IP Library Granted Patent US 12681769
Granted Patent B2
US 12681769 · App. 17/962,301 · Granted Jul 14, 2026

Cloud-based resource throttling prediction

Inventors: Bo Zong (Bellevue, WA); Huan Wang (Fremont, CA); Tian Lan (San Francisco, CA); Ran Yao (San Francisco, CA); Tony Wong (San Francisco, CA); Daeki Cho (Kirkland, WA); Caiming Xiong (San Francisco, CA); Silvio Savarese (San Francisco, CA); Yingbo Zhou (Palo Alto, CA)
Assignee: Salesforce, Inc.
G06F9/505G06F9/468G06F9/5072
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Quick Facts
Patent No.
US 12681769
App. No.
17/962,301
Granted
Jul 14, 2026
Kind
B2
Abstract

Embodiments herein relate to prediction, based on previous usage of a cloud-based computing resource by a user of one or more users of the cloud-based computing resource, future usage of the cloud-based computing resource. Based on the predicted future usage, embodiments relate to identifying that throttling of access to the cloud-based computing resource is to occur, and notifying the user of the throttling. Other embodiments may be described and/or claimed.

Claims (40)

1 . One or more non-transitory machine-readable storage media having program instructions stored thereon that are capable of causing a computer system to perform operations comprising:

detecting that a first current usage of a cloud-based computing resource by a user of one or more users that utilize the cloud-based computing resource satisfies an initial threshold;

based on the detecting that the first current usage satisfies the initial threshold, predicting, using a neural network and based on previous usage of the cloud-based computing resource by the user, future usage of the cloud-based computing resource by the user;

identifying, based on the predicted future usage of the cloud-based computing resource satisfying a throttle threshold for a first period of time, that throttling of the user's access to the cloud-based computing resource is to occur; and

before the throttling of the user's access, notifying the user that the throttling is to occur; and

after the notifying the user and based on a detection that a second current usage of the cloud-based computing resource by the user satisfies the throttle threshold for the first period of time, throttling the user's access to the cloud-based computing resource by limiting a number of requests processed for the user within a second period of time.

2 . The one or more non-transitory machine-readable storage media of claim 1 , wherein the cloud-based computing resource is a resource of a database (DB) server.

3 . The one or more non-transitory machine-readable storage media of claim 1 , wherein the throttle threshold is a pre-defined threshold.

4 . The one or more non-transitory machine-readable storage media of claim 1 , wherein the throttle threshold is a dynamic threshold.

5 . The one or more non-transitory machine-readable storage media of claim 1 , wherein the throttle threshold is a dynamic value related to a future level of usage of the resource by a plurality of users that includes the user.

6 . The one or more non-transitory machine-readable storage media of claim 1 , wherein the throttle threshold is based on a comparison of the user's predicted future usage to a predicted total usage by a plurality of users that includes the user.

7 . An article of manufacture comprising:

one or more processors operable to implement a neural network; and

a non-transitory machine-readable storage medium having program instructions stored thereon that are executable by the one or more processors to perform operations comprising:

identifying a plurality of sets of data related to usage of a cloud-based computing resource, wherein a set of data of the plurality of sets of data includes:

an indication of an amount of usage of the cloud-based computing resource at a first historical time; and

an indication of an amount of usage of the cloud-based computing resource at a second historical time that is after the first historical time;

generating, based on the plurality of sets of data, a model configured to predict future usage of the cloud-based computing resource based on previous usage of the cloud-based computing resource; and

detecting that a first current usage of the cloud-based computing resource by a user satisfies an initial threshold;

based on the detecting that the first current usage satisfies the initial threshold, predicting, using the model and based on previous usage of the cloud-based computing resource by the user, future usage of the cloud-based computing resource by the user;

identifying, based on the predicted future usage by the user satisfying a throttle threshold for a first period of time, that throttling of the user's access to the cloud-based computing resource is to occur; and

before the throttling of the user's access, notifying the user that the throttling is to occur; and

after the notifying the user and based on a detection that a second current usage of the cloud-based computing resource by the user satisfies the throttle threshold for the first period of time, throttling the user's access to the cloud-based computing resource by limiting a number of requests processed for the user within a second period of time.

8 . The article of claim 7 , wherein the cloud-based computing resource is a resource of a database (DB) server.

9 . The article of claim 7 , wherein the throttle threshold is a pre-defined threshold.

10 . The article of claim 7 , wherein the throttle threshold is a dynamic threshold.

11 . The article of claim 7 , wherein the throttle threshold is a dynamic value related to a future level of usage of the resource by a plurality of users that includes the user.

12 . The article of claim 7 , wherein the throttle threshold is based on a comparison of the user's predicted future usage to a predicted total usage by a plurality of users that includes the user.

13 . An electronic device comprising:

one more processors; and

one or more non-transitory machine-readable storage medium having program instructions stored thereon that are executable by the one or more processors to cause the electronic device to perform operations comprising:

detecting that a first current usage of a resource of a database server by a user satisfies an initial threshold;

based on the detecting that the first current usage satisfies the initial threshold, predicting, using a neural network and based on previous usage of the resource by the user, future usage of the resource by the user;

identifying, based on the predicted future usage satisfying a throttle threshold for a first period of time, that the user's access to the resource is to be throttled at a future time;

providing, to the user based on the identifying, an indication that the user's access to the resource is to be throttled at the future time; and

after the providing of the indication to the user and based on a detection that a second current usage of the resource by the user satisfies the throttle threshold at the future time, throttling the user's access to the resource by limiting a number of requests processed for the user within a period of time.

14 . The electronic device of claim 13 , wherein the throttle threshold is a pre-defined value.

15 . The electronic device of claim 13 , wherein the throttle threshold is based on a comparison of the user's predicted future usage to total usage capacity of the resource.

16 . The electronic device of claim 13 , wherein the throttle threshold is a dynamic value related to a future level of usage of the resource by a plurality of users that includes the user.

17 . The electronic device of claim 13 , wherein the throttle threshold is based on a comparison of the user's predicted future usage to a predicted total usage by a plurality of users that includes the user.