Computing resource scheduling method and device and storage medium
A technology of computing resources and scheduling methods, applied in the Internet field, can solve the problems of lack of cloud computing platform, waste of computing resources, high cost, improve the accuracy of resource utilization and allocation, realize dynamic automatic scheduling, and improve management efficiency. Effect
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Embodiment 1
[0034] Embodiments of the present application provides a resource scheduling method for calculating, as figure 1 Distance figure 1 Present application flow chart of a method of calculating the resource scheduling according to an embodiment, the computing resource scheduling method comprising:
[0035] S101, extracts key indicators cloud computing platform services and services from the log data, the acquired data bearer service service performance;
[0036] Wherein the key indicators include: traffic, frequency the API interface calls, the user request at least one indicator of the number of data, the performance data comprising traffic load, the processor load, memory load, disk load, the load network IO at least one of performance data.
[0037] In practical application scenario of the present embodiment, in order to improve the accuracy and comprehensiveness of resource scheduling, extraction cloud computing platform services business key indicators and performance data from th...
Embodiment 3
[0072] Based on the image processing method provided by the above embodiment, the present application provides a storage medium that stores a computer program on which the processor performs a computer program stored on the storage medium, and implements the present application In any of the first aspect, the method of calculating a resource scheduling method comprising: extracting a key indicator of a cloud computing platform service service from the log data to obtain the business service performance data; wherein the key indicators comprise: Business, API interface call frequency, at least one indicator data in the user request number, the performance data includes at least one of the service load, a processor load, a memory load, a disk load, a network IO load;
[0073] The extracted key indicators and performance data are sample data, and the processing resource prediction model and the business support capability index model are constructed by the machine learning algorithm....
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