Cloud-based accounting monitoring and management system

Abstract

A cloud-based billing monitoring and management system is configured to: perform cost trend analysis on multiple billing processing data using a cost anomaly detection module to generate a cost anomaly detection result; when the cost anomaly detection result indicates that an abnormal cost event has occurred in a project, select a target billing processing data from the billing processing data; send a resource query request to a public cloud platform and receive resource data from the public cloud platform; generate an evaluation result using a resource correction suggestion module based on the target billing processing data and the resource data; generate resource optimization suggestion data based on the evaluation result; receive an execution instruction corresponding to the resource optimization suggestion data, and accordingly call the application interface of the public cloud platform to execute a resource optimization program.

Claims

1. A cloud-based billing monitoring and management system, suitable for communicating with a public cloud platform and a user-end electronic device, comprising: a processing unit; a storage unit electrically connected to the processing unit, storing multiple billing processing data related to the cost usage of a project in a previous period, a cost anomaly detection module, and a resource correction suggestion module, each billing processing data including a daily cost, a project identification code, and a resource identification code; the processing unit using the cost anomaly detection module to perform cost trend analysis on the billing processing data to determine whether an abnormal cost event has occurred for the project, and generating a cost anomaly detection result if the determination result is yes; the processing unit selecting a target billing processing data from the billing processing data based on the cost anomaly detection result, wherein... The target billing processing data includes the resource identification code as a target resource identification code; the processing unit transmits a resource query request containing the target resource identification code to the public cloud platform, and receives resource data corresponding to the resource query request from the public cloud platform; the processing unit uses the resource modification suggestion module to generate an evaluation result based on the target billing processing data and the resource data; the processing unit generates resource optimization suggestion data based on the evaluation result, and transmits the resource optimization suggestion data to the user electronic device; the processing unit receives an execution instruction from the user electronic device corresponding to the resource optimization suggestion data, and calls the application interface of the public cloud platform to execute a resource optimization program accordingly.

2. The cloud-based billing monitoring and management system as described in claim 1, wherein each billing processing data further includes a timestamp and a resource usage record, and the cost anomaly detection module includes a time series analysis model; the processing unit trains the time series analysis model based on the timestamp, the daily cost, and the resource usage record included in each billing processing data to generate a normal cost baseline for the corresponding project, the normal cost baseline including multiple baseline costs corresponding to multiple previous time points within the corresponding previous period, and the previous time points respectively corresponding to the timestamp, the daily cost, and the resource usage record included in the billing processing data. The processing unit determines whether the daily cost included in any of the billing processing data deviates from the normal cost baseline. When it is determined that the daily cost included in any of the billing processing data deviates from the normal cost baseline, the processing unit determines that an abnormal cost event has occurred in the project and generates an abnormal cost detection result. The abnormal cost detection result includes the daily cost included in the billing processing data, the baseline cost corresponding to the previous time point corresponding to the timestamp included in the billing processing data, and abnormal feature data indicating the cost difference between the daily cost and the baseline cost.

3. The cloud-based billing monitoring and management system as described in claim 1, wherein each billing processing data further includes a timestamp; the processing unit performs a periodic time shift on the timestamp included in any of the billing processing data to generate a concurrent comparison benchmark time; the processing unit selects a benchmark billing processing data corresponding to the concurrent comparison benchmark time from the billing processing data, and uses the daily cost included in the benchmark billing processing data as a benchmark cost; the processing unit calculates a cost growth rate based on the daily cost included in one of the billing processing data and the daily cost included in the benchmark billing processing data; the processing unit determines whether the cost growth rate is greater than a preset percentage, and if the determination result is yes, determines that an abnormal cost event has occurred in the project and generates a cost anomaly detection result, the cost anomaly detection result including the daily cost included in the billing processing data, the benchmark cost included in the benchmark billing processing data, and anomaly feature data indicating the cost difference between the daily cost and the benchmark cost.

4. The cloud-based billing monitoring and management system as described in claim 1, wherein each billing processing data further includes a timestamp, and the resource correction suggestion module includes a pre-trained large language model pre-trained using machine learning technology; the processing unit performs semantic analysis using the pre-trained large language model based on the target billing processing data, the resource data, and the cost anomaly detection result to generate the evaluation result including the resource anomaly type and the resource adjustment suggestion.

5. The cloud-based billing monitoring and management system as described in claim 1, wherein each billing processing data further includes a service type, the resource correction suggestion module includes a rule-based suggestion sub-module, and the storage unit further stores multiple resource type determination conditions corresponding to multiple preset service types, each resource type determination condition corresponding to a preset resource type and a preset resource adjustment suggestion; the processing unit executes the rule-based suggestion sub-module to select one of the target resource type determination conditions from the resource type determination conditions according to the service type included in the target billing processing data; the processing unit executes the rule-based suggestion sub-module to determine whether the resource data meets the target resource type determination condition, and if the determination result is yes, obtains the preset resource type corresponding to the target resource type determination condition and the preset resource adjustment suggestion; the processing unit generates the evaluation result based on the preset resource type and the preset resource adjustment suggestion.

6. The cloud-based billing monitoring and management system as described in claim 1 is further adapted to communicate with a cloud-based pricing server, wherein each billing processing data includes current specification information and a current resource unit cost corresponding to the current specification information, and the evaluation result includes a resource optimization suggestion with optimized specification information; the processing unit transmits a pricing query request containing the optimized specification information to the cloud-based pricing server, and receives a suggested resource unit cost corresponding to the pricing query request from the cloud-based pricing server; the processing unit generates an estimated savings amount based on the current resource unit cost, the suggested resource unit cost, and an estimated usage time included in the target billing processing data; the processing unit transmits the current specification information, the optimized specification information, the estimated savings amount, and the resource optimization suggestion data included in the target billing processing data to the user-end electronic device.

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