CN114282919A - Cloud sea resource charging dynamic cost analysis optimization method and system - Google Patents
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Abstract
The invention provides a dynamic cost analysis and optimization method and a dynamic cost analysis and optimization system for cloud sea resource charging, which can change the traditional physical disk granularity into the charging resource granularity in a resource measurement charging cost analysis and optimization mode, can independently perform measurement charging on a large number of running resource instances on a single physical storage of a third-party platform according to each measurement charging index, provide analysis and optimization suggestions of the use condition and analysis and optimization suggestions of the cost condition for each running resource, can effectively manage the resources according to the result of the resource measurement charging, have uniform knowledge on the resource use condition of the platform resource, provide basic support for the expansion and reduction of the resource, and finally realize the effective utilization of the physical resource.
Description
Technical Field
The invention relates to the technical field of cloud computing data centers, in particular to a dynamic cost analysis optimization method and system for cloud sea resource charging.
Background
In the cloud computing era, with the increasingly wide application field of cloud services, for a public cloud computing platform, only three services of computing, networking and storage are often insufficient, and under the background that the internet is applied in hundreds of flowers at present, the cloud resource information computing consumption and cost technology is also one of the key technologies of the cloud computing platform and plays a crucial role in the cloud computing platform. In addition, under the background that big data analysis is more and more prevalent, reliable and convenient management of metering and charging of cloud resources becomes more important. Therefore, the cloud resource metering and charging can be organized into an important service for creating value for users by the cloud computing platform, however, it is not enough to merely meter and charge the resources in the cloud computing platform, and there is a need for analyzing the usage and cost of the resources by the user, including but not limited to which resource index usage analysis (usage analysis of indexes such as CPU, memory, and storage) of a certain resource, which resource index cost analysis (cost analysis of indexes such as CPU, memory, and storage) of a certain resource, so that the user can visually see the usage of the whole resources of the system and the consumption of the resources, the user can adjust the system resource, such as a series of optimization operations like increasing configuration and decreasing configuration, therefore, the metering charging cost analysis of the resources is also organized into another important service which is used by the cloud computing platform to create value for the user.
Disclosure of Invention
The invention aims to provide a dynamic cost analysis and optimization method and a dynamic cost analysis and optimization system for cloud sea resource charging, which aim to solve the problem that the use amount condition of the whole resources of the system and the consumption condition of the resources cannot be visually seen in the prior art, realize effective management of the resources according to the result of resource measurement charging and improve the effective utilization rate of the resources.
In order to achieve the technical purpose, the invention provides a dynamic cost analysis and optimization method for charging cloud sea resources, which comprises the following operations:
configuring a cloud sea environment and initializing charging related parameters;
configuring a running charging resource timing acquisition task, inquiring and acquiring charging resource list data and resource operation list data according to an interface, filtering and converting the acquired resource data, and inquiring the real usage amount of resources according to the acquired resource data;
configuring and operating a charging resource timing metering task, calculating the use amount of each index of the current charging resource type according to the charging resource metering index set and the metering type of the charging resource by using the resource operation list data of all charging resource types, calculating the real use amount of each index of each resource according to the real use amount data of the resource index and the use amount data of the resource index, and generating resource use statistical data according to the current resource use amount and the real use amount;
configuring a running charging resource timing charging task, calculating the cost of each index usage of the current charging resource type according to the resource usage list data of all the current charging resource types, the charging type and the index unit price according to the charging resource charging index set, the charging type and the index unit price, calculating the real cost of each index of each resource according to the real resource index usage and the index unit price, and generating the cost statistical data of the resource usage according to the current resource cost and the real cost;
and (4) in the cloud environment, resources for optimization suggestion are given according to the statistical needs of cost analysis parameters.
Preferably, the charging related parameters include a resource type to be charged, a resource state, an interface parameter, an interface return object, and an interface object data conversion mode.
Preferably, the charging resource list data and the resource operation list data need to be processed, including:
processing the inquired charging resource list data, filtering the state of the charging resource list data, removing the list data in an invalid state, converting other data into an acquisition object, and setting the attribute of the acquisition object;
processing the charging resource operation list data in the inquired life cycle, filtering the operation of the charging resource list data, removing the list data of invalid operation, setting the attribute of the acquisition object by taking other data states as the acquisition object, and updating the resource name, the user and the resource index detail according to different types of operation.
Preferably, the querying the real usage of the resource according to the collected resource data specifically includes:
traversing all resource data in the current metering and charging period, inquiring historical data of the usage amount of each index of each resource, and acquiring an average numerical value of the usage amount;
and processing all inquired real usage conditions of the charging resources, and setting real usage data of each index of each resource in the current metering and charging period.
Preferably, the attributes of the collection object include resource type, domain, department, VDC, user, resource name, resource operation, resource index details, and resource operation time.
The invention also provides a dynamic cost analysis and optimization system for charging cloud sea resources, which comprises:
the environment configuration module is used for configuring a cloud environment and initializing charging related parameters;
the timing acquisition module is used for configuring a running charging resource timing acquisition task, inquiring and acquiring charging resource list data and resource operation list data according to the interface, filtering and converting the acquired resource data, and inquiring the real use amount of the resource according to the acquired resource data;
the timing metering module is used for configuring and operating the charging resource timing metering task, calculating the use amount of each index of the current charging resource type according to the charging resource metering index set and the metering type of the charging resource by using the resource operation list data of all charging resource types, calculating the real use amount of each index of each resource according to the real use amount data of the resource index and the use amount data of the resource index, and generating resource use statistical data according to the current resource use amount and the real use amount;
the timing charging module is used for configuring a running charging resource timing charging task, calculating the cost of each index usage of the current charging resource type according to the resource usage list data of all the current charging resource types, the charging type and the index unit price according to the charging resource charging index set, the charging type and the index unit price, calculating the real cost of each index of each resource according to the real resource index usage and the index unit price, and generating the cost statistical data of the resource usage according to the current resource cost and the real cost;
and the cost analysis module is used for giving out resources of optimization suggestions according to the statistical needs of cost analysis parameters in the cloud environment.
Preferably, the charging related parameters include a resource type to be charged, a resource state, an interface parameter, an interface return object, and an interface object data conversion mode.
Preferably, the attributes of the collection object include resource type, domain, department, VDC, user, resource name, resource operation, resource index details, and resource operation time.
The effect provided in the summary of the invention is only the effect of the embodiment, not all the effects of the invention, and one of the above technical solutions has the following advantages or beneficial effects:
compared with the prior art, the method can change the analysis and optimization mode of the resource measurement charging cost from the traditional physical disk granularity to the charging resource granularity, can independently perform all the running large number of resource instances on a single physical storage of a measurement charging third-party platform according to each measurement charging index, provides analysis and optimization suggestions of the use condition and analysis and optimization suggestions of the cost condition for each running resource, can effectively manage the resources according to the result of the resource measurement charging, has uniform understanding on the resource use condition of the platform resource, provides basic support for the expansion and reduction of the resources, and finally realizes the effective utilization of the physical resources.
Drawings
Fig. 1 is a flowchart of a dynamic cost analysis and optimization method for charging cloud resources according to an embodiment of the present invention;
fig. 2 is a block diagram of a dynamic cost analysis and optimization system for cloud resource billing according to an embodiment of the present invention.
Detailed Description
In order to clearly explain the technical features of the present invention, the following detailed description of the present invention is provided with reference to the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and procedures are omitted so as to not unnecessarily limit the invention.
The method and system for cloud sea resource billing dynamic cost analysis optimization provided by the embodiments of the present invention are described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the present invention discloses a dynamic cost analysis and optimization method for cloud resources charging, which comprises the following operations:
configuring a cloud sea environment and initializing charging related parameters;
configuring a running charging resource timing acquisition task, inquiring and acquiring charging resource list data and resource operation list data according to an interface, filtering and converting the acquired resource data, and inquiring the real usage amount of resources according to the acquired resource data;
configuring and operating a charging resource timing metering task, calculating the use amount of each index of the current charging resource type according to the charging resource metering index set and the metering type of the charging resource by using the resource operation list data of all charging resource types, calculating the real use amount of each index of each resource according to the real use amount data of the resource index and the use amount data of the resource index, and generating resource use statistical data according to the current resource use amount and the real use amount;
configuring a running charging resource timing charging task, calculating the cost of each index usage of the current charging resource type according to the resource usage list data of all the current charging resource types, the charging type and the index unit price according to the charging resource charging index set, the charging type and the index unit price, calculating the real cost of each index of each resource according to the real resource index usage and the index unit price, and generating the cost statistical data of the resource usage according to the current resource cost and the real cost;
and (4) in the cloud environment, resources for optimization suggestion are given according to the statistical needs of cost analysis parameters.
The embodiment of the invention can reasonably and simply complete the realization of the resource metering charging dynamic cost analysis optimization model through simple operation and reasonable platform construction, has low coupling and high expansibility, dynamically provides the running usage analysis result and the running cost analysis result of the resource for the user, saves the cost of the host resource for the user, and is convenient for the user to manage the third party resource under the cloud platform.
The initialization of basic data is completed by initializing the resource type, interface parameter, interface return object, interface object data conversion mode and the like which need to be charged through the script. Calling the resource list to obtain the first resource list data, completing the operation of incrementally acquiring the charging resources, converting all the acquired data, and completing the operation of acquiring the charging resources. The charging resource usage amount timing task fills collected operation data by collecting real usage amount of resources in monitoring, the charging resource metering timing task collects operation data of all current charging resources, calculates usage amount information and real usage amount information of the charging resources in a current metering period, after the metering timing task of the charging resources is executed, the charging timing task of the charging resources inquires charging resource metering data needing to be charged according to unit price opening time of the charging resources, calculates charge of the charging resources and real resource usage charge according to the inquired charging resource metering data and the unit price multiplied by the usage amount, users define index percentage of cost analysis, generates cost analysis result according to cost analysis parameter percentage, performs cost analysis according to the usage amount information of the resources, the real usage amount information, the charge information and the real charge information, and gives analysis of the current resources And optimization recommendations.
And the cloud sea environment is configured, so that each module in the environment can operate normally.
Initializing the resource type, resource state, interface parameter, interface return object and interface object data conversion mode to be charged.
And configuring and operating a charging resource timing acquisition task in the cloud environment.
Adding a charging resource acquisition task in a task list in a cloud environment, and configuring a task for charging resource timing acquisition; inquiring the charging resource interface configuration according to the initialization script configuration, and inquiring a charging resource list according to the interface; inquiring resource operation data of a life cycle according to the operation of all charging resources needing to be acquired and configured by the initialization script; configuring and processing the inquired charging resource list data and resource operation list data according to the initialization script, wherein the method comprises the following steps:
processing the inquired charging resource list data, filtering the state of the charging resource list data, removing the list data in an invalid state, converting other data into an acquisition object, and setting the attribute of the acquisition object, such as resource type, domain, department, VDC, user, resource name, resource operation, resource index detail and resource operation time; processing the inquired charging resource operation list data in the life cycle, filtering the operation of the charging resource list data, removing the list data of invalid operation, setting the attributes of the acquisition object, such as resource type, domain, department, VDC, user, resource name, resource operation, resource index detail (type, CPU, memory, storage, network card, floating IP) and resource operation time, and updating the resource name, user and resource index detail according to different types of operation, wherein other data states are the acquisition object.
Acquiring resource data according to all the inquired resource data, and inquiring the real use amount condition of the resources, wherein the method comprises the following steps:
traversing all resource data in the current metering and charging period, inquiring historical data of the usage amount of each index of each resource, and acquiring an average numerical value of the usage amount;
and processing all inquired real usage conditions of the charging resources, and setting real usage data of each index of each resource in the current metering and charging period.
And configuring and operating a charging resource timing metering task in the cloud sea environment.
Adding a charging resource metering task in a task list in a cloud environment, and configuring a task of timing metering of charging resources;
and executing a metering task, determining whether the current metering is the first metering or the periodic metering, if the current charging resource type has no metering data, indicating that the current metering is the first metering, and if the current charging resource type has the metering data, indicating that the current metering is the periodic metering. If the measurement is the first measurement, the resource operation list data of all the current charging resource types are inquired, calculating the usage of each index of the charging resource type resource according to the configured charging resource metering index set and the configured metering type of the charging resource, storing the generated use case of each index of the resource of the charging resource type in a database, then calculating the actual use condition of each index of each current resource according to the collected resource index actual use data and the resource index use data, generating statistical data of resource usage according to the current resource usage and the real usage, and then, completing optimization suggestion according to the actual condition of the resource usage, for example, for a certain resource, CPU configuration should be increased/decreased, memory configuration should be increased/decreased, and storage configuration should be increased/decreased.
And configuring and operating a charging resource timing charging task in the cloud environment.
Adding a charging resource charging task in a task list in the cloud environment, and configuring a task for charging the charging resource at regular time;
and executing a charging task, determining whether the current charging is the first charging or the periodic charging, if the current charging resource type resource has no charge data, indicating that the current charging is the first charging, and if the current charging resource type resource has the charge data, indicating that the current charging is the periodic charging. If the charging is the first charging, inquiring the resource usage list data of all the charging resource type resources at present, calculating the usage cost of each index of the charging resource type resources according to the configured charging resource charging index set, the configured charging type of the calculation resources and the configured index unit price of the charging resources, then storing the generated usage cost of each index of the charging resource type resources in a database, then calculating the real cost using condition of each index of each current resource according to the acquired resource index real usage data and the resource index unit price data, generating the resource usage cost statistical data according to the cost using condition of each current resource and the real cost using condition, completing optimization suggestion according to the real resource cost using condition, such as increasing CPU configuration/reducing CPU configuration aiming at a certain resource cost, memory allocation is increased/decreased, and storage allocation is increased/decreased.
Cost analysis data is dynamically generated in a cloud environment.
The default of cost analysis parameters (CPU cost analysis parameter proportion and memory cost analysis parameter proportion) is 60%, if the CPU usage cost in the bill of one resource is less than 60% of the allocation cost or the memory usage cost is less than 60% of the allocation cost, the resource is the resource needing to give optimization suggestion, all the resources needing to give optimization suggestion are counted, and cost analysis data are generated; the cost analysis parameters can also be configured in a customized way.
The user regenerates the metering and charging data through the reset function, the super administrator can reset the metering and charging data through the charging reset function, the consumption data and the bill data of all resources can be deleted after the reset, the system can record the reset time, the resources are collected again according to the reset time as the starting time of the metering and charging, the metering and charging data are generated, and finally the cost analysis data are generated.
The embodiment of the invention can change the analysis and optimization mode of the resource measurement charging cost from the traditional physical disk granularity into the charging resource granularity, can independently carry out analysis and optimization suggestions of the use condition and the cost condition of each running resource on a single physical storage of a measurement charging third-party platform according to each measurement charging index, can effectively manage the resources according to the result of the resource measurement charging, has uniform understanding on the resource use condition of the platform resources, provides basic support for the expansion and reduction of the resources, and finally realizes the effective utilization of the physical resources.
As shown in fig. 2, an embodiment of the present invention further discloses a dynamic cost analysis and optimization system for cloud resource billing, where the system includes:
the environment configuration module is used for configuring a cloud environment and initializing charging related parameters;
the timing acquisition module is used for configuring a running charging resource timing acquisition task, inquiring and acquiring charging resource list data and resource operation list data according to the interface, filtering and converting the acquired resource data, and inquiring the real use amount of the resource according to the acquired resource data;
the timing metering module is used for configuring and operating the charging resource timing metering task, calculating the use amount of each index of the current charging resource type according to the charging resource metering index set and the metering type of the charging resource by using the resource operation list data of all charging resource types, calculating the real use amount of each index of each resource according to the real use amount data of the resource index and the use amount data of the resource index, and generating resource use statistical data according to the current resource use amount and the real use amount;
the timing charging module is used for configuring a running charging resource timing charging task, calculating the cost of each index usage of the current charging resource type according to the resource usage list data of all the current charging resource types, the charging type and the index unit price according to the charging resource charging index set, the charging type and the index unit price, calculating the real cost of each index of each resource according to the real resource index usage and the index unit price, and generating the cost statistical data of the resource usage according to the current resource cost and the real cost;
and the cost analysis module is used for giving out resources of optimization suggestions according to the statistical needs of cost analysis parameters in the cloud environment.
The initialization of basic data is completed by initializing the resource type, interface parameter, interface return object, interface object data conversion mode and the like which need to be charged through the script. Calling the resource list to obtain the first resource list data, completing the operation of incrementally acquiring the charging resources, converting all the acquired data, and completing the operation of acquiring the charging resources. The charging resource usage amount timing task fills collected operation data by collecting real usage amount of resources in monitoring, the charging resource metering timing task collects operation data of all current charging resources, calculates usage amount information and real usage amount information of the charging resources in a current metering period, after the metering timing task of the charging resources is executed, the charging timing task of the charging resources inquires charging resource metering data needing to be charged according to unit price opening time of the charging resources, calculates charge of the charging resources and real resource usage charge according to the inquired charging resource metering data and the unit price multiplied by the usage amount, users define index percentage of cost analysis, generates cost analysis result according to cost analysis parameter percentage, performs cost analysis according to the usage amount information of the resources, the real usage amount information, the charge information and the real charge information, and gives analysis of the current resources And optimization recommendations.
And the cloud sea environment is configured, so that each module in the environment can operate normally.
Initializing the resource type, resource state, interface parameter, interface return object and interface object data conversion mode to be charged.
And configuring and operating a charging resource timing acquisition task in the cloud environment.
Adding a charging resource acquisition task in a task list in a cloud environment, and configuring a task for charging resource timing acquisition; inquiring the charging resource interface configuration according to the initialization script configuration, and inquiring a charging resource list according to the interface; inquiring resource operation data of a life cycle according to the operation of all charging resources needing to be acquired and configured by the initialization script; configuring and processing the inquired charging resource list data and resource operation list data according to the initialization script, wherein the method comprises the following steps:
processing the inquired charging resource list data, filtering the state of the charging resource list data, removing the list data in an invalid state, converting other data into an acquisition object, and setting the attribute of the acquisition object, such as resource type, domain, department, VDC, user, resource name, resource operation, resource index detail and resource operation time; processing the inquired charging resource operation list data in the life cycle, filtering the operation of the charging resource list data, removing the list data of invalid operation, setting the attributes of the acquisition object, such as resource type, domain, department, VDC, user, resource name, resource operation, resource index detail (type, CPU, memory, storage, network card, floating IP) and resource operation time, and updating the resource name, user and resource index detail according to different types of operation, wherein other data states are the acquisition object.
Acquiring resource data according to all the inquired resource data, and inquiring the real use amount condition of the resources, wherein the method comprises the following steps:
traversing all resource data in the current metering and charging period, inquiring historical data of the usage amount of each index of each resource, and acquiring an average numerical value of the usage amount;
and processing all inquired real usage conditions of the charging resources, and setting real usage data of each index of each resource in the current metering and charging period.
And configuring and operating a charging resource timing metering task in the cloud sea environment.
Adding a charging resource metering task in a task list in a cloud environment, and configuring a task of timing metering of charging resources;
and executing a metering task, determining whether the current metering is the first metering or the periodic metering, if the current charging resource type has no metering data, indicating that the current metering is the first metering, and if the current charging resource type has the metering data, indicating that the current metering is the periodic metering. If the measurement is the first measurement, the resource operation list data of all the current charging resource types are inquired, calculating the usage of each index of the charging resource type resource according to the configured charging resource metering index set and the configured metering type of the charging resource, storing the generated use case of each index of the resource of the charging resource type in a database, then calculating the actual use condition of each index of each current resource according to the collected resource index actual use data and the resource index use data, generating statistical data of resource usage according to the current resource usage and the real usage, and then, completing optimization suggestion according to the actual condition of the resource usage, for example, for a certain resource, CPU configuration should be increased/decreased, memory configuration should be increased/decreased, and storage configuration should be increased/decreased.
And configuring and operating a charging resource timing charging task in the cloud environment.
Adding a charging resource charging task in a task list in the cloud environment, and configuring a task for charging the charging resource at regular time;
and executing a charging task, determining whether the current charging is the first charging or the periodic charging, if the current charging resource type resource has no charge data, indicating that the current charging is the first charging, and if the current charging resource type resource has the charge data, indicating that the current charging is the periodic charging. If the charging is the first charging, inquiring the resource usage list data of all the charging resource type resources at present, calculating the usage cost of each index of the charging resource type resources according to the configured charging resource charging index set, the configured charging type of the calculation resources and the configured index unit price of the charging resources, then storing the generated usage cost of each index of the charging resource type resources in a database, then calculating the real cost using condition of each index of each current resource according to the acquired resource index real usage data and the resource index unit price data, generating the resource usage cost statistical data according to the cost using condition of each current resource and the real cost using condition, completing optimization suggestion according to the real resource cost using condition, such as increasing CPU configuration/reducing CPU configuration aiming at a certain resource cost, memory allocation is increased/decreased, and storage allocation is increased/decreased.
Cost analysis data is dynamically generated in a cloud environment.
The default of cost analysis parameters (CPU cost analysis parameter proportion and memory cost analysis parameter proportion) is 60%, if the CPU usage cost in the bill of one resource is less than 60% of the allocation cost or the memory usage cost is less than 60% of the allocation cost, the resource is the resource needing to give optimization suggestion, all the resources needing to give optimization suggestion are counted, and cost analysis data are generated; the cost analysis parameters can also be configured in a customized way.
The user regenerates the metering and charging data through the reset function, the super administrator can reset the metering and charging data through the charging reset function, the consumption data and the bill data of all resources can be deleted after the reset, the system can record the reset time, the resources are collected again according to the reset time as the starting time of the metering and charging, the metering and charging data are generated, and finally the cost analysis data are generated.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (8)
1. A dynamic cost analysis optimization method for cloud sea resource charging is characterized by comprising the following operations:
configuring a cloud sea environment and initializing charging related parameters;
configuring a running charging resource timing acquisition task, inquiring and acquiring charging resource list data and resource operation list data according to an interface, filtering and converting the acquired resource data, and inquiring the real usage amount of resources according to the acquired resource data;
configuring and operating a charging resource timing metering task, calculating the use amount of each index of the current charging resource type according to the charging resource metering index set and the metering type of the charging resource by using the resource operation list data of all charging resource types, calculating the real use amount of each index of each resource according to the real use amount data of the resource index and the use amount data of the resource index, and generating resource use statistical data according to the current resource use amount and the real use amount;
configuring a running charging resource timing charging task, calculating the cost of each index usage of the current charging resource type according to the resource usage list data of all the current charging resource types, the charging type and the index unit price according to the charging resource charging index set, the charging type and the index unit price, calculating the real cost of each index of each resource according to the real resource index usage and the index unit price, and generating the cost statistical data of the resource usage according to the current resource cost and the real cost;
and (4) in the cloud environment, resources for optimization suggestion are given according to the statistical needs of cost analysis parameters.
2. The cloud resource charging dynamic cost analysis optimization method according to claim 1, wherein the charging related parameters include a resource type to be charged, a resource state, an interface parameter, an interface return object, and an interface object data conversion mode.
3. The cloud resource billing dynamic cost analysis optimization method of claim 1, wherein the billing resource list data and the resource operation list data need to be processed, comprising:
processing the inquired charging resource list data, filtering the state of the charging resource list data, removing the list data in an invalid state, converting other data into an acquisition object, and setting the attribute of the acquisition object;
processing the charging resource operation list data in the inquired life cycle, filtering the operation of the charging resource list data, removing the list data of invalid operation, setting the attribute of the acquisition object by taking other data states as the acquisition object, and updating the resource name, the user and the resource index detail according to different types of operation.
4. The cloud resource billing dynamic cost analysis optimization method according to claim 1, wherein the querying of the actual usage of resources according to the collected resource data specifically comprises:
traversing all resource data in the current metering and charging period, inquiring historical data of the usage amount of each index of each resource, and acquiring an average numerical value of the usage amount;
and processing all inquired real usage conditions of the charging resources, and setting real usage data of each index of each resource in the current metering and charging period.
5. The cloud resource billing dynamic cost analysis optimization method of claim 3, wherein the attributes of the collection object include resource type, domain, department, VDC, user, resource name, resource operation, resource index details, and resource operation time.
6. A cloud resource billing dynamic cost analysis optimization system, the system comprising:
the environment configuration module is used for configuring a cloud environment and initializing charging related parameters;
the timing acquisition module is used for configuring a running charging resource timing acquisition task, inquiring and acquiring charging resource list data and resource operation list data according to the interface, filtering and converting the acquired resource data, and inquiring the real use amount of the resource according to the acquired resource data;
the timing metering module is used for configuring and operating the charging resource timing metering task, calculating the use amount of each index of the current charging resource type according to the charging resource metering index set and the metering type of the charging resource by using the resource operation list data of all charging resource types, calculating the real use amount of each index of each resource according to the real use amount data of the resource index and the use amount data of the resource index, and generating resource use statistical data according to the current resource use amount and the real use amount;
the timing charging module is used for configuring a running charging resource timing charging task, calculating the cost of each index usage of the current charging resource type according to the resource usage list data of all the current charging resource types, the charging type and the index unit price according to the charging resource charging index set, the charging type and the index unit price, calculating the real cost of each index of each resource according to the real resource index usage and the index unit price, and generating the cost statistical data of the resource usage according to the current resource cost and the real cost;
and the cost analysis module is used for giving out resources of optimization suggestions according to the statistical needs of cost analysis parameters in the cloud environment.
7. The cloud resource billing dynamic cost analysis optimization system according to claim 6, wherein the billing related parameters include a resource type to be billed, a resource state, an interface parameter, an interface return object, and an interface object data conversion method.
8. The cloud resource billing dynamic cost analysis optimization system of claim 6, wherein the attributes of the collection object include resource type, domain, department, VDC, user, resource name, resource operation, resource index details, and resource operation time.
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