Multi-cloud management platform with comprehensive financial management function

Abstract

The invention discloses a multi-cloud management platform with a comprehensive financial management function, and relates to the technical field of cloud services, and the multi-cloud management platform comprises a data integration unit, a cost management unit, a budget control unit, a bill processing unit, a security and compliance unit, a user interaction unit and a monitoring and alarm unit. Through the data integration unit, financial data from different cloud platforms can be effectively acquired and integrated, through the cost management unit, financial characteristic data can be deeply analyzed, a cost structure can be better understood, and a cost saving opportunity can be found, so that strategy or budget allocation can be timely adjusted to cope with changing demands and market conditions, and the economic benefit is improved. And meanwhile, the real-time monitoring of the use condition and the cost change of the cloud platform is realized.

Description

Technical Field

[0001] The present invention relates to the field of cloud service technology, and in particular to a multi-cloud management platform with comprehensive financial management functions. Background Art

[0002] At present, there are many cloud vendors in the market. When users purchase cloud resources, if they need to compare resources from different cloud vendors, they can only log in to multiple cloud vendor platforms for comparison and viewing. When they need to purchase different resources from multiple cloud vendors, they can only purchase them one by one through multiple platforms. This is extremely inconvenient for both early resource purchase and later resource operation and maintenance. The resource bills generated by each cloud vendor are difficult to collect and unify. To this end, it is necessary to use one account to connect multiple cloud vendor platforms, support price comparison and combined ordering of cloud products from multiple cloud vendors, and output unified billing data. The existing multi-cloud management platform is not convenient for obtaining and integrating financial data from different cloud platforms, providing a unified data view, and is not convenient for identifying key factors affecting costs, and cannot effectively understand the cost structure and find opportunities for cost savings, which is not convenient for better financial management and decision support.

[0003] Currently, no effective solution has been proposed for the problems in the related technologies. Summary of the invention

[0004] In view of the problems in the related technology, the present invention proposes a multi-cloud management platform with comprehensive financial management functions to overcome the above-mentioned technical problems existing in the existing related technology.

[0005] To this end, the specific technical solution adopted by the present invention is as follows:

[0006] A multi-cloud management platform with comprehensive financial management functions, the multi-cloud management platform comprising: a data integration unit, a cost management unit, a budget control unit, a bill processing unit, a security and compliance unit, a user interaction unit, and a monitoring and alarm unit;

[0007] The data integration unit is used to obtain financial data from different cloud platforms and integrate them to obtain financial characteristic data;

[0008] The cost management unit is used to analyze the obtained financial characteristic data and identify the key factors affecting the cost;

[0009] Budget control unit, which is used to allocate budgets for different cloud platforms and services based on key factors and financial characteristic data, and adjust strategies or budget allocations in a timely manner;

[0010] The bill processing unit is used to review and compare billing data of various cloud platforms, make cost optimization suggestions, and generate customer and internal financial reports;

[0011] The Security and Compliance Unit is responsible for protecting the security of financial data and billing information, monitoring the compliance of the platform, and assessing the security risks associated with the use of cloud services;

[0012] A user interaction unit, used to provide a user interface and interactive functions to facilitate users to access and manage cloud services;

[0013] The monitoring and alarm unit is used to monitor the usage and cost changes of each cloud platform in real time and provide alarm functions to prevent budget overspending.

[0014] Further, the data integration unit includes: a data acquisition module and a data processing module;

[0015] Data acquisition module, used to obtain financial data from different cloud platforms;

[0016] The data processing module is used to pre-process the acquired financial data to obtain financial characteristic data.

[0017] Furthermore, the obtained financial characteristic data was analyzed to identify the key factors affecting costs, including:

[0018] Set the sample set of financial characteristic data and preset the number of mutation and crossover operations;

[0019] Mutate the financial feature data sample set through mutation operation, calculate the difference vector between each financial feature data sample, determine the best mutated financial feature data sample in the sample set, and use it as a new mutated financial feature data sample;

[0020] The new variant financial characteristic data samples are crossed through the crossover operation to determine the best experimental financial characteristic data sample in the sample set;

[0021] Use the analysis algorithm to conduct a new cluster analysis on the financial feature data samples to determine the cluster where each financial feature data sample belongs and the optimal distance between samples;

[0022] For the newly formed financial feature data sample set, the experimental financial feature data sample and the objective function are compared according to the mutation crossover, and the financial feature data sample set with the lowest objective function value is selected as the new sample set;

[0023] Determine whether the termination condition is met. If so, end the optimization process and use the current best financial feature data sample set as the key factor affecting the cost. Otherwise, continue the optimization.

[0024] Furthermore, the formula for the mutation operation is:

[0025]

[0026] in, It is represented as the i-th mutated financial feature data sample obtained after the mutation operation in the financial data sample set at time t+1;

[0027] Represented as parent basis vectors;

[0028] is the parent difference vector;

[0029] S represents the scaling factor;

[0030] r1, r2, and r3 represent three different indexes randomly selected from the index of the current financial data sample set.

[0031] Furthermore, the analysis algorithm is used to perform a new cluster analysis on the financial feature data samples to determine the cluster where each financial feature data sample belongs and the optimal distance between the samples, including:

[0032] Randomly select K financial feature data samples from the financial feature data sample set as the center points of the initial cluster;

[0033] Assign each unassigned financial feature data sample to the cluster center point closest to it;

[0034] Randomly select a financial feature data sample that is not a cluster center from the financial feature data sample set, and record it as a random financial feature data sample;

[0035] Calculate the total cost change caused by replacing the current cluster center point with a random financial feature data sample, and update the cluster center set;

[0036] When the cluster center point no longer changes, the final cluster of each financial feature data sample is determined, and the optimal distance between each financial feature data sample is calculated.

[0037] Furthermore, the budget control unit includes: a data analysis module, a budget allocation module and a strategy adjustment module;

[0038] Data analysis module, used to analyze the impact of financial characteristic data and key factors on cloud service costs and benefits;

[0039] Budget allocation module, which is used to allocate budgets to different cloud platforms and services based on the impact, ensuring that resources are allocated effectively;

[0040] The strategy adjustment module is used to monitor market trends, cloud service usage and financial performance, and adjust strategies or budget allocations in a timely manner based on performance to adapt to market changes and business needs.

[0041] Furthermore, the bill processing unit includes: an abnormal consumption identification module, a cost optimization evaluation module, and a report generation module;

[0042] Abnormal consumption identification module, used to analyze bill data and identify abnormal consumption characteristics;

[0043] Cost optimization evaluation module, which is used to analyze the current cost-benefit ratio and make cost optimization suggestions based on preset evaluation criteria and thresholds;

[0044] Report generation module for generating detailed customer and internal financial reports based on proposed cost optimization recommendations.

[0045] Further, the security and compliance unit includes: a data encryption module, an access control management module, a risk assessment and management module, and a data backup and recovery module;

[0046] Data encryption module, used to encrypt stored and transmitted financial data to ensure that the data remains confidential in the event of unauthorized access;

[0047] Access control management module, used to manage user permissions to ensure that only authorized personnel can access financial data and billing information;

[0048] Risk assessment and management module, which is used to regularly assess and identify potential security risks associated with the use of cloud services, and to design and implement corresponding risk mitigation strategies and control measures;

[0049] Data backup and recovery module, used to regularly back up financial data and billing information and ensure rapid recovery in case of data loss or damage.

[0050] Further, the user interaction unit includes: an interface display module, a user input processing module, a user customization module, and a security and authority management module;

[0051] The interface display module is responsible for presenting the user interface and enabling users to intuitively view cloud service information, billing data, and cost optimization reports;

[0052] The user input processing module is used to process user input and ensure that user operations can be correctly transmitted to the backend system for processing;

[0053] User customization module is used to allow users to customize the interface and functions according to their own needs to improve the user experience;

[0054] The security and permission management module is used to manage user login verification and permission control to ensure data security and privacy protection for users on various cloud platforms.

[0055] Furthermore, the monitoring and alarm unit includes: a resource usage monitoring module, a cost tracking module, and a budget management and alarm module;

[0056] Resource usage monitoring module, which is used to track and monitor resource usage on the cloud platform and provide real-time data and historical usage trends;

[0057] Cost tracking module, which monitors the costs and expenditures of the cloud platform and helps identify cost-saving opportunities by analyzing the expenses of different services, projects or departments;

[0058] Budget management and alerting module allows setting budget limits and sends alert notifications when the predetermined budget is approached or exceeded.

[0059] The beneficial effects of the present invention are:

[0060] 1. The present invention can effectively acquire and integrate financial data from different cloud platforms through the data integration unit, and can deeply analyze financial characteristic data through the cost management unit to identify key factors affecting costs, so as to better understand the cost structure and find opportunities for cost savings, thereby timely adjusting strategies or budget allocations to cope with changing demands and market conditions, while realizing real-time monitoring of cloud platform usage and cost changes.

[0061] 2. The present invention sets a sample set of financial feature data and performs mutation and crossover operations, so that the platform can analyze financial data more deeply and identify key factors affecting costs. Through cluster analysis methods, the platform can classify financial feature data more accurately and find the optimal combination of financial features, which helps to formulate more accurate cost control strategies and budget allocations. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0063] Figure 1 is a principle block diagram according to an embodiment of the present invention;

[0064] Figure 2 is a structural block diagram of a data integration unit according to an embodiment of the present invention;

[0065] Figure 3 is a structural block diagram of a budget control unit according to an embodiment of the present invention;

[0066] Figure 4is a structural block diagram of a bill processing unit according to an embodiment of the present invention;

[0067] Figure 5 is a structural block diagram of a security and compliance unit according to an embodiment of the present invention;

[0068] Figure 6 is a structural block diagram of a user interaction unit according to an embodiment of the present invention;

[0069] Figure 7 4 is a structural block diagram of a monitoring and alarm unit according to an embodiment of the present invention.

[0070] In the figure:

[0071] 1. Data integration unit; 101. Data acquisition module; 102. Data processing module; 2. Cost management unit; 3. Budget control unit; 301. Data analysis module; 302. Budget allocation module; 303. Policy adjustment module; 4. Bill processing unit; 401. Abnormal consumption identification module; 402. Cost optimization evaluation module; 403. Report generation module; 5. Security and compliance unit; 501. Data encryption module; 502. Access control management module; 503. Risk assessment and management module; 504. Data backup and recovery module; 6. User interaction unit; 601. Interface display module; 602. User input processing module; 603. User customization module; 7. Monitoring and alarm unit; 701. Resource usage monitoring module; 702. Cost tracking module; 703. Budget management and alarm module. DETAILED DESCRIPTION

[0072] The present invention is further described with reference to the accompanying drawings and specific embodiments. Figure 1-Figure 7 As shown, according to an embodiment of the present invention, a multi-cloud management platform with comprehensive financial management functions includes: a data integration unit 1, a cost management unit 2, a budget control unit 3, a bill processing unit 4, a security and compliance unit 5, a user interaction unit 6 and a monitoring and alarm unit 7;

[0073] The data integration unit 1 is used to obtain financial data from different cloud platforms and perform integration processing to obtain financial characteristic data;

[0074] Cost management unit 2, used to analyze the obtained financial characteristic data and identify key factors affecting the cost;

[0075] Budget control unit 3, used to allocate budgets for different cloud platforms and services based on key factors and financial characteristic data, and to adjust strategies or budget allocations in a timely manner;

[0076] Billing processing unit 4, used to review and compare billing data of each cloud platform, make cost optimization suggestions, and generate customer and internal financial reports;

[0077] Security and Compliance Unit 5, which is used to protect the security of financial data and billing information, monitor platform compliance, and assess security risks associated with the use of cloud services;

[0078] A user interaction unit 6, used to provide a user interface and interactive functions to facilitate users to access and manage cloud services;

[0079] The monitoring and alarm unit 7 is used to monitor the usage and cost changes of each cloud platform in real time and provide an alarm function to prevent budget overspending.

[0080] Preferably, the data integration unit 1 comprises: a data acquisition module 101 and a data processing module 102;

[0081] The data acquisition module 101 is used to acquire financial data from different cloud platforms;

[0082] The data processing module 102 is used to pre-process the acquired financial data to obtain financial characteristic data.

[0083] Preferably, the obtained financial characteristic data is analyzed to identify key factors affecting the cost including:

[0084] Set the sample set of financial characteristic data and preset the number of mutation and crossover operations;

[0085] Mutate the financial feature data sample set through mutation operation, calculate the difference vector between each financial feature data sample, determine the best mutated financial feature data sample in the sample set, and use it as a new mutated financial feature data sample;

[0086] Specifically, the mutation operation is the processing of the mutation operation in the differential evolution algorithm (DE).

[0087] The new variant financial characteristic data samples are crossed through the crossover operation to determine the best experimental financial characteristic data sample in the sample set;

[0088] Specifically, the crossover operation is the processing of the crossover operation in the differential evolution algorithm (DE).

[0089] Use the analysis algorithm to conduct a new cluster analysis on the financial feature data samples to determine the cluster where each financial feature data sample belongs and the optimal distance between samples;

[0090] For the newly formed financial feature data sample set, the experimental financial feature data sample and the objective function are compared according to the mutation crossover, and the financial feature data sample set with the lowest objective function value is selected as the new sample set;

[0091] Determine whether the termination condition is met. If so, end the optimization process and use the current best financial feature data sample set as the key factor affecting the cost. Otherwise, continue the optimization.

[0092] Preferably, the formula for the mutation operation is:

[0093]

[0094] in, It is represented as the i-th mutated financial feature data sample obtained after the mutation operation in the financial data sample set at time t+1;

[0095] Represented as parent basis vectors;

[0096] is the parent difference vector;

[0097] S represents the scaling factor;

[0098] Specifically, the value of S is between 0.4 and 0.6. When S is close to 0.5, Close to the parent vector.

[0099] r1, r2, and r3 represent three different indexes randomly selected from the index of the current financial data sample set.

[0100] Preferably, performing a new cluster analysis on the financial feature data samples using an analysis algorithm to determine the cluster to which each financial feature data sample belongs and the optimal distance between samples includes:

[0101] Randomly select K financial feature data samples from the financial feature data sample set as the center points of the initial cluster;

[0102] Assign each unassigned financial feature data sample to the cluster center point closest to it;

[0103] Randomly select a financial feature data sample that is not a cluster center from the financial feature data sample set, and record it as a random financial feature data sample;

[0104] Calculate the total cost change caused by replacing the current cluster center point with a random financial feature data sample, and update the cluster center set;

[0105] When the cluster center point no longer changes, the final cluster of each financial feature data sample is determined, and the optimal distance between each financial feature data sample is calculated.

[0106] Specifically, the analysis algorithm is a K-medoids clustering algorithm based on differential evolution. The idea of ​​the K-medoids clustering algorithm based on differential evolution is: first, a group of a certain size is randomly selected from the population, and the size of the group is set to a fixed value. At the same time, the maximum size limit of the population is set. Then, the differential evolution algorithm (DE) is used to perform mutation and crossover operations on this population to determine the optimal mutant individuals and experimental individuals in the population, thereby avoiding the population from falling into the local optimum and enhancing the algorithm's local search ability in the cluster space area. Next, according to the K-medoids clustering algorithm, a new clustering analysis is performed on these optimized experimental individuals to determine the cluster to which each individual belongs and the optimal distance between them. In this way, the individual with the lowest objective function value can be found and used as a member of the new population, and the optimal solution is finally output. Finally, the global search ability of the differential evolution algorithm (DE) and the local search efficiency of the K-medoids clustering algorithm in a specific spatial area are combined to achieve more efficient clustering analysis and feature extraction.

[0107] Preferably, the budget control unit 3 includes: a data analysis module 301, a budget allocation module 302 and a strategy adjustment module 303;

[0108] Data analysis module 301, used to analyze the impact of financial characteristic data and key factors on cloud service costs and benefits;

[0109] It should be explained that the specific impact of financial characteristic data and key factors on the cost and benefits of cloud services can be explained from the following aspects:

[0110] 1) Specific manifestations and impacts of financial characteristic data:

[0111] Cost control: Financial characteristic data such as cost structure analysis (fixed costs and variable costs), capital expenditures (CapEx), operating expenses (OpEx), etc. directly affect the total cost of cloud services. For example, a high proportion of fixed costs may lead to large initial investments, but as the scale expands, the unit cost decreases.

[0112] Revenue and profitability: Financial indicators such as revenue growth rate and profit margin can reflect the profitability and cost recovery speed of cloud services. Services with high revenue may be able to cover costs faster and achieve profitability.

[0113] Cash flow: Analysis of cash inflows and outflows helps assess the financial health of a cloud service, impacting its long-term sustainability and ability to scale.

[0114] 2) Specific manifestations and impacts of key factors:

[0115] Technical factors: including technology update speed, maintenance costs, technology reliability, etc. These factors directly affect the operation and maintenance costs and efficiency of cloud services.

[0116] Market factors: market demand, competition, customer acquisition costs, etc. These factors determine the pricing strategy and market share of cloud services, which in turn affects revenue.

[0117] It should be explained that the analysis process is implemented as follows:

[0118] Data integration: First, data needs to be collected and integrated from multiple data sources, such as financial systems, customer management systems, and operation monitoring systems.

[0119] Data modeling: Build appropriate statistical or machine learning models based on the business problem. For example, use regression analysis to explore the relationship between key financial indicators and costs, or use decision trees to analyze which market factors have the greatest impact on revenue.

[0120] Insight extraction: Analysis of model results to identify which financial characteristics or key factors have a significant impact on the cost and benefits of cloud services. This requires professional data analysts to interpret the data and understand the business.

[0121] Strategy formulation: Based on the analysis results, companies need to adjust their financial strategies or business operation models to optimize cost structure and improve service efficiency.

[0122] A budget allocation module 302 is used to allocate budgets to different cloud platforms and services according to the impact conditions to ensure that resources are effectively allocated;

[0123] It is important to explain that the purpose of allocating budgets to different cloud platforms and services is to ensure that resources are allocated effectively based on their impact and benefits. This process can be achieved by following the following steps and considerations:

[0124] 1) Determine the measurement criteria

[0125] Metrics to ensure resources are allocated efficiently include:

[0126] Cost-effectiveness: ensuring that every expense invested brings the greatest return.

[0127] Service performance: Ensure that the performance of cloud services meets user requirements, such as response time, availability, and scalability.

[0128] Strategic alignment: Budget allocation should support the organization’s long-term strategies, such as market expansion and technology upgrades.

[0129] Flexibility and adjustability: Budget allocations should be easily adjustable as markets and technologies change.

[0130] 2) Data analysis and budget modeling

[0131] Based on the previous analysis of financial characteristics and key factors, the model can predict the cost-benefit relationship of different cloud platforms and services. Based on these predictions:

[0132] Build budget models: Use historical data and forecasting models to determine budget requirements for individual cloud services and platforms.

[0133] Risk assessment: Assess the risks of each option, such as technology failure, market changes, etc., and make adjustments to budget allocation.

[0134] 3) Priority and allocation strategy

[0135] Prioritization: Set priorities based on the strategic importance and urgency of the service or platform.

[0136] Allocation strategy: Determine the budget allocation ratio. Services and platforms with high priority or high returns can get more resources.

[0137] 4) Implementation and monitoring

[0138] Implement budget allocation: Allocate budgets to various cloud platforms and services according to policies.

[0139] Continuous Monitoring and Evaluation: After implementation, continuously monitor the performance and cost-effectiveness of the service. Use real-time data analytics to evaluate the effectiveness of budget allocations and make adjustments as needed.

[0140] 5) Feedback and Adjustment

[0141] Collect feedback: Gather feedback from operations teams and users to understand whether budget allocations are achieving the desired results.

[0142] Periodic Adjustment: Budget allocations are reviewed and adjusted periodically to ensure they are aligned with the organization’s current needs and market conditions.

[0143] The strategy adjustment module 303 is used to monitor market dynamics, cloud service usage and financial performance, and adjust strategies or budget allocations in a timely manner according to the performance to adapt to market changes and business needs.

[0144] It is important to explain how monitoring market dynamics, cloud service usage, and financial performance affect budget allocation. This can be explained from the following aspects:

[0145] 1) Monitoring and influencing market dynamics

[0146] Market dynamics include industry trends, competitor behavior, changes in customer demand, etc. The impact of these dynamics on budget allocation is mainly reflected in:

[0147] Changes in demand: An increase or decrease in market demand may result in increased investment or reduced budget for certain cloud services.

[0148] Competitive pressures: The entry of new competitors or changes in strategies by existing competitors may require adjustments to service pricing or increases in innovation budgets to remain competitive.

[0149] Technological development: The emergence of new technologies may require more R&D investment, affecting the original budget allocation.

[0150] 2) Monitoring and impact of cloud service usage

[0151] The usage of cloud services reflects the acceptance, performance, and reliability of the services. The impact on budget allocation includes:

[0152] Resource utilization: Platforms with high service utilization may require more resource support, whereas platforms with low service utilization may require less.

[0153] Performance indicators: Performance that does not meet standards, such as latency and downtime, may require additional technical support and investment.

[0154] Customer feedback: Low user satisfaction with a service may require reallocation of budget by improving service quality or customer service.

[0155] 3) Monitoring and influence of financial performance

[0156] Financial performance involves key financial indicators such as revenue, cost, and profit. Their performance affects budget allocation as follows:

[0157] Revenue and Profit: Services with high revenue and profit are likely to receive more reinvestment to support continued growth.

[0158] Cost control: If the cost of a service exceeds the budget, you may need to adjust your strategy to control costs or reduce unnecessary expenses.

[0159] Return on investment: Projects with low ROI may have their funding cut or reallocated to higher-yield projects.

[0160] It should be noted that some methods for adjusting strategies or budget allocations in a timely manner based on performance include:

[0161] Data-driven decision making: Use data analysis tools and models to track and monitor market trends, cloud service usage, and financial performance in real time to ensure that decisions are based on sufficient data support.

[0162] Dynamic adjustment mechanism: Set thresholds and indicators. Once certain key indicators reach the preset thresholds, budget or strategy adjustments are automatically triggered.

[0163] Regular review: Review market dynamics, service usage, and financial performance regularly (e.g., quarterly), evaluate the effectiveness of existing strategies, and make adjustments based on business needs and market changes.

[0164] Flexible response strategy: To cope with the rapidly changing market environment, budget and strategy adjustments should be highly flexible and adaptable to ensure rapid response to market and operational needs.

[0165] Preferably, the bill processing unit 4 includes: an abnormal consumption identification module 401, a cost optimization evaluation module 402, and a report generation module 403;

[0166] The abnormal consumption identification module 401 is used to analyze bill data and identify abnormal consumption characteristics;

[0167] The cost optimization evaluation module 402 is used to analyze the current cost-effectiveness ratio according to the preset evaluation criteria and thresholds, and to make cost optimization suggestions;

[0168] The report generation module 403 is used to generate detailed customer and internal financial reports based on the proposed cost optimization suggestions.

[0169] Preferably, the security and compliance unit 5 includes: a data encryption module 501, an access control management module 502, a risk assessment and management module 503 and a data backup and recovery module 504;

[0170] Data encryption module 501, used to encrypt stored and transmitted financial data to ensure that the data remains confidential in the event of unauthorized access;

[0171] Access control management module 502, used to manage user rights and ensure that only authorized personnel can access financial data and billing information;

[0172] Risk assessment and management module 503, used to regularly assess and identify potential security risks associated with the use of cloud services, and to design and implement corresponding risk mitigation strategies and control measures;

[0173] The data backup and recovery module 504 is used to regularly back up financial data and billing information and ensure rapid recovery in the event of data loss or damage.

[0174] Preferably, the user interaction unit 6 includes: an interface display module 601, a user input processing module 602, a user customization module 603, and a security and authority management module 604;

[0175] The interface display module 601 is responsible for presenting the user interface and enabling the user to intuitively view the cloud service information, billing data and cost optimization report;

[0176] The user input processing module 602 is used to process the user's input and ensure that the user's operation can be correctly transmitted to the backend system for processing;

[0177] User customization module 603, used to allow users to customize the interface and functions according to their needs, thereby improving the user experience;

[0178] The security and authority management module 604 is used to manage the user's login verification and authority control to ensure the data security and privacy protection of the user on each cloud platform.

[0179] Preferably, the monitoring and alarm unit 7 includes: a resource usage monitoring module 701, a cost tracking module 702 and a budget management and alarm module 703;

[0180] Resource usage monitoring module 701, used to track and monitor resource usage on the cloud platform and provide real-time data and historical usage trends;

[0181] A cost tracking module 702 for monitoring costs and expenditures of the cloud platform and helping to identify cost saving opportunities by analyzing expenses of different services, projects or departments;

[0182] The budget management and alarm module 703 is used to allow the setting of budget limits and send alarm notifications when the budget is approaching or exceeding the preset budget.

[0183] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A multi-cloud management platform with comprehensive financial management functions, characterized in that: The multi-cloud management platform includes: a data integration unit, a cost management unit, a budget control unit, a bill processing unit, a security and compliance unit, a user interaction unit, and a monitoring and alarm unit; The data integration unit is used to obtain financial data from different cloud platforms and integrate them to obtain financial characteristic data; The cost management unit is used to analyze the obtained financial characteristic data and identify the key factors affecting the cost; Budget control unit, which is used to allocate budgets for different cloud platforms and services based on key factors and financial characteristic data, and adjust strategies or budget allocations in a timely manner; The bill processing unit is used to review and compare billing data of various cloud platforms, make cost optimization suggestions, and generate customer and internal financial reports; The Security and Compliance Unit is responsible for protecting the security of financial data and billing information, monitoring the compliance of the platform, and assessing the security risks associated with the use of cloud services; A user interaction unit, used to provide a user interface and interactive functions to facilitate users to access and manage cloud services; The monitoring and alarm unit is used to monitor the usage and cost changes of each cloud platform in real time and provide alarm functions to prevent budget overspending.

2. A multi-cloud management platform with comprehensive financial management functions according to claim 1, characterized in that: The data integration unit includes: a data acquisition module and a data processing module; Data acquisition module, used to obtain financial data from different cloud platforms; The data processing module is used to pre-process the acquired financial data to obtain financial characteristic data.

3. A multi-cloud management platform with comprehensive financial management functions according to claim 1, characterized in that: By analyzing the obtained financial characteristic data, the key factors affecting the cost are identified, including: Set the sample set of financial characteristic data and preset the number of mutation and crossover operations; Mutate the financial feature data sample set through mutation operation, calculate the difference vector between each financial feature data sample, determine the best mutated financial feature data sample in the sample set, and use it as a new mutated financial feature data sample; The new variant financial characteristic data samples are crossed through the crossover operation to determine the best experimental financial characteristic data sample in the sample set; Use the analysis algorithm to perform a new cluster analysis on the financial feature data samples to determine the cluster where each financial feature data sample belongs and the optimal distance between samples; For the newly formed financial feature data sample set, the experimental financial feature data sample and the objective function are compared according to the mutation crossover, and the financial feature data sample set with the lowest objective function value is selected as the new sample set; Determine whether the termination condition is met. If so, end the optimization process and use the current best financial feature data sample set as the key factor affecting the cost. Otherwise, continue the optimization.

4. A multi-cloud management platform with comprehensive financial management functions according to claim 3, characterized in that: The formula for the mutation operation is: in, It is represented as the i-th mutated financial feature data sample obtained after the mutation operation in the financial data sample set at time t+1; Represented as parent basis vectors; is the parent difference vector; S represents the scaling factor; r1, r2, and r3 represent three different indexes randomly selected from the index of the current financial data sample set.

5. A multi-cloud management platform with comprehensive financial management functions according to claim 3, characterized in that: Using the analysis algorithm to perform a new cluster analysis on the financial feature data samples, determine the cluster where each financial feature data sample is located and the optimal distance between samples, including: Randomly select K financial feature data samples from the financial feature data sample set as the center points of the initial cluster; Assign each unassigned financial feature data sample to the cluster center point closest to it; Randomly select a financial feature data sample that is not a cluster center from the financial feature data sample set, and record it as a random financial feature data sample; Calculate the total cost change caused by replacing the current cluster center point with a random financial feature data sample, and update the cluster center set; When the cluster center point no longer changes, the final cluster of each financial feature data sample is determined, and the optimal distance between each financial feature data sample is calculated.

6. A multi-cloud management platform with comprehensive financial management functions according to claim 1, characterized in that: The budget control unit includes: a data analysis module, a budget allocation module and a strategy adjustment module; Data analysis module, used to analyze the impact of financial characteristic data and key factors on cloud service costs and benefits; Budget allocation module, which is used to allocate budgets to different cloud platforms and services based on the impact, ensuring that resources are allocated effectively; The strategy adjustment module is used to monitor market trends, cloud service usage and financial performance, and adjust strategies or budget allocations in a timely manner based on performance to adapt to market changes and business needs.

7. A multi-cloud management platform with comprehensive financial management functions according to claim 1, characterized in that: The bill processing unit includes: abnormal consumption identification module, cost optimization evaluation module, and report generation module; Abnormal consumption identification module, used to analyze bill data and identify abnormal consumption characteristics; Cost optimization evaluation module, which is used to analyze the current cost-benefit ratio and make cost optimization suggestions based on preset evaluation criteria and thresholds; Report generation module for generating detailed customer and internal financial reports based on proposed cost optimization recommendations.

8. A multi-cloud management platform with comprehensive financial management functions according to claim 1, characterized in that: The security and compliance unit includes: data encryption module, access control management module, risk assessment and management module and data backup and recovery module; Data encryption module, used to encrypt stored and transmitted financial data to ensure that the data remains confidential in the event of unauthorized access; Access control management module, used to manage user permissions to ensure that only authorized personnel can access financial data and billing information; Risk assessment and management module, which is used to regularly assess and identify potential security risks associated with the use of cloud services, and to design and implement corresponding risk mitigation strategies and control measures; Data backup and recovery module, used to regularly back up financial data and billing information and ensure rapid recovery in case of data loss or damage.

9. The multi-cloud management platform with comprehensive financial management function according to claim 1, characterized in that: The user interaction unit includes: an interface display module, a user input processing module, a user customization module, and a security and authority management module; The interface display module is responsible for presenting the user interface and enabling users to intuitively view cloud service information, billing data, and cost optimization reports; The user input processing module is used to process user input and ensure that user operations can be correctly transmitted to the backend system for processing; User customization module is used to allow users to customize the interface and functions according to their own needs to improve the user experience; The security and permission management module is used to manage user login verification and permission control to ensure data security and privacy protection for users on various cloud platforms.

10. A multi-cloud management platform with comprehensive financial management functions according to claim 1, characterized in that: The monitoring and alarm unit includes: the monitoring and alarm unit includes: resource usage monitoring module, cost tracking module and budget management and alarm module; Resource usage monitoring module, which is used to track and monitor resource usage on the cloud platform and provide real-time data and historical usage trends; Cost tracking module, which monitors the costs and expenditures of the cloud platform and helps identify cost-saving opportunities by analyzing the expenses of different services, projects or departments; Budget management and alerting module allows setting budget limits and sends alert notifications when the predetermined budget is approached or exceeded.

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