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US 2026/0289452 A1Published application
Technologies for managing operational risk in a computing platform infrastructure
AssigneeDK Crown Holdings Inc.
InventorsDavid A. Covino, Benjamin Lieberman, Charles Arnaudo
Life of this patent
Estimating the term…
Abstract
Techniques for managing resource optimization tools on a cloud-based platform (e.g., an online sportsbook platform) include a computing system that retrieves schedule data associated with events (e.g., sport events). The system predicts, based on the schedule data, events having a likelihood of increasing user traffic to a platform, in which the platform has resource optimization tools configured to optimize resource utilization on the platform. Time windows associated with each of the predicted events are identified, and configuration parameters of the resource optimization tools are modified to adjust operation of the tools during the identified time windows.
Claims20
A system comprising:
- one or more processors;
- and
- a memory storing a plurality of instructions, which, when executed on the one or more processors, causes the system to:
- retrieve schedule data associated with a plurality of events by polling an application programming interface (API) of one of a plurality of internal services of a platform, each event occurring between a future start time and end time, the platform comprising a plurality of nodes and at least one resource optimization tool configured to optimize utilization of one or more computing resources of the platform;
- retrieve historical data associated with the platform by polling an API of another one of the plurality of internal services on the platform, the historical data comprising prior betting activity, platform engagement, and utilization of the one or more computing resources relating to each of the plurality of events;
- predict, based on a weighting of the schedule data and on the historical data, one or more of the plurality of events having a likelihood of increasing user traffic to the platform;
- identify a time window associated with each of the predicted one or more events;
- modify, prior to entering the identified time windows, one or more configuration parameters of at least one resource optimization tool from pre-time window settings to temporary settings to adjust operation of the resource optimization tool during the identified time windows and minimize a risk of disruption to the plurality of internal services of the platform during the identified time windows, wherein to modify the one or more configuration parameters comprises to adjust at least one of a pod disruption budget, a node churn threshold, a bin-packing density parameter, or a dynamic scaling aggressiveness parameter of a resource optimization tool configured to control pod scheduling or node provisioning within the platform;
- upon entering one of the identified time windows, execute the at least one resource optimization tool under the modified one or more configuration parameters;
- and
- upon exiting the one of the identified time windows, restore the one or more configuration parameters to the pre-time window settings.
8 more elements
(canceled)
A computer-readable storage medium storing a plurality of instructions, which, when executed by one or more processors, causes a system to:
- retrieve schedule data associated with a plurality of events by polling an application programming interface (API) of one of a plurality of internal services of a platform, each event occurring between a future start time and end time, the platform comprising a plurality of nodes and at least one resource optimization tool configured to optimize utilization of one or more computing resources of the platform;
- retrieve historical data associated with the platform by polling an API of another one of the plurality of internal services on the platform, the historical data comprising prior betting activity, platform engagement, and utilization of the one or more computing resources relating to each of the plurality of events;
- predict, based on a weighting of the schedule data and on the historical data, one or more of the plurality of events having a likelihood of increasing user traffic to the platform;
- identify a time window associated with each of the predicted one or more events;
- modify, prior to entering the identified time windows, one or more configuration parameters of at least one resource optimization tool from pre-time window settings to temporary settings to adjust operation of the resource optimization tool during the identified time windows and minimize a risk of disruption to the plurality of internal services of the platform during the identified time windows, wherein to modify the one or more configuration parameters comprises to adjust at least one of a pod disruption budget, a node churn threshold, a bin-packing density parameter, or a dynamic scaling aggressiveness parameter of a resource optimization tool configured to control pod scheduling or node provisioning within the platform;
- upon entering one of the identified time windows execute the at least one resource optimization tool under the modified one or more configuration parameters;
- and
- upon exiting the one of the identified time windows, restore the one or more configuration parameters to the pre-time window settings.
5 more elements
(canceled)
A method comprising:
- retrieving, by one or more processors, schedule data associated with a plurality of events by polling an application programming interface (API) of one of a plurality of internal services of a platform, each event occurring between a future start time and end time, the platform comprising a plurality of nodes and at least one resource optimization tool configured to optimize utilization of one or more computing resources of the platform;
- retrieving historical data associated with the platform by polling an API of another one of the plurality of internal services on the platform, the historical data comprising prior betting activity, platform engagement, and utilization of the one or more computing resources relating to each of the plurality of events;
- predicting, based on a weighting of the schedule data and on the historical data, one or more of the plurality of events having a likelihood of increasing user traffic to the platform;
- identifying a time window associated with each of the predicted one or more events;
- modifying, prior to entering the identified time windows, one or more configuration parameters of at least one resource optimization tool to adjust operation of the resource optimization tool during the identified time windows and minimize a risk of disruption to the plurality of internal services of the platform during the identified time windows, wherein modifying the one or more configuration parameters comprises adjusting at least one of a pod disruption budget, a node churn threshold, a bin-packing density parameter, or a dynamic scaling aggressiveness parameter of a resource optimization tool configured to control pod scheduling or node provisioning within the platform;
- upon entering one of the identified time windows, executing the at least one resource optimization tool under the modified one or more configuration parameters;
- and
- upon exiting the one of the identified time windows, restore the one or more configuration parameters to the pre-time window settings.
5 more elements
(canceled)
Dependencies are inferred from the claim text.