Method, device, equipment and storage medium for determining cloud service implementation strategy

Abstract

The present disclosure provides a method for determining a cloud service implementation strategy, which can be applied to the cloud computing field, the financial field, or other fields. The method includes: setting a scheduled task, wherein the scheduled task includes initiating a data collection instruction at intervals of a preset time period; in response to the data collection instruction, obtaining the first historical implementation time consumption data of the target cloud service; performing a stability analysis on the first historical implementation time consumption data to obtain the implementation stability parameter of the target cloud service; based on the implementation stability parameter, determining the target implementation strategy of the target cloud service from a policy library, wherein the policy library includes a variety of implementation strategies suitable for different implementation stability parameters; and using the target implementation strategy to replace the original implementation strategy of the target cloud service. In addition, the present disclosure also provides a device for determining a cloud service implementation strategy, an electronic device, and a readable storage medium.

Description

Technical Field

[0001] The present disclosure relates to the fields of cloud computing and finance, and more specifically, to a method, apparatus, device, storage medium, and program product for determining a cloud service implementation strategy. Background Art

[0002] With the rapid development of computer and network technologies, modern society has entered the information age, and the demand for efficient and fast integration, management, development and utilization of information resources is increasing day by day. At the same time, with the development of the Internet of Things, information management has become more complex, the requirements for computing power have increased, and the data to be managed has become increasingly large, which has led to the increasing costs of technologies such as security assurance and daily operation and maintenance of information management systems. The emergence of "cloud computing" can achieve informationization methods with low cost and high returns. Cloud services refer to the supply, change, and recovery services provided by cloud computing management products to users, such as applying for virtual machines, mounting disks, installing software, and virtual machine recovery. These services are like goods placed on shelves and are provided by product providers.

[0003] In the process of realizing the concept of the present disclosure, the inventors found that there are at least the following problems in the related technology: the determination of cloud service implementation strategy depends on the work experience of business personnel. As the number and complexity of cloud services increase, the feasibility of relying on personnel experience to judge service implementation is poor. Summary of the invention

[0004] In view of this, the present disclosure provides a method for determining a cloud service implementation policy, an apparatus for determining a cloud service implementation policy, an electronic device, a readable storage medium, and a computer program product.

[0005] According to a first aspect of the present disclosure, there is provided a method for determining a cloud service implementation strategy, comprising:

[0006] Setting a scheduled task, wherein the scheduled task includes initiating a data collection instruction at every preset time interval;

[0007] In response to the data collection instruction, obtaining first historical implementation time consumption data of the target cloud service;

[0008] Performing stability analysis on the first historical implementation time consumption data to obtain implementation stability parameters of the target cloud service;

[0009] Based on the implementation stability parameter, determining a target implementation strategy for the target cloud service from a strategy library, wherein the strategy library includes multiple implementation strategies applicable to different implementation stability parameters; and

[0010] The target implementation policy is used to replace the original implementation policy of the target cloud service.

[0011] According to an embodiment of the present disclosure, the stability analysis of the first historical implementation time consumption data to obtain the implementation stability parameter of the target cloud service includes:

[0012] An outlier filtering method is used to filter out outliers in the first historical implementation time consumption data to obtain second historical implementation time consumption data;

[0013] Determine the historical implementation quantity of the target cloud service based on the second historical implementation time consumption data; and

[0014] When the above-mentioned historical implementation quantity is greater than or equal to a preset value, the above-mentioned second historical implementation time-consuming data and the above-mentioned historical implementation quantity are input into a preset probability model, and the above-mentioned implementation stability parameter is outputted.

[0015] According to an embodiment of the present disclosure, the second historical implementation time consumption data and the historical implementation quantity are input into a preset probability model, and the implementation stability parameter is output, including:

[0016] According to the above second historical implementation time data and the above historical implementation quantity, the historical implementation time average is calculated;

[0017] The standard deviation of the historical implementation time is calculated based on the above historical implementation time average, the above second historical implementation time data and the above historical implementation quantity;

[0018] Determine a stability coefficient based on the historical implementation time average and a preset coefficient function; and

[0019] Based on the above historical implementation time standard deviation and the above stability coefficient, the above implementation stability parameter is determined.

[0020] According to an embodiment of the present disclosure, the preset coefficient function includes a non-negative monotonically increasing function.

[0021] According to an embodiment of the present disclosure, the method for determining a cloud service implementation strategy further includes:

[0022] When the above historical implementation quantity is less than the above preset value, the above implementation stability parameter is determined to be the preset stability parameter.

[0023] According to an embodiment of the present disclosure, it also includes:

[0024] Storing the above implementation stability parameters in a database;

[0025] In response to the display instructions for the plurality of target cloud services, obtaining implementation stability parameters of the plurality of target cloud services from the database; and

[0026] The implementation stability parameters of the above-mentioned multiple target cloud services are displayed in a preset data format.

[0027] According to an embodiment of the present disclosure, the implementation strategy of the target cloud service includes starting the implementation of the target cloud service by a preset time in advance based on the standard implementation time of the target cloud service.

[0028] According to a second aspect of the present disclosure, there is provided an apparatus for determining a cloud service implementation strategy, comprising:

[0029] A timing module is used to set a timing task, wherein the timing task includes initiating a data collection instruction at every preset time interval;

[0030] A first acquisition module, configured to acquire first historical implementation time consumption data of a target cloud service in response to the data collection instruction;

[0031] An analysis module, configured to perform stability analysis on the first historical implementation time consumption data to obtain implementation stability parameters of the target cloud service;

[0032] a processing module, configured to determine a target implementation strategy of the target cloud service from a strategy library based on the implementation stability parameter, wherein the strategy library includes a plurality of implementation strategies applicable to different implementation stability parameters; and

[0033] The replacement module is used to replace the original implementation strategy of the above target cloud service with the above target implementation strategy.

[0034] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0035] one or more processors;

[0036] a memory for storing one or more instructions,

[0037] When the one or more instructions are executed by the one or more processors, the one or more processors implement the method.

[0038] According to a fourth aspect of the present disclosure, a computer-readable storage medium is provided, on which executable instructions are stored. When the executable instructions are executed by a processor, the processor implements the method.

[0039] According to a fifth aspect of the present disclosure, a computer program product is provided, the computer program product comprising computer executable instructions, and the computer executable instructions are used to implement the method when executed.

[0040] According to the embodiments of the present disclosure, because a technical means is adopted to analyze the implementation stability parameters of the cloud service by collecting historical implementation time consumption data and to select the implementation strategy based on the implementation stability parameters, it at least partially overcomes the technical problem in the related technology that the determination of the cloud service implementation strategy usually depends on the work experience of the business personnel, thereby achieving the technical effect of effectively reducing the degree of dependence of the selection of the implementation strategy on the work experience of the business personnel and improving the reliability of the implementation of the business. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0042] Figure 1 A system architecture diagram schematically illustrates a method for determining a cloud service implementation strategy according to an embodiment of the present disclosure to which the method can be applied;

[0043] Figure 2 A flowchart of a method for determining a cloud service implementation strategy according to an embodiment of the present disclosure is schematically shown;

[0044] Figure 3 A flow chart of a stability analysis method according to an embodiment of the present disclosure is schematically shown;

[0045] Figure 4 A flowchart of a method for determining and implementing stability parameters according to an embodiment of the present disclosure is schematically shown;

[0046] Figure 5 A flowchart of a display method according to another embodiment of the present disclosure is schematically shown;

[0047] Figure 6 A structural block diagram schematically shows a device for determining a cloud service implementation strategy according to an embodiment of the present disclosure; and

[0048] Figure 7 A block diagram of an electronic device suitable for implementing a method for determining a cloud service implementation strategy according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0049] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0050] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0051] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0052] In the case of using expressions such as "at least one of A, B, and C, etc.", it should generally be interpreted in accordance with the meaning of the expression generally understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.). In the case of using expressions such as "at least one of A, B, or C, etc.", it should generally be interpreted in accordance with the meaning of the expression generally understood by those skilled in the art (for example, "a system having at least one of A, B, or C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0053] In the technical solution disclosed in the present invention, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations, necessary confidentiality measures are taken, and do not violate public order and good morals.

[0054] With the rapid development of technologies such as computers and the Internet of Things, information management has become more complex, and the requirements for computing power are increasing. The emergence of "cloud computing" can realize information methods at low cost and high return. In the field of cloud computing, cloud management refers to cloud computing management products, which are platform products used to manage infrastructure and provide cloud services to users. Cloud services refer to the supply, change, and recovery services provided by cloud computing management products to users, such as applying for virtual machines, mounting disks, installing software, and recovering virtual machines. These services are like goods placed on shelves and are provided by product providers. Implementation refers to the implementation of cloud services (also known as supply), which refers to the process of executing the steps and processes after the cloud services applied by users are disassembled into technical implementation steps and processes (Orchestration). From a broad classification perspective, cloud services can be divided into IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service). Each category contains many cloud services, and the implementation process of each cloud service is different. Although users combine the various services they apply for and use them together, in the implementation stage, cloud services are relatively independent. To provide a new cloud service, it is necessary to design and implement the implementation steps and processes of the cloud service. This is an important technical implementation link of the cloud service. Depending on the cloud service, the complexity of the implementation steps and processes will vary, and the time required to execute the steps and processes will also vary.

[0055] In the relevant technologies, the implementation of current cloud management products requires the management and implementation personnel and technical support personnel of the relevant services to pay real-time attention to the implementation process, and promptly handle and solve the problems that arise to ensure the normal and timely completion of the implementation; it is also necessary to have personnel with relevant experience to conduct research and judgment on it, so as to arrange personnel and time in advance to support it. However, early research and judgment requires relevant personnel to have rich knowledge and experience accumulation, and the degree of dependence on people is high; if the implementation to be executed is not judged, or it is impossible to judge the implementation, then the service implementation will be in a passive situation as to whether it can be completed on time; and as the number and complexity of cloud services increase, the feasibility of relying entirely on personnel experience to judge the implementation of services will gradually decrease.

[0056] In order to at least partially solve the technical problems existing in the related art, the present disclosure provides a method for determining a cloud service implementation strategy, which can be applied to the cloud computing field and the financial field. The method for determining a cloud service implementation strategy includes: in response to a data collection instruction, obtaining the first historical implementation time consumption data of the target cloud service; performing a stability analysis on the first historical implementation time consumption data to obtain the implementation stability parameter of the target cloud service; based on the implementation stability parameter, determining the implementation strategy of the target cloud service from a policy library, wherein the policy library includes a plurality of implementation strategies applicable to different implementation stability parameters. The present disclosure also provides a device, an electronic device, a computer storage medium, and a computer program product for determining a cloud service implementation strategy.

[0057] It should be noted that the method and apparatus for determining the cloud service implementation strategy provided by the embodiments of the present disclosure can be used in the cloud computing field or the financial field. For example, the stability of the cloud service can be evaluated based on the cloud service implementation data accumulated in the banking product system as a sample. The method and apparatus for determining the cloud service implementation strategy provided by the embodiments of the present disclosure can also be used in any field other than the cloud computing field and the financial field. The application field of the method and apparatus for determining the cloud service implementation strategy provided by the embodiments of the present disclosure is not limited.

[0058] Figure 1 The system architecture 100 to which the method for determining a cloud service implementation strategy according to an embodiment of the present disclosure can be applied is schematically shown. It should be noted that: Figure 1 What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0059] like Figure 1 As shown, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired and / or wireless communication links, etc.

[0060] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients and / or social platform software, etc. (only as examples).

[0061] The terminal devices 101 , 102 , and 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0062] The server 105 may be a server that provides various services, such as a background management server (only an example) that provides support for websites browsed by users using the terminal devices 101, 102, and 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0063] It should be noted that the method for determining the cloud service implementation strategy provided by the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the device for determining the cloud service implementation strategy provided by the embodiment of the present disclosure can generally be set in the server 105. The method for determining the cloud service implementation strategy provided by the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal device 101, 102, 103 and / or the server 105. Correspondingly, the device for determining the cloud service implementation strategy provided by the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the terminal device 101, 102, 103 and / or the server 105. Alternatively, the method for determining the cloud service implementation strategy provided by the embodiment of the present disclosure can also be executed by the terminal device 101, 102, or 103, or can also be executed by other terminal devices different from the terminal device 101, 102, or 103. Correspondingly, the apparatus for determining a cloud service implementation strategy provided by the embodiments of the present disclosure may also be disposed in the terminal device 101 , 102 , or 103 , or in another terminal device different from the terminal device 101 , 102 , or 103 .

[0064] For example, the historical implementation time consumption data may be originally stored in any one of the terminal devices 101, 102, or 103 (for example, the terminal device 101, but not limited thereto), or stored in an external storage device and may be imported into the terminal device 101. Then, the terminal device 101 may locally execute the method for determining the cloud service implementation strategy provided by the embodiment of the present disclosure, or send the data collection instruction to other terminal devices, servers, or server clusters, and the other terminal devices, servers, or server clusters that receive the data collection instruction may execute the method for determining the cloud service implementation strategy provided by the embodiment of the present disclosure.

[0065] It should be understood that Figure 1The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0066] Figure 2 The flowchart of the method for determining a cloud service implementation strategy according to an embodiment of the present disclosure is schematically shown.

[0067] like Figure 2 As shown, the method for determining a cloud service implementation strategy in this embodiment includes operations S201 to S203.

[0068] In operation S201, a timed task is set, wherein the timed task includes initiating a data collection instruction at intervals of a preset time period.

[0069] According to an embodiment of the present disclosure, setting a timed task may be, for example, setting a timer to execute a task action at intervals of a preset time period.

[0070] According to an embodiment of the present disclosure, a data query and collection module may execute a data collection instruction to query and collect the historical implementation target quantity and historical implementation time consumption data of each cloud service.

[0071] According to an embodiment of the present disclosure, the historical implementation time consumption data of each cloud service collected by the query can be transferred to a subsequent process for use.

[0072] In operation S202 , in response to a data collection instruction, first historical implementation time consumption data of a target cloud service is obtained.

[0073] According to an embodiment of the present disclosure, cloud service may be a service provided to terminal users in cloud computing.

[0074] According to an embodiment of the present disclosure, cloud services may include provisioning, changing, and recycling services provided by cloud computing management products to users, such as applying for virtual machines, mounting disks, installing software, and recycling virtual machines. These services are like merchandise placed on shelves and are provided by product providers.

[0075] According to an embodiment of the present disclosure, the target cloud service may be, for example, creating a virtual machine, installing and upgrading software on the target virtual machine, etc.

[0076] According to an embodiment of the present disclosure, the first historical implementation time-consuming data may be, for example, the time consumed in the process of completing a series of operations of the applied cloud service.

[0077] In operation S203, a stability analysis is performed on the first historical implementation time consumption data to obtain an implementation stability parameter of the target cloud service.

[0078] According to an embodiment of the present disclosure, the stability analysis may be, for example, the degree of concentration of multiple implementation times. The more concentrated the implementation time is, the better the stability of the target cloud service is.

[0079] According to the embodiments of the present disclosure, the implementation stability parameters can be based on the cloud services provided by the cloud computing management platform products, and the historical implementation time of each cloud service can be used as sample data to measure its stability. The stability of the cloud services can be calculated, and the implementation stability parameters of each cloud service can be output as the basis for judging the stability of the cloud services.

[0080] In operation S204, based on the implementation stability parameter, a target implementation policy of the target cloud service is determined from a policy library, wherein the policy library includes a plurality of implementation policies applicable to different implementation stability parameters.

[0081] According to the embodiments of the present disclosure, due to various factors such as environmental differences, resource inventory, network fluctuations, rationality of cloud service design, and whether the implementation is fully automated, the implementation time of cloud services is not always the same.

[0082] According to an embodiment of the present disclosure, the policy library may include a variety of implementation policies applicable to different implementation stability parameters.

[0083] In operation S205 , the original implementation policy of the target cloud service is replaced with the target implementation policy.

[0084] According to an embodiment of the present disclosure, the implementation strategy of the target cloud service includes starting the implementation of the target cloud service by a preset time in advance based on the standard implementation time of the target cloud service.

[0085] According to an embodiment of the present disclosure, a timer is set to cycle according to a preset time period, and the timer initiates a data collection instruction to collect historical implementation time-consuming data to analyze the implementation stability parameters of the cloud service. An implementation strategy is selected based on the implementation stability parameters, and a preset time for handling problems is reserved for the implementation process to ensure that the software installation service can be completed on time. This effectively reduces the degree of dependence of the selection of implementation strategies on the work experience of business personnel and improves the reliability of business implementation.

[0086] Figure 3 The flowchart of the stability analysis method according to the embodiment of the present disclosure is schematically shown.

[0087] like Figure 3 As shown, this embodiment performs stability analysis on the first historical implementation time consumption data according to the embodiment of the present disclosure to obtain the implementation stability parameters of the target cloud service, including operations S301 to S303.

[0088] In operation S301, an outlier filtering method is used to filter out outliers in the first historical implementation time consumption data to obtain second historical implementation time consumption data.

[0089] According to an embodiment of the present disclosure, the abnormal value may be, for example, special sample data.

[0090] According to an embodiment of the present disclosure, an abnormal value may be when a number exceeds a certain standard value, and it can be determined whether the maximum or minimum value in the data exceeds the theoretical range value, and whether there are any erroneous values ​​in the data that are obviously inconsistent with the actual situation.

[0091] According to an embodiment of the present disclosure, an outlier may be a value in a set of measured values ​​whose deviation from the mean value exceeds 3 standard deviations. When processing data, according to the properties of normal distribution, data outside three standard deviations can be regarded as erroneous data and thus excluded.

[0092] According to an embodiment of the present disclosure, taking the installation of a cloud service for a certain software as an example, assuming that the implementation time is 30 minutes under normal circumstances, if the network transmission speed fluctuates resulting in a slower speed of sending the software media package, in extreme cases the time required for implementation may even be several times longer than the normal time. In this case, the implementation time data can be determined as an abnormal value.

[0093] According to an embodiment of the present disclosure, the outlier discrimination method may include but is not limited to the Laida criterion method, the Chauville criterion method, the Dixon criterion method, the Romanowski criterion method, the Grubbs criterion method and the range method.

[0094] According to an embodiment of the present disclosure, the outlier filtering method may include but is not limited to Isolation forest, DBSCAN (Density-Based Spatial Clustering of Applications with Noise) principle, OneClassSVM and LOF (Local Outlier Factor).

[0095] According to an embodiment of the present disclosure, the second historical implementation time consumption data is data obtained after filtering out abnormal values ​​in the first historical implementation time consumption data.

[0096] In operation S302 , the historical implementation quantity of the target cloud service is determined based on the second historical implementation time consumption data.

[0097] According to an embodiment of the present disclosure, the historical implementation quantity is the implementation quantity of the second historical implementation time-consuming data obtained after filtering outliers.

[0098] In operation S303, when the historical implementation quantity is greater than or equal to a preset value, the second historical implementation time-consuming data and the historical implementation quantity are input into a preset probability model, and an implementation stability parameter is outputted.

[0099] According to an embodiment of the present disclosure, when the historical implementation quantity is less than a preset value, the implementation stability parameter is determined to be a preset stability parameter.

[0100] According to an embodiment of the present disclosure, the preset value may be sample data of a boundary case, for example, the number of sample data is 0, which means that the target cloud service has not been implemented yet.

[0101] According to the embodiments of the present disclosure, for multiple implementations of a single cloud service, the duration of each implementation is not fixed, but is any point within a certain interval on the time axis. It is not possible to list all possible values ​​one by one, which conforms to the definition of a continuous random variable in probability theory.

[0102] According to the embodiments of the present disclosure, the preset probability model may be a continuous random variable. A continuous random variable is a probability model definition in probability theory. If all possible values ​​of a random variable X cannot be listed one by one, but a random variable at any point in a certain interval on the number axis, then X is called a continuous random variable. For example: the time when a train arrives at a certain station, the height distribution of adult humans, etc.

[0103] According to the embodiments of the present disclosure, special sample data in the sample data can be excluded by setting outliers, thereby obtaining the historical implementation quantity after filtering outliers; boundary conditions in the sample data can be excluded by setting preset values, so that the method can always return the implementation stability parameters, thereby improving the method of selecting the implementation strategy according to the implementation stability parameters.

[0104] Figure 4 The flowchart of the method for determining and implementing stability parameters according to an embodiment of the present disclosure is schematically shown.

[0105] like Figure 4 As shown, in this embodiment, the second historical implementation time consumption data and the historical implementation quantity are input into a preset probability model, and the output to obtain the implementation stability parameter includes operations S401 to S404.

[0106] In operation S401, a historical implementation time average is calculated based on the second historical implementation time data and the historical implementation quantity.

[0107] According to an embodiment of the present disclosure, the historical implementation time average is calculated based on the second historical implementation time data and the historical implementation quantity:

[0108]

[0109] in, is the mean, x i is the time-consuming data of the second historical implementation, and n is the number of historical implementations.

[0110] In operation S402, a standard deviation of the historical implementation time consumption is calculated according to the historical implementation time consumption mean, the second historical implementation time consumption data, and the historical implementation quantity.

[0111] According to an embodiment of the present disclosure, the standard deviation is a measure of the degree of dispersion when the probability theory and statistical variance measure a random variable or a set of data. In probability theory, the variance is used to measure the degree of deviation between a random variable and its mathematical expectation (i.e., the mean). The variance (sample variance) in statistics is the average of the squared values ​​of the difference between each sample value and the mean of all sample values.

[0112] According to an embodiment of the present disclosure, the standard deviation of the historical implementation time consumption is calculated based on the historical implementation time consumption mean, the second historical implementation time consumption data and the historical implementation quantity:

[0113]

[0114] Where σ is the standard deviation, x i It is the time-consuming data of the second historical implementation. is the mean, and n is the number of historical implementations.

[0115] According to an embodiment of the present disclosure, the smaller the standard deviation σ is, the more sample data is concentrated around the mean value, and the better the stability is.

[0116] In operation S403, a stability coefficient is determined based on the historical implementation time average and a preset coefficient function.

[0117] According to an embodiment of the present disclosure, the stability coefficient is to eliminate the numerical difference problem of standard deviations between cloud services, and the calculated standard deviation σ is multiplied by the stability coefficient E.

[0118] According to an embodiment of the present disclosure, the preset coefficient function includes a non-negative monotonically increasing function.

[0119] In operation S404, an implementation stability parameter is determined based on the historical implementation time standard deviation and the stability coefficient.

[0120] According to an embodiment of the present disclosure, the implementation stability parameter is calculated based on the historical implementation time standard deviation and the stability coefficient:

[0121] S=E·σ (3)

[0122] Where S is the implementation stability parameter, E is the stability coefficient, and σ is the standard deviation.

[0123] According to the embodiments of the present disclosure, the implementation stability parameters based on cloud services can truly reflect whether the implementation time of cloud services is stable, improve the operability of cloud service stability assessment, reduce the degree of dependence on product familiarity and experience, and change from relying entirely on people to assessing based on objective score values.

[0124] According to the embodiments of the present disclosure, the stability parameter is a unitless score based on the cloud service dimension, which makes horizontal comparison of the stability between cloud services possible, and uses statistical data to help relevant personnel examine the cloud services from the perspective of stability, thereby promoting the improvement of cloud service stability.

[0125] Figure 5 The flowchart of the display method according to the embodiment of the present disclosure is schematically shown.

[0126] like Figure 5 As shown, the method for determining a cloud service implementation strategy in this embodiment further includes operations S501 to S503.

[0127] In operation S501, implementation stability parameters are stored in a database.

[0128] According to an embodiment of the present disclosure, the database may be, for example, a relational database such as Mysql, SqlServer, or a non-relational database such as MongoDB, Redis, or Memcache.

[0129] In operation S502 , in response to a display instruction for a plurality of target cloud services, implementation stability parameters of the plurality of target cloud services are obtained from a database.

[0130] In operation S503, implementation stability parameters of multiple target cloud services are displayed in a preset data format.

[0131] According to an embodiment of the present disclosure, the preset data format may be, for example, an array type in which all components belong to the same type, a record type in which the components do not necessarily belong to the same type, a set type of all subsets of the value domain of a base type, and a sequence of components belonging to the same type, a file type that specifies the natural order of the components.

[0132] According to an embodiment of the present disclosure, the calculated implementation stability parameters can be saved in a database. After receiving a display instruction, the implementation stability parameters of multiple target cloud service records can be displayed in a certain format to achieve horizontal comparison of different cloud services, thereby helping relevant personnel to sort out existing cloud services from the perspective of stability and improve the stability of cloud services.

[0133] It should be noted that, unless it is explicitly stated that there is a sequence of execution between different operations shown in the flowchart in the embodiments of the present disclosure, or there is a sequence of execution between different operations in technical implementation, otherwise, the execution order of multiple operations may not be prioritized, and multiple operations may also be executed simultaneously.

[0134] Figure 6 The structure block diagram of the device for determining a cloud service implementation strategy according to an embodiment of the present disclosure is schematically shown.

[0135] like Figure 6 As shown, the device for determining a cloud service implementation strategy includes a timing module 610 , a first acquisition module 620 , an analysis module 630 , a processing module 640 and a replacement module 650 .

[0136] The timing module 610 is used to set a timing task, wherein the timing task includes initiating a data collection instruction at every preset time period.

[0137] The first acquisition module 620 is used to acquire first historical implementation time consumption data of the target cloud service in response to the data collection instruction.

[0138] The analysis module 630 is used to perform stability analysis on the first historical implementation time consumption data to obtain implementation stability parameters of the target cloud service.

[0139] The processing module 640 is used to determine the target implementation strategy of the target cloud service from the strategy library based on the implementation stability parameter, wherein the strategy library includes multiple implementation strategies applicable to different implementation stability parameters.

[0140] The replacement module 650 is used to replace the original implementation policy of the target cloud service with the target implementation policy.

[0141] According to an embodiment of the present disclosure, the analysis module 630 includes a filtering submodule, a determining submodule, and an output submodule.

[0142] The filtering submodule is used to adopt an abnormal value filtering method to filter out abnormal values ​​in the first historical implementation time consumption data to obtain the second historical implementation time consumption data.

[0143] The determination submodule is used to determine the historical implementation quantity of the target cloud service based on the second historical implementation time consumption data.

[0144] The output submodule is used to input the second historical implementation time consumption data and the historical implementation quantity into a preset probability model when the historical implementation quantity is greater than or equal to a preset value, and output an implementation stability parameter.

[0145] According to an embodiment of the present disclosure, the output submodule includes a first calculation unit, a second calculation unit, a first determination unit, and a second determination unit.

[0146] The first calculation unit is used to calculate the average historical implementation time consumption according to the second historical implementation time consumption data and the historical implementation quantity.

[0147] The second calculation unit is used to calculate the standard deviation of the historical implementation time consumption according to the historical implementation time consumption mean, the second historical implementation time consumption data and the historical implementation quantity.

[0148] The first determination unit is used to determine the stability coefficient based on the historical implementation time average and a preset coefficient function.

[0149] The second determination unit is used to determine the implementation stability parameter based on the historical implementation time standard deviation and the stability coefficient.

[0150] According to an embodiment of the present disclosure, the apparatus for determining a cloud service implementation strategy further includes a storage module, a second acquisition module and a display module.

[0151] The storage module is used to store the implementation stability parameters in a database.

[0152] The second acquisition module is used to obtain implementation stability parameters of the multiple target cloud services from a database in response to display instructions for the multiple target cloud services.

[0153] The display module is used to display the implementation stability parameters of multiple target cloud services in a preset data format.

[0154] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0155] For example, any multiple of the timing module 610, the first acquisition module 620, the analysis module 630, the processing module 640, and the replacement module 650 can be combined in one module / unit / subunit for implementation, or any one of the modules / units / subunits can be split into multiple modules / units / subunits. Alternatively, at least part of the functions of one or more of these modules / units / subunits can be combined with at least part of the functions of other modules / units / subunits and implemented in one module / unit / subunit. According to an embodiment of the present disclosure, at least one of the timing module 610, the first acquisition module 620, the analysis module 630, the processing module 640, and the replacement module 650 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or by any one of the three implementation methods of software, hardware, and firmware, or by a suitable combination of any of them. Alternatively, at least one of the timing module 610, the first acquisition module 620, the analysis module 630, the processing module 640 and the replacement module 650 may be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function may be performed.

[0156] It should be noted that the device part for determining the cloud service implementation strategy in the embodiments of the present disclosure corresponds to the method part for determining the cloud service implementation strategy in the embodiments of the present disclosure. The description of the device part for determining the cloud service implementation strategy specifically refers to the method part for determining the cloud service implementation strategy, which will not be repeated here.

[0157] Figure 7 A block diagram of an electronic device suitable for implementing a method for determining a cloud service implementation strategy according to an embodiment of the present disclosure is schematically shown. Figure 7 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0158] like Figure 7As shown, the computer electronic device 700 according to the embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 702 or the program loaded from the storage part 708 to the random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (such as a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (for example, an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include an onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to the embodiment of the present disclosure.

[0159] In RAM 703, various programs and data required for the operation of electronic device 700 are stored. Processor 701, ROM 702 and RAM 703 are connected to each other via bus 704. Processor 701 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 702 and / or RAM 703. It should be noted that the program can also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0160] According to an embodiment of the present disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to the bus 704. The electronic device 700 may further include one or more of the following components connected to the I / O interface 705: an input portion 706 including a keyboard, a mouse, etc.; an output portion 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage portion 708 including a hard disk, etc.; and a communication portion 709 including a network interface card such as a LAN card, a modem, etc. The communication portion 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed, so that a computer program read therefrom is installed into the storage portion 708 as needed.

[0161] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0162] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0163] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0164] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 702 and / or the RAM 703 described above and / or one or more memories other than the ROM 702 and the RAM 703 .

[0165] An embodiment of the present disclosure also includes a computer program product, which includes a computer program, and the computer program contains a program code for executing the method provided by the embodiment of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the method for determining the cloud service implementation strategy provided by the embodiment of the present disclosure.

[0166] When the computer program is executed by the processor 701, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0167] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 709, and / or installed from the removable medium 711. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0168] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0169] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments and / or claims of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0170] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A method for determining a cloud service implementation strategy, include: Setting a timed task, wherein the timed task includes initiating a data collection instruction at every preset time interval; In response to the data collection instruction, obtaining first historical implementation time consumption data of the target cloud service; Performing stability analysis on the first historical implementation time consumption data to obtain implementation stability parameters of the target cloud service; Based on the implementation stability parameter, determining a target implementation strategy of the target cloud service from a strategy library, wherein the strategy library includes multiple implementation strategies applicable to different implementation stability parameters; and Replace the original implementation policy of the target cloud service with the target implementation policy; The performing stability analysis on the first historical implementation time-consuming data to obtain the implementation stability parameter of the target cloud service includes: Adopting an outlier filtering method to filter out outliers in the first historical implementation time consumption data to obtain second historical implementation time consumption data; Determining the historical implementation quantity of the target cloud service based on the second historical implementation time consumption data; and When the historical implementation quantity is greater than or equal to a preset value, the second historical implementation time-consuming data and the historical implementation quantity are input into a preset probability model, and the implementation stability parameter is output; The step of inputting the second historical implementation time consumption data and the historical implementation quantity into a preset probability model and outputting the implementation stability parameter includes: Calculate the historical implementation time average according to the second historical implementation time data and the historical implementation quantity; Calculate the historical implementation time standard deviation according to the historical implementation time mean, the second historical implementation time data and the historical implementation quantity; Determining a stability coefficient based on the historical implementation time average and a preset coefficient function; and The implementation stability parameter is determined based on the historical implementation time standard deviation and the stability coefficient.

2. The method according to claim 1, in, The preset coefficient function includes a non-negative monotonically increasing function.

3. The method according to claim 1, further comprising: include: When the historical implementation quantity is less than the preset value, the implementation stability parameter is determined to be a preset stability parameter.

4. The method according to claim 1, further comprising: include: storing the implementation stability parameters in a database; In response to the display instructions for the plurality of target cloud services, acquiring implementation stability parameters of the plurality of target cloud services from the database; as well as The implementation stability parameters of the multiple target cloud services are displayed in a preset data format.

5. The method according to any one of claims 1 to 4, in, The implementation strategy of the target cloud service includes starting the implementation of the target cloud service at a preset time in advance based on the standard implementation time of the target cloud service.

6. A device for determining a cloud service implementation strategy, include: A timing module is used to set a timing task, wherein the timing task includes initiating a data collection instruction at every preset time interval; A first acquisition module, configured to acquire first historical implementation time consumption data of a target cloud service in response to the data collection instruction; An analysis module, configured to perform stability analysis on the first historical implementation time consumption data to obtain implementation stability parameters of the target cloud service; a processing module, configured to determine a target implementation strategy of the target cloud service from a strategy library based on the implementation stability parameter, wherein the strategy library includes a plurality of implementation strategies applicable to different implementation stability parameters; and A replacement module, used to replace an original implementation policy of the target cloud service with the target implementation policy; Wherein, the analysis module includes: A filtering submodule, configured to filter out abnormal values ​​in the first historical implementation time-consuming data by using an abnormal value filtering method, so as to obtain second historical implementation time-consuming data; a determination submodule, configured to determine the historical implementation quantity of the target cloud service based on the second historical implementation time consumption data; and An output submodule, for inputting the second historical implementation time-consuming data and the historical implementation quantity into a preset probability model, and outputting the implementation stability parameter when the historical implementation quantity is greater than or equal to a preset value; Wherein, the output submodule includes: A first calculation unit, configured to calculate an average historical implementation time consumption according to the second historical implementation time consumption data and the historical implementation quantity; A second calculation unit is used to calculate a standard deviation of the historical implementation time consumption according to the historical implementation time consumption mean, the second historical implementation time consumption data and the historical implementation quantity; A first determining unit, configured to determine a stability coefficient based on the historical implementation time average and a preset coefficient function; and The second determination unit is used to determine the implementation stability parameter based on the historical implementation time standard deviation and the stability coefficient.

7. An electronic device, include: one or more processors; a memory for storing one or more instructions, Wherein, when the one or more instructions are executed by the one or more processors, the one or more processors are enabled to implement the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having executable instructions stored thereon, wherein when the executable instructions are executed by a processor, the processor is enabled to implement the method according to any one of claims 1 to 5.

9. A computer program product, comprising computer executable instructions, wherein the computer executable instructions are used to implement the method according to any one of claims 1 to 5 when executed.

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