated period of time, the given storage object being stored on a first storage tier of a storage system. The processing device is also configured to determine a write penalty associated with writing storage objects having the given IO pattern to a second storage tier of the storage system. The processing device is further configured to determine, based on the IO activity level of the given storage object and the determined write penalty, whether to move the given storage object from the first to the second storage tier and to move, responsive to an affirmative movement determination, the given storage object to the second storage tier.

Data movement based on write penalties of input/output patterns associated with storage objects

Techniques for managing disks involve determining performance information of an access pattern of a disk slice based on differences in performance parameters of the access pattern of the disk slice on a plurality of disks. Such techniques further involve determining a score for the disk slice based on the performance information and access frequency information of the disk slice. Such techniques further involve determining a position of the disk slice in the plurality of disks based on the score.

Method, electronic device and computer program product for managing disks based on performance information of access pattern

An apparatus comprises a processing device configured to obtain information associated with services hosted in an information technology infrastructure comprising a core data center hosting a first subset of the services and edge computing sites hosting a second subset of the services. The processing device is also configured to determine, based on the obtained information, values associated with parameters characterizing suitability of hosting respective ones of the services at the computing sites, and to generate, based on the determined values, scores for each of the services. The processing device is further configured to identify, based on the generated scores, at least a given one of the services to be migrated from the core data center to the edge computing devices or from the edge computing sites to the core data center. The processing device is further configured to migrate the given one of the services.

Automated service tiering between edge computing sites and a core data center

An apparatus comprises at least one processing device that includes a processor coupled to a memory. The at least one processing device is configured to determine a current state of a storage system, the current state of the storage system comprising two or more input-output (IO) performance metric values for the storage system, to generate, utilizing a reinforcement learning framework, an IO throttling recommendation for the storage system based at least in part on the current state of the storage system, to apply the IO throttling recommendation to the storage system, and to update the reinforcement learning framework based at least in part on a subsequent state of the storage system following the application of the IO throttling recommendation to the storage system.

Growing community of inventors

Chengdu, China

Changyue Dai