Salesforce, Inc.

Vaibhav Tendulkar

Kaushal Bansal

Rakesh Ganapathi Karanth

Venkata Muralidhar Tejomurtula

Fangchen Richard Sun

Examples include maintaining a virtual pool of containers; receiving a request from a client for one of a plurality of services to performed; when the request includes client code, determining whether the request belongs to regular or priority queue based on two models; adding the request to an appropriate shard in the queue; getting the request from the selected one of the plurality of queues and assigning a container for the request from the virtual pool of containers, the client code to be executed in the container; and after the client code is executed in the container, deleting the container from the virtual pool.

Predictive allocation of ephemeral containers for cloud computing services

Examples include a method of predictive rate limiting for performing services requested by a client in a cloud computing system. The method includes receiving a request from a client for one of a plurality of services to be performed, the client belonging to an organization; and determining a current threshold for the organization by applying a real time data model and a historical data model, the real time data model generating a first threshold at least in part by determining a number of requests received from the organization over a first preceding period of time; the historical data model generating a second threshold, the historical data model being generated by applying a machine learning model to historical data stored during processing of previous requests for the plurality of services from the organization over a second preceding period of time, the current threshold being the average of the first threshold and the second threshold. The method further includes performing the requested service when the current threshold is not exceeded; and denying the request when the current threshold is exceeded.

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San Francisco, CA, United States of America

Vaibhav Tendulkar