CAPACITY TRACKING AND FORECAST MODELING ACROSS MULTIPLE PLATFORMS

20240430201

18/340829

June 23, 2023

Systems and methods track capacity and model forecasts across multiple platforms. A flow of data traffic from a first device to a second device is monitored. A future flow of data traffic is forecast based on the monitored flow, the future flow of data traffic including additional data traffic in addition to the monitored flow of data traffic. A threshold is anticipated to be reached in the forecasted future flow of data traffic. A corrective action is determined to mitigate the anticipated threshold being reached and then implemented.

1. A computer-implemented method comprising: monitoring a flow of data traffic from a first device to a second device; forecasting a future flow of data traffic based on the monitored flow, the future flow of data traffic including additional data traffic in addition to the monitored flow of data traffic; anticipating that a threshold is to be reached in the forecasted future flow of data traffic; determining a corrective action to mitigate the anticipated threshold being reached; and causing the determined corrective action to be implemented, the corrective action proactively preventing the anticipated threshold from being reached.

2. The computer-implemented method of claim 1, wherein the corrective action includes one or more of adding additional capacity, adjusting the flow of data traffic, limiting a rate of the flow of data traffic, pausing the flow of data traffic.

3. The computer-implemented method of claim 1, wherein the threshold includes a first threshold indicating a warning threshold level and a second threshold indicating a critical threshold level, wherein the critical threshold level is a higher threshold level than the warning threshold level.

4. The computer-implemented method of claim 3, wherein: the critical threshold level is an indication that resource usage exceeds a peak capacity for a particular component in the forecasted future flow of data traffic; and the warning threshold level is an indication that resource usage reaches a predetermined percentage of the peak capacity for the particular component in the forecasted future flow of data traffic.

5. The computer-implemented method of claim 3, wherein: anticipating that the first threshold is to be reached further comprises anticipating that resource usage for a component in the flow of data traffic, based on the forecasted future flow of data traffic, reaches a predetermined percentage of peak capacity for the component; and anticipating that the second threshold is to be reached further comprises anticipating that resource usage for the component in the flow of data traffic, based on the forecasted future flow of data traffic, exceeds the peak capacity for the component.

6. The computer-implemented method of claim 5, wherein causing the corrective action to be implemented comprises: causing a first corrective action to be implemented based on the anticipation that the first threshold is to be reached in the forecasted future flow of data traffic; and causing a second corrective action to be implemented based on the anticipation that the second threshold is to be reached in the forecasted future flow of data traffic, wherein the first corrective action is different than the second corrective action.

7. The computer-implemented method of claim 1, wherein the flow of data traffic includes one or more of traversing an application programming interface (API) gateway, traversing a firewall, traversing a load balancer, and traversing an application container on the second device.

8. The computer-implemented method of claim 1, wherein the corrective action is implemented prior to the threshold being reached.

9. The computer-implemented method of claim 1, wherein monitoring the flow of data traffic further comprises identifying a subtype usage or frequency of units involved traversed in the monitored flow of data traffic.

10. The computer-implemented method of claim 1, wherein monitoring the flow of data traffic further comprises identifying a customer identifier associated with a received request that initiates the monitored flow of data traffic.

11. The computer-implemented method of claim 1, wherein monitoring the flow of data traffic further comprises identifying downstream requests that are processed in the flow of data traffic.

12. The computer-implemented method of claim 1, further comprising defining a measurement of a workload based on the monitored flow of data traffic.

13. The computer-implemented method of claim 1, further comprising defining an interface that maps the flow of data traffic, wherein forecasting the future flow of data traffic further comprises extrapolating the monitored flow of data traffic through the flow of data traffic mapped by the defined interface.

14. The computer-implemented method of claim 1, further comprising: receiving a query, the query initiating the monitored flow of data traffic; and forecasting the future flow of data traffic for the received query based on the monitored flow.

15. The computer-implemented method of claim 1, further comprising: causing the corrective action to be applied to mitigate a likelihood that the threshold is reached based on the forecasted future flow of data traffic.

16. A system comprising: a processor; a memory communicatively coupled to the processor; and a capacity modeler, implemented on the processor, that: monitors a flow of data traffic from a first device to a second device; forecasts a future flow of data traffic based on the monitored flow, the future flow of data traffic including additional data traffic in addition to the monitored flow of data traffic; anticipates that a threshold is to be reached in the forecasted future flow of data traffic; determines a corrective action to mitigate the anticipated threshold being reached; and initiates the determined corrective action, the corrective action proactively preventing the anticipated threshold from being reached.

17. The system of claim 16, wherein the threshold includes a first threshold indicating a warning threshold level and a second threshold indicating a critical threshold level, wherein the critical threshold level is a higher threshold level than the warning threshold level.

18. The system of claim 17, wherein: to anticipate that the first threshold is to be reached, the capacity modeler further anticipates that resource usage for a component in the flow of data traffic, based on the forecasted future flow of data traffic, reaches a predetermined percentage of peak capacity for the component; and to anticipate that the second threshold is to be reached, the capacity modeler further anticipates that resource usage for the component in the flow of data traffic, based on the forecasted future flow of data traffic, exceeds the peak capacity for the component.

19. The system of claim 18, wherein, to initiate the corrective action, the capacity modeler further: identifies a first corrective action based on the anticipation that the first threshold is to be reached in the forecasted future flow of data traffic; and identifies a second corrective action based on the anticipation that the second threshold is to be reached in the forecasted future flow of data traffic, wherein the first corrective action is different than the second corrective action.

20. A computer-storage medium storing instructions that, when executed by a processor, cause the processor to: monitor a flow of data traffic from a first device to a second device; forecast a future flow of data traffic based on the monitored flow, the future flow of data traffic including additional data traffic in addition to the monitored flow of data traffic; anticipate that a threshold is to be reached in the forecasted future flow of data traffic; determine a corrective action to mitigate the anticipated threshold being reached; and initiate the determined corrective action, the corrective action proactively preventing the anticipated threshold from being reached.

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edspap.20240430201