CN112363926A - Production environment capacity detection method and device, computer equipment and storage medium - Google Patents
Production environment capacity detection method and device, computer equipment and storage medium Download PDFInfo
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Abstract
The invention discloses a production environment capacity detection method, a production environment capacity detection device, computer equipment and a readable storage medium, wherein the method comprises the following steps: and respectively carrying out limit pressure test on a target sub-server and a test sub-server based on the production flow, carrying out amplification test on the test environment according to the number of the test sub-servers and the test limit pressure value of the test sub-servers, synchronously amplifying according to the limit capacity value of the target sub-server to obtain the total capacity of the production environment if the test environment normally operates, and obtaining the total test capacity and carrying out equal-proportion scaling on the limit capacity value to obtain the total capacity of the production environment if the test environment cannot normally operate. The invention is based on a testing tool technology, belongs to the field of software testing, carries out limit pressure testing based on production flow, obtains testing limit total capacity by simulating the input production flow in a testing environment and further obtains the testing environment total capacity so as to accurately and efficiently detect the production environment capacity under the condition of not interrupting the service of the production environment.
Description
Technical Field
The invention relates to the technical field of software testing, belongs to an application scene of detecting production environment capacity in a smart city, and particularly relates to a production environment capacity detection method, a production environment capacity detection device, computer equipment and a storage medium.
Background
With the development of internet technology, more and more services can be handled in an online manner, a client sends a service request to a service terminal of an enterprise through a client to handle the services quickly and conveniently online, the client sends a service request to the service terminal, that is, a flow is correspondingly generated, before the service terminal provides services for the client, a test environment is usually constructed for system software version test and flow test, a production flow estimated value is obtained through corresponding amplification and estimation based on the result of the flow test, the production flow estimated value is used as a total capacity to deploy a production environment in the service terminal and provide services for the client, and generally speaking, the capacity of the deployed production environment must meet the actual production flow. However, in the actual production process, the flow pressure of the production environment and the condition of the whole network link are much more complicated than those of the test environment, the production environment and the performance of the server used in the test environment may be greatly different, and with the iterative update of the version of the system software in the production environment, the capacity of the production environment obtained based on the result of the flow test may be seriously deviated from the actual use requirement and is difficult to provide high-quality service for the customer, and as the enterprise cannot interrupt the service of the production environment to detect the total capacity of the production environment, the ultimate production capacity of the production environment cannot be accurately and efficiently obtained, and further the system resource of the production environment cannot be flexibly adjusted in time according to the actual production flow. Therefore, the prior art method has the problem that the capacity of the production environment cannot be accurately and efficiently detected without interrupting the service of the production environment.
Disclosure of Invention
The embodiment of the invention provides a method and a device for detecting the capacity of a production environment, computer equipment and a storage medium, and aims to solve the problem that the prior art method cannot accurately and efficiently detect the capacity of the production environment without interrupting the service of the production environment.
In a first aspect, an embodiment of the present invention provides a method for detecting capacity of a production environment, including:
if a capacity detection instruction input by an administrator is received, selecting one production sub-server in the production environment as a target sub-server according to the capacity detection instruction to perform capacity test so as to obtain a production capacity curve of the target sub-server;
acquiring a limit capacity value meeting the capacity acquisition condition from the production capacity curve according to the capacity acquisition condition in the capacity detection instruction;
acquiring a production flow copy from the production environment, inputting the production flow copy into any one test sub-server in the test environment, and acquiring a test limit capacity value meeting the capacity acquisition condition;
carrying out amplification test according to the test limit capacity value and the number of the test sub-servers contained in the test environment, and judging whether the test environment normally operates according to preset state threshold information;
if the test environment normally operates, synchronously amplifying the limit capacity value according to the number of production sub-servers contained in the production environment to obtain the total capacity of the production environment;
and if the test environment cannot normally run, acquiring the total test capacity of the test environment, and scaling the total test capacity in equal proportion according to the limit capacity value, the test limit capacity value, the number of the production sub-servers and the number of the test sub-servers to obtain the total production environment capacity.
In a second aspect, an embodiment of the present invention provides a production environment capacity detection apparatus, including:
the production capacity curve acquisition unit is used for selecting one production sub-server in the production environment as a target sub-server according to a capacity detection instruction to perform capacity test to obtain a production capacity curve of the target sub-server if the capacity detection instruction input by an administrator is received;
a limit capacity value acquisition unit configured to acquire a limit capacity value satisfying a capacity acquisition condition from the production capacity curve according to the capacity acquisition condition in the capacity detection instruction;
a test limit capacity value obtaining unit, configured to obtain a production flow copy from the production environment and input the production flow copy to any one of the test sub-servers in the test environment, and obtain a test limit capacity value that satisfies the capacity obtaining condition;
the amplification test unit is used for carrying out amplification test according to the test limit capacity value and the number of the test sub-servers contained in the test environment and judging whether the test environment normally operates or not according to preset state threshold information;
a first capacity obtaining unit, configured to, if the test environment operates normally, synchronously amplify the limit capacity value according to the number of production sub-servers included in the production environment to obtain a total capacity of the production environment;
and the second capacity acquisition unit is used for acquiring the total test capacity of the test environment and scaling the total test capacity in equal proportion according to the limit capacity value, the test limit capacity value, the number of the production sub-servers and the number of the test sub-servers to obtain the total production environment capacity if the test environment cannot normally run.
In a third aspect, an embodiment of the present invention further provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the processor implements the method for detecting capacity of a production environment according to the first aspect.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program, and the computer program, when executed by a processor, causes the processor to execute the method for detecting capacity of a production environment according to the first aspect.
The embodiment of the invention provides a production environment capacity detection method and device, computer equipment and a storage medium. Selecting a target sub-server of the production environment according to the capacity detection instruction to perform capacity testing to obtain a production capacity curve and obtain a limit capacity value meeting capacity obtaining conditions from the production capacity curve, obtaining a testing limit capacity value of any testing sub-server in the testing environment, performing amplification testing on the testing environment according to the number of the testing sub-servers, synchronously amplifying according to the limit capacity value to obtain the total capacity of the production environment if the testing environment normally operates during amplification testing, and obtaining the total testing capacity and performing equal-proportion scaling on the limit capacity value to obtain the total capacity of the production environment if the testing environment cannot normally operate during amplification testing. By the method, the ultimate pressure test is respectively carried out on one target sub-server and one testing sub-server based on the production flow, the production flow is input to simulate the testing ultimate total capacity of a production server cluster under the real environment in the testing environment, the total capacity of the production environment is correspondingly obtained based on the testing ultimate capacity to carry out capacity detection on the production environment, and the capacity of the production environment can be accurately and efficiently detected without interrupting the service of the production environment.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for measuring capacity of a production environment according to an embodiment of the present invention;
fig. 2 is a schematic view of an application scenario of the method for detecting capacity of a production environment according to an embodiment of the present invention;
FIG. 3 is a schematic diagram illustrating an effect of the method for detecting capacity of a production environment according to an embodiment of the present invention;
FIG. 4 is a schematic sub-flow chart of a method for measuring capacity of a production environment according to an embodiment of the present invention;
FIG. 5 is a schematic view of another sub-flow of a method for measuring capacity of a production environment according to an embodiment of the present invention;
FIG. 6 is a schematic view of another sub-flow of a method for measuring capacity of a production environment according to an embodiment of the present invention;
FIG. 7 is a schematic view of another sub-flow of a method for measuring capacity of a production environment according to an embodiment of the present invention;
FIG. 8 is a schematic flow chart of a method for measuring capacity of a production environment according to an embodiment of the present invention;
FIG. 9 is a schematic flow chart of a method for measuring capacity of a production environment according to an embodiment of the present invention;
FIG. 10 is a schematic block diagram of a production environment capacity detection apparatus provided by an embodiment of the present invention;
FIG. 11 is a schematic block diagram of a computer device provided by an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1 and fig. 2, fig. 1 is a schematic flowchart of a method for detecting capacity of a production environment according to an embodiment of the present invention, fig. 2 is a schematic diagram of an application scenario of the method for detecting capacity of a production environment according to an embodiment of the present invention, where the method is applied to a management server 10, the method is executed by application software installed in the management server 10, the management server 10 is in communication connection with a production server cluster 20 and a test server cluster 30 respectively to implement transmission of data information, where the management server 10 is a load balancing server configured inside an enterprise to perform traffic distribution management on the production server cluster 20 and the test server cluster 30, a user of the management server 10 is an administrator of the enterprise, the production server cluster 20 is composed of a plurality of production sub-servers, the production server cluster 20 is deployed with a production environment, the test server cluster 30 is composed of a plurality of test sub-servers, and a test environment is deployed in the test server cluster 30. As shown in fig. 1, the method includes steps S110 to S160.
S110, if a capacity detection instruction input by an administrator is received, selecting one production sub-server in the production environment as a target sub-server according to the capacity detection instruction to perform capacity test so as to obtain a production capacity curve of the target sub-server.
If receiving a capacity detection instruction input by an administrator, the administrator is a user of the management server, the capacity detection instruction is instruction information input by the administrator and used for detecting the system resource capacity of the production environment, and the management server executes the capacity detection instruction and detects the capacity of the production environment. Specifically, the production environment is deployed in a production server cluster including a plurality of production sub-servers, and the management server may select one production sub-server in the production environment as a target sub-server, and perform a limit capacity test on the target sub-server to obtain a corresponding production capacity curve.
In addition, the capacity detection instruction may also automatically trigger execution, and as the version of the system software in the production environment is updated, the total capacity of the production environment that can be provided by the production environment may be reduced or the method may be performed, at this time, the capacity of the production environment needs to be detected, for example, if the management server detects that the version of the system software in the production environment is updated, the capacity detection instruction is automatically triggered to execute and the capacity detection of the production environment is completed.
The client sends a service request to the management server through the client, that is, a service flow is correspondingly generated, the service flow received in real time from the management server is distributed to the production environment for processing, the production flow is the service flow which is received by the production environment and needs to be processed, each production sub-server in the production environment can process the production flow, the rate of processing the production flow by the production sub-server is the number of processing the production flow by the production sub-server in unit time, the operation state of the production sub-server can change along with the distributed production flow, and the obtained production capacity curve comprises specific information that the operation state changes along with the distributed production flow in the process of processing the production flow by the target sub-server. The running state may include server state information such as data processing response time, interface call response time, traffic processing rate, data processing load, and the like.
In an embodiment, as shown in fig. 4, step S110 includes sub-steps S111, S112 and S113.
And S111, randomly selecting one production sub-server in the production environment as a target sub-server.
One production sub-server in the production environment can be randomly selected as a target sub-server, and one designated production sub-server can be selected as the target sub-server. In the whole process of carrying out capacity test on the target sub-server and detecting the capacity of the production environment, the service of the production environment does not need to be interrupted, namely, the service request received by the management server can be normally processed.
In an embodiment, the capacity check instruction may further include a filtering condition, and as shown in fig. 5, the sub-steps included in step S110 may also be S1111, S1112, S112, and S113.
S1111, sending a state acquisition request to the production environment to acquire the server state information of each production sub-server fed back by the production environment; s1112, acquiring a production sub-server of which the server state information meets the screening condition as the target sub-server.
In addition, the production sub-servers included in the production environment can be screened according to the screening condition in the capacity detection instruction, so that one production sub-server meeting the screening condition is obtained as the target sub-server. Specifically, a resource acquisition request is sent to acquire the current server state information of each production sub-server, the server state information may include data processing response time, interface call response time, traffic processing rate, data processing load, and the like, the method comprises the steps of obtaining data processing response time, interface calling response time and median or average value of data processing load according to server state information of each production sub-server, obtaining the production sub-servers with the flow processing rates larger than the flow processing rate threshold value as alternative sub-servers, calculating the data processing response time, the interface calling response time and Euclidean distance between the data processing load and the median or average value of each alternative sub-server, and obtaining one alternative sub-server with the minimum Euclidean distance as a target sub-server meeting the screening condition.
The Euclidean distance can be calculated by adopting the formula (1):
Ωp＝||Pa-Oa||2+||Pb-Ob||2+||Pc-Oc||2 (1)；
wherein, PaFor the data processing response time of the P-th alternative sub-server, PbInvoking a response time, P, for the interface of the alternative sub-servercFor the data processing load of the alternative sub-server, OaFor median of data processing response time, ObCalling the median of the response time for the interface, OcFor the median of the data processing load, Ω P is the euclidean distance of the pth candidate sub-server. Or OaIs the average value of the data processing response time, ObAverage value of response time for interface call, OcIs an average of the data processing load.
And S112, continuously increasing the weight value of the target sub-server so as to continuously increase the production flow distributed to the target sub-server according to the weight value.
The management server is pre-configured with a weight value matched with each production sub-server, and the production flow required to be processed by each production sub-server can be adjusted according to the weight value and the service flow received by the management server so as to realize load balance. The weight value of the target sub-server may be continuously increased to continuously increase the production traffic allocated to the target sub-server.
For example, if the initial weight value of the target sub-server is 0.12, and the production flow allocated to the target sub-server accounts for 0.12 of the total production flow, the weight value may be continuously increased to three times the initial weight value, that is, 0.12 may be continuously increased to 0.36, so that the amount of the production flow allocated to the target sub-server may be continuously increased.
S113, acquiring the corresponding relation between the server state information of the target sub-server and the production flow to generate the production capacity curve.
The production sub-server receives the production flow, processes the production flow in time when the flow pressure is small, the production sub-server may not process the production flow in time when the flow pressure is gradually increased, the production sub-server normally receives all the production flow from the management server at the moment and processes the production flow at the maximum rate, and the production flow which cannot be processed in time is stored in the memory of the production sub-server. The server state information in the process of processing the production flow by the target sub-server can be recorded, and the corresponding relation between the server state information and the production flow distributed to the target sub-server is obtained to obtain a production capacity curve. Fig. 3 is a schematic diagram illustrating an effect of the method for detecting capacity of a production environment according to the embodiment of the present invention, and an obtained production capacity curve is shown in fig. 3, in which a weight value of the target sub-server is 0.12 when an abscissa is 0 second, and the weight value of the target sub-server is increased to 0.36 when the abscissa is 24 seconds.
And S120, acquiring a limit capacity value meeting the capacity acquisition condition from the production capacity curve according to the capacity acquisition condition in the capacity detection command.
And acquiring a limit capacity value meeting the capacity acquisition condition from the production capacity curve according to the capacity acquisition condition in the capacity detection instruction. The production capacity curve comprises an average response time curve and a flow processing rate curve, the capacity obtaining condition further comprises a slope threshold, corresponding limit capacity values can be obtained from the two curves based on the slope values of the curves, the slope threshold is threshold information used for judging the slope values of the average response time curve, and the limit capacity values are the maximum values of the production capacity which can be borne by the target sub-servers, namely the maximum values of the production capacity which can be processed by the target sub-servers at the same time.
In an embodiment, as shown in fig. 6, step S120 includes sub-steps S121, S122 and S123.
S121, calculating a curve slope value of each time point in the average response time curve; s122, acquiring a time period in which the slope value of the curve in the average response time curve is greater than the slope threshold value; and S123, acquiring a curve segment matched with the time segment in the flow processing rate curve, and acquiring the maximum flow processing rate in the curve segment as the limit capacity value.
The average response time curve is a curve in which the average of the data processing response time and the interface call response time in the target sub-server changes with time, and specifically, the curve slope value of each time point in the average response time curve can be calculated to obtain the curve slope value of each time point and judge whether the curve slope value of each time point is greater than a slope threshold value, and the time points greater than the slope threshold value are obtained to form the time period.
As shown in fig. 3, the solid line part is a flow rate processing curve, the dashed line part is an average response time curve, and the time period in which the slope value of the curve is greater than the slope threshold value is obtained according to the above method, and the obtained time period is shown as a-B in fig. 3, where a and B respectively represent two time points on the abscissa.
A corresponding curve segment in the traffic processing rate curve is obtained according to the time period, and the maximum traffic processing rate in the curve segment is obtained as the limit capacity value of the target sub-server satisfying the capacity obtaining condition, that is, the maximum traffic processing rate between the point a and the point B in the traffic processing rate curve shown in fig. 3 is obtained as the limit capacity value.
S130, obtaining a production flow copy from the production environment, inputting the production flow copy into any one test sub-server in the test environment, and obtaining a test limit capacity value meeting the capacity obtaining condition.
And acquiring a production flow copy from the production environment, inputting the production flow copy into any one test sub-server in the test environment, and acquiring a test limit capacity value meeting the capacity acquisition condition. In order to realize the authenticity of the test sub-server, the corresponding production flow in the production environment can be copied to obtain a production flow copy, and the obtained production flow copy is input into any test sub-server of the test environment; the method for obtaining the test limit capacity value is the same as the method for obtaining the limit capacity value in the target sub-server, and the detailed description thereof is omitted here.
S140, carrying out amplification test according to the test limit capacity value and the number of the test sub-servers contained in the test environment, and judging whether the test environment normally operates according to preset state threshold information.
And carrying out amplification test according to the test limit capacity value and the number of the test sub-servers contained in the test environment, and judging whether the test environment normally operates. Besides performing the limit capacity test on a single test sub-server in the test environment, the test server cluster deploying the test environment needs to be subjected to an amplification test based on the test limit capacity value, and whether the test environment normally operates can be judged according to the state threshold value information.
In an embodiment, as shown in fig. 7, step S140 includes sub-steps S141, S142 and S143.
S141, calculating an amplified test value according to the test limit capacity value and the number of the test sub-servers; s142, obtaining a production flow copy matched with the amplification test value from the production environment, inputting the production flow copy into a test server cluster of the test environment, and obtaining cluster state information; s143, judging the cluster state information according to the state threshold value information to obtain a judgment result of whether the test environment normally operates.
The test limit capacity value is a numerical value obtained by carrying out limit capacity test on a single test sub-server, and the amplified test value can be obtained by multiplying the test limit capacity value by the number of the test sub-servers.
For example, if the test limit capacity value is 1600 and the number of test sub-servers included in the test server cluster is 5, the corresponding amplified test value is 1600 × 5 — 8000.
Acquiring a corresponding number of production flow copies according to the amplified test value, inputting the production flow copies into a test server cluster of the test environment to obtain cluster state information, wherein the state threshold information is a specific rule for judging the cluster state information of the test environment, the cluster state information is specific information of the running state changing along with the distributed production flow copies in the process of processing the production flow copies by the test server cluster, if the cluster state information does not exceed the state threshold information, judging that the test environment runs normally, and otherwise, judging that the test environment runs abnormally.
Specifically, the state threshold information may include a cluster processing load threshold, a processing response time threshold, an interface call response time threshold, a call error rate threshold, an abnormal state code frequency threshold, and the like. Then, cluster processing load, cluster processing response time, cluster interface calling response time, interface calling error rate, abnormal state code frequency and other information in the cluster state information can be obtained, whether each item of information is smaller than a threshold value matched with each item of information in the state threshold value information or not is judged, and if the item of information is smaller than the threshold value, the test environment is judged to normally operate; and if any one of the items of information is not less than the corresponding threshold value, judging that the test environment operates abnormally.
S150, if the test environment normally operates, synchronously amplifying the limit capacity value according to the number of the production sub-servers contained in the production environment to obtain the total capacity of the production environment.
And if the test environment normally operates, synchronously amplifying the limit capacity value according to the number of the production sub-servers contained in the production environment to obtain the total capacity of the production environment. If the test environment operates normally, it indicates that the test environment can normally process the production flow copy matched with the amplification test value in the amplification test, that is, after the limit capacity value of the target sub-server is synchronously amplified based on the same mode, the test environment can also normally process the production flow after synchronous amplification, and the production flow quantity obtained by synchronously amplifying the limit capacity value is taken as the total capacity of the production environment matched with the production environment. That is, the total capacity of the production environment matched with the production environment can be obtained by multiplying the limit capacity value by the number of the production sub-servers contained in the production environment.
And S160, if the test environment cannot normally run, acquiring the total test capacity of the test environment, and scaling the total test capacity in equal proportion according to the limit capacity value, the test limit capacity value, the number of the production sub-servers and the number of the test sub-servers to obtain the total production environment capacity.
And if the test environment cannot normally run, acquiring the total test capacity of the test environment, and scaling the total test capacity in equal proportion according to the limit capacity value, the test limit capacity value, the number of the production sub-servers and the number of the test sub-servers to obtain the total production environment capacity. If the test environment cannot normally operate, it indicates that the test environment cannot normally process the production flow copies matched with the amplification test values in the amplification test, and the test total capacity of the test environment needs to be obtained by continuously increasing the production flow copies and inputting the production flow copies into the production server cluster, where the test total capacity is a numerical value obtained by performing a limit capacity test on the production server cluster.
After the total testing capacity is obtained, the total testing capacity can be scaled in equal proportion based on the limit capacity value, the testing limit capacity value, the number of the production sub-servers and the number of the testing sub-servers, and the total production environment capacity matched with the production environment is obtained. Specifically, the calculation formula for performing the equal scaling can be expressed by using formula (2):
wherein S is the calculated total capacity of the production environment, ScTo test the total capacity, KsIs a limit capacity value, NsTo produce the number of child servers, KcFor testing the ultimate capacity value, NcTo test the number of child servers.
In an embodiment, as shown in fig. 8, steps S1601 and S1602 are further included after step S160.
S1601, periodically monitoring a test limit capacity value and an operation state of any test sub-server in the test environment to obtain periodic monitoring information of the test sub-server; s1602, judging whether the periodic monitoring information meets a preset capacity detection condition in real time, and if so, returning to the step of selecting one production sub-server in the production environment as a target sub-server according to the capacity detection instruction to perform capacity test to obtain a production capacity curve of the target sub-server.
In addition, the method can also perform periodic monitoring on the testing limit capacity value and the corresponding running state of any testing sub-server in the testing environment according to a preset time period to obtain periodic monitoring information, and stop performing periodic monitoring on the testing sub-server until the end time of the time period is reached, for example, the preset time period is the integral time included between 10:00 and 18:00, and the testing sub-server is not periodically monitored after 18:00 is reached. The obtained periodic monitoring information comprises server state information such as the number processing response time, the interface calling response time, the data processing load and the like of the testing sub-servers, the information obtained by each monitoring is recorded to form the periodic monitoring information of the testing sub-servers, whether the periodic monitoring information meets a capacity detection condition can be judged, wherein the capacity detection condition can be that the data processing response time is greatly increased, the interface calling response time is greatly increased, the limit capacity value is greatly reduced, and the data processing load exceeds a preset load threshold value, if any judgment condition is met, the periodic monitoring information is judged to meet the capacity detection condition, and the step S110 is returned to be executed to detect the production environment again and obtain the total capacity of the production environment; otherwise, judging that the periodic monitoring information does not meet the capacity detection condition, and waiting for the next monitoring.
For example, whether the data processing response time in the period monitoring information is greatly increased or not is judged, the data processing response time obtained by previous monitoring can be obtained and the average value and the standard deviation of the previous data processing response time are obtained through calculation, the sum of the average value and the standard deviation is obtained to obtain the data processing response time judgment threshold value of the current monitoring, whether the data processing response time of the current monitoring exceeds the data processing response time judgment threshold value or not is judged, if yes, the data processing response time in the period monitoring information is greatly increased, and if not, the data processing response time is not greatly increased.
In an embodiment, as shown in fig. 9, step S170 is further included after step S150 or S160.
S170, acquiring a target adjustment strategy matched with the total capacity of the production environment from a pre-stored adjustment strategy set according to pre-stored historical flow information and the total capacity of the production environment.
And acquiring a target adjustment strategy matched with the total capacity of the production environment from a pre-stored adjustment strategy set according to pre-stored historical flow information and the total capacity of the production environment. Specifically, the management server stores historical traffic information and an adjustment policy set in advance, the historical traffic information is traffic information obtained by counting the number of service requests received by the management server in real time, the adjustment policy set is a set for storing various adjustment policies, and the adjustment policies are policy information for adjusting the production server cluster. Specifically, the capacity ratio can be calculated according to the historical flow information and the total capacity of the production environment, and an adjustment strategy matched with the capacity ratio in the adjustment strategy set is obtained based on the capacity ratio and serves as a target adjustment strategy.
For example, the flow values in the historical flow information are sorted, the smallest flow value in the flow values which are sorted in the top 10% is obtained as a typical flow value, the capacity ratio is the typical flow value divided by the total capacity of the production environment, if the capacity ratio is 0.7, it is indicated that the production environment can meet the actual use requirement and has a certain capacity margin, and the target adjustment strategy can be to appropriately reduce the cluster scale of the production server; if the capacity ratio is 1.15, it indicates that the production environment cannot meet the actual use requirement at this time, and the target adjustment strategy may be to enlarge the scale of the production server cluster.
And calculating to obtain a capacity ratio according to the historical flow information and the total capacity of the production environment, calculating to obtain a sub-server ratio according to the test limit capacity value and the limit capacity value, and acquiring an adjustment strategy matched in the adjustment strategy set as a target adjustment strategy based on the capacity ratio and the sub-server ratio.
For example, the sub-server ratio is the testing limit capacity value divided by the limit capacity value, the capacity ratio is 1.15, the sub-server ratio is 1.4, and the target adjustment strategy is to increase the total capacity of the production environment by increasing the processing performance of the production sub-server (increasing the number of processing chip cores, increasing the data transmission bandwidth, etc.); with a capacity ratio of 1.15 and a sub-server ratio of 1.03, the objective tuning strategy is to increase the total capacity of the production environment by increasing the number of production sub-servers.
The technical method can be applied to application scenes including detection of production environment capacity, such as intelligent government affairs, intelligent city management, intelligent community, intelligent security protection, intelligent logistics, intelligent medical treatment, intelligent education, intelligent environmental protection and intelligent traffic, and the like, so that the construction of a smart city is promoted.
In the method for detecting the capacity of the production environment provided by the embodiment of the invention, a target sub-server of the production environment is selected according to a capacity detection instruction to carry out capacity test to obtain a production capacity curve and obtain a limit capacity value meeting a capacity obtaining condition from the production capacity curve, the test limit capacity value of any test sub-server in the test environment is obtained, the test environment is subjected to amplification test according to the number of the test sub-servers, if the test environment normally runs during the amplification test, the total capacity of the production environment is synchronously amplified according to the limit capacity value to obtain the total capacity of the production environment, and if the test environment cannot normally run during the amplification test, the total capacity of the test is obtained and the limit capacity value is subjected to equal-proportion scaling to obtain the total capacity of the production environment. By the method, the ultimate pressure test is respectively carried out on one target sub-server and one testing sub-server based on the production flow, the production flow is input to simulate the testing ultimate total capacity of a production server cluster under the real environment in the testing environment, the total capacity of the production environment is correspondingly obtained based on the testing ultimate capacity to carry out capacity detection on the production environment, and the capacity of the production environment can be accurately and efficiently detected without interrupting the service of the production environment.
Embodiments of the present invention further provide a production environment capacity detection apparatus, which is configured to execute any of the embodiments of the production environment capacity detection method. Specifically, referring to fig. 10, fig. 10 is a schematic block diagram of a production environment capacity detection apparatus according to an embodiment of the present invention. The production environment capacity detection means may be provided in the management server 10.
As shown in fig. 10, the production environment capacity detection apparatus 100 includes a production capacity curve acquisition unit 110, a limit capacity value acquisition unit 120, a test limit capacity value acquisition unit 130, an amplification test unit 140, a first capacity acquisition unit 150, and a second capacity acquisition unit 160.
A production capacity curve obtaining unit 110, configured to, if a capacity detection instruction input by an administrator is received, select a production sub-server in the production environment as a target sub-server according to the capacity detection instruction to perform a capacity test to obtain a production capacity curve of the target sub-server.
In an embodiment, the production capacity curve obtaining unit 110 comprises sub-units: the system comprises a random selection unit, a production flow distribution unit and a production capacity curve generation unit.
A random selection unit, configured to randomly select one production sub-server in the production environment as a target sub-server; a production flow allocation unit for continuously increasing the weight value of the target sub-server to continuously increase the production flow allocated to the target sub-server according to the weight value; and the production capacity curve generating unit is used for acquiring the corresponding relation between the server state information of the target sub-server and the production flow to generate the production capacity curve.
In an embodiment, the production capacity curve obtaining unit 110 comprises sub-units: the system comprises a server state information acquisition unit, a production sub-server screening unit, a production flow distribution unit and a production capacity curve generation unit.
The server state information acquisition unit is used for sending a state acquisition request to the production environment so as to acquire the server state information of each production sub-server fed back by the production environment; the production sub-server screening unit is used for acquiring one production sub-server of which the server state information meets the screening condition as the target sub-server; a production flow allocation unit for continuously increasing the weight value of the target sub-server to continuously increase the production flow allocated to the target sub-server according to the weight value; and the production capacity curve generating unit is used for acquiring the corresponding relation between the server state information of the target sub-server and the production flow to generate the production capacity curve.
A limit capacity value obtaining unit 120, configured to obtain a limit capacity value satisfying the capacity obtaining condition from the production capacity curve according to the capacity obtaining condition in the capacity detecting instruction.
In one embodiment, the limit capacity value obtaining unit 120 includes sub-units: the device comprises a curve slope value calculation unit, a time period acquisition unit and a processing rate acquisition unit.
The curve slope value calculation unit is used for calculating the curve slope value of each time point in the average response time curve; a time period obtaining unit, configured to obtain a time period in which a slope value of a curve in the average response time curve is greater than the slope threshold; and the processing rate acquiring unit is used for acquiring a curve segment matched with the time segment in the flow processing rate curve and acquiring the maximum flow processing rate in the curve segment as the limit capacity value.
A test limit capacity value obtaining unit 130, configured to obtain a production flow copy from the production environment, input the production flow copy into any one of the test sub-servers in the test environment, and obtain a test limit capacity value that satisfies the capacity obtaining condition.
And the amplification test unit 140 is configured to perform an amplification test according to the test limit capacity value and the number of the test sub-servers included in the test environment, and determine whether the test environment normally operates according to preset state threshold information.
In one embodiment, the amplification test unit 140 includes sub-units: the device comprises a method test value calculation unit, a cluster state information acquisition unit and an operation judgment unit.
The method test value calculation unit is used for calculating an amplified test value according to the test limit capacity value and the number of the test sub-servers; a cluster state information obtaining unit, configured to obtain, from the production environment, a production traffic replica that matches the amplified test value, input the production traffic replica into a test server cluster of the test environment, and obtain cluster state information; and the operation judgment unit is used for judging the cluster state information according to the state threshold information so as to obtain a judgment result of whether the test environment operates normally.
A first capacity obtaining unit 150, configured to, if the test environment operates normally, perform synchronous amplification on the limit capacity value according to the number of production sub-servers included in the production environment to obtain a total capacity of the production environment.
A second capacity obtaining unit 160, configured to, if the test environment cannot operate normally, obtain a total test capacity of the test environment, and scale the total test capacity in an equal proportion according to the limit capacity value, the test limit capacity value, the number of the production sub-servers, and the number of the test sub-servers to obtain the total production environment capacity.
In an embodiment, the production environment capacity detection apparatus 100 further comprises sub-units: the system comprises a period monitoring information acquisition unit and a period monitoring information judgment unit.
A periodic monitoring information obtaining unit, configured to periodically monitor a test limit capacity value and an operating state of any one test sub-server in the test environment to obtain periodic monitoring information of the test sub-server; and the period monitoring information judging unit is used for judging whether the period monitoring information meets a preset capacity detection condition in real time, and if so, returning to execute the step of selecting one production sub-server in the production environment as a target sub-server according to the capacity detection instruction to perform capacity test so as to obtain a production capacity curve of the target sub-server.
In an embodiment, the production environment capacity detection apparatus 100 further comprises sub-units: and a target adjustment strategy matching unit.
And the target adjustment strategy matching unit is used for acquiring a target adjustment strategy matched with the total capacity of the production environment from a prestored adjustment strategy set according to prestored historical flow information and the total capacity of the production environment.
The production environment capacity detection device provided by the embodiment of the invention applies the production environment capacity detection method, selects a target sub-server of a production environment according to a capacity detection instruction to perform capacity test to obtain a production capacity curve and obtain a limit capacity value meeting a capacity obtaining condition from the production capacity curve, obtains a test limit capacity value of any test sub-server in the test environment, performs amplification test on the test environment according to the number of the test sub-servers, synchronously amplifies according to the limit capacity value to obtain the total capacity of the production environment if the test environment normally operates in the amplification test, and obtains the total capacity of the test environment and performs equal-proportion scaling on the limit capacity value to obtain the total capacity of the production environment if the test environment cannot normally operate in the amplification test. By the method, the ultimate pressure test is respectively carried out on one target sub-server and one testing sub-server based on the production flow, the production flow is input to simulate the testing ultimate total capacity of a production server cluster under the real environment in the testing environment, the total capacity of the production environment is correspondingly obtained based on the testing ultimate capacity to carry out capacity detection on the production environment, and the capacity of the production environment can be accurately and efficiently detected without interrupting the service of the production environment.
The above-described production environment capacity detection apparatus may be implemented in the form of a computer program that can be run on a computer device as shown in fig. 11.
Referring to fig. 11, fig. 11 is a schematic block diagram of a computer device according to an embodiment of the present invention. The computer device may be a management server 10 for performing a production environment capacity detection method for capacity detecting a production environment.
Referring to fig. 11, the computer device 500 includes a processor 502, memory, and a network interface 505 connected by a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.
The non-volatile storage medium 503 may store an operating system 5031 and a computer program 5032. The computer program 5032, when executed, causes the processor 502 to perform the production environment capacity detection method.
The processor 502 is used to provide computing and control capabilities that support the operation of the overall computer device 500.
The internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503, and when the computer program 5032 is executed by the processor 502, the processor 502 can be enabled to execute the production environment capacity detection method.
The network interface 505 is used for network communication, such as providing transmission of data information. Those skilled in the art will appreciate that the configuration shown in fig. 11 is a block diagram of only a portion of the configuration associated with aspects of the present invention and is not intended to limit the computing device 500 to which aspects of the present invention may be applied, and that a particular computing device 500 may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
The processor 502 is configured to run the computer program 5032 stored in the memory to implement the corresponding functions in the production environment capacity detection method.
Those skilled in the art will appreciate that the embodiment of a computer device illustrated in fig. 11 does not constitute a limitation on the specific construction of the computer device, and that in other embodiments a computer device may include more or fewer components than those illustrated, or some components may be combined, or a different arrangement of components. For example, in some embodiments, the computer device may only include a memory and a processor, and in such embodiments, the structures and functions of the memory and the processor are consistent with those of the embodiment shown in fig. 11, and are not described herein again.
It should be understood that, in the embodiment of the present invention, the Processor 502 may be a Central Processing Unit (CPU), and the Processor 502 may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. Wherein a general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In another embodiment of the invention, a computer-readable storage medium is provided. The computer readable storage medium may be a non-volatile computer readable storage medium. The computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps included in the above-described production environment capacity detection method.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described apparatuses, devices and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided by the present invention, it should be understood that the disclosed apparatus, device and method can be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only a logical division, and there may be other divisions when the actual implementation is performed, or units having the same function may be grouped into one unit, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention essentially contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product stored in a computer-readable storage medium, which includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned computer-readable storage media comprise: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a magnetic disk, or an optical disk.
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A production environment capacity detection method is applied to a management server, the management server is respectively in communication connection with a production server cluster and a test server cluster to realize data information transmission, the production server cluster deploys a production environment, and the test server cluster deploys a test environment, and the method is characterized by comprising the following steps:
if a capacity detection instruction input by an administrator is received, selecting one production sub-server in the production environment as a target sub-server according to the capacity detection instruction to perform capacity test so as to obtain a production capacity curve of the target sub-server;
acquiring a limit capacity value meeting the capacity acquisition condition from the production capacity curve according to the capacity acquisition condition in the capacity detection instruction;
acquiring a production flow copy from the production environment, inputting the production flow copy into any one test sub-server in the test environment, and acquiring a test limit capacity value meeting the capacity acquisition condition;
carrying out amplification test according to the test limit capacity value and the number of the test sub-servers contained in the test environment, and judging whether the test environment normally operates according to preset state threshold information;
if the test environment normally operates, synchronously amplifying the limit capacity value according to the number of production sub-servers contained in the production environment to obtain the total capacity of the production environment;
and if the test environment cannot normally run, acquiring the total test capacity of the test environment, and scaling the total test capacity in equal proportion according to the limit capacity value, the test limit capacity value, the number of the production sub-servers and the number of the test sub-servers to obtain the total production environment capacity.
2. The method for detecting the capacity of the production environment according to claim 1, wherein the selecting a production sub-server in the production environment as a target sub-server according to the capacity detection instruction to perform a capacity test to obtain a production capacity curve of the target sub-server comprises:
randomly selecting one production sub-server in the production environment as a target sub-server;
continuously increasing the weight value of the target sub-server to continuously increase the production flow allocated to the target sub-server according to the weight value;
and acquiring the corresponding relation between the server state information of the target sub-server and the production flow to generate the production capacity curve.
3. The method according to claim 1, wherein the capacity detection instruction includes a screening condition, and the selecting a production sub-server in the production environment as a target sub-server according to the capacity detection instruction for performing a capacity test to obtain a production capacity curve of the target sub-server includes:
sending a state acquisition request to the production environment to acquire server state information of each production sub-server fed back by the production environment;
acquiring a production sub-server of which the server state information meets the screening condition as the target sub-server;
continuously increasing the weight value of the target sub-server to continuously increase the production flow allocated to the target sub-server according to the weight value;
and acquiring the corresponding relation between the server state information of the target sub-server and the production flow to generate the production capacity curve.
4. The method according to claim 1, wherein the capacity obtaining condition comprises a slope threshold, the production capacity curve comprises an average response time curve and a flow rate processing rate curve, and the obtaining a limit capacity value satisfying the capacity obtaining condition from the production capacity curve according to the capacity obtaining condition in the capacity detecting instruction comprises:
calculating a curve slope value of each time point in the average response time curve;
obtaining a time period in which a curve slope value in the average response time curve is greater than the slope threshold value;
and acquiring a curve section matched with the time section in the flow processing rate curve, and acquiring the maximum flow processing rate in the curve section as the limit capacity value.
5. The method for detecting the capacity of the production environment according to claim 1, wherein the performing the amplification test according to the test limit capacity value and the number of the test sub-servers included in the test environment and determining whether the test environment normally operates according to preset state threshold information comprises:
calculating an amplified test value according to the test limit capacity value and the number of the test sub-servers;
acquiring a production flow copy matched with the amplification test value from the production environment, inputting the production flow copy into a test server cluster of the test environment, and acquiring cluster state information;
and judging the cluster state information according to the state threshold information to obtain a judgment result of whether the test environment normally operates.
6. The method of claim 1, wherein after obtaining the total testing capacity of the testing environment and scaling the total testing capacity according to the limit capacity value, the testing limit capacity value, the number of the production sub-servers and the number of the testing sub-servers to obtain the total production environment capacity, the method further comprises:
periodically monitoring the test limit capacity value and the running state of any test sub-server in the test environment to obtain periodic monitoring information of the test sub-server;
and judging whether the periodic monitoring information meets a preset capacity detection condition in real time, and if so, returning to the step of executing the step of selecting one production sub-server in the production environment as a target sub-server according to the capacity detection instruction to perform capacity test so as to obtain a production capacity curve of the target sub-server.
7. The production environment capacity detection method of claim 1, further comprising:
and acquiring a target adjustment strategy matched with the total capacity of the production environment from a pre-stored adjustment strategy set according to pre-stored historical flow information and the total capacity of the production environment.
8. A production environment capacity detection apparatus, comprising:
the production capacity curve acquisition unit is used for selecting one production sub-server in the production environment as a target sub-server according to a capacity detection instruction to perform capacity test to obtain a production capacity curve of the target sub-server if the capacity detection instruction input by an administrator is received;
a limit capacity value acquisition unit configured to acquire a limit capacity value satisfying a capacity acquisition condition from the production capacity curve according to the capacity acquisition condition in the capacity detection instruction;
a test limit capacity value obtaining unit, configured to obtain a production flow copy from the production environment and input the production flow copy to any one of the test sub-servers in the test environment, and obtain a test limit capacity value that satisfies the capacity obtaining condition;
the amplification test unit is used for carrying out amplification test according to the test limit capacity value and the number of the test sub-servers contained in the test environment and judging whether the test environment normally operates or not according to preset state threshold information;
a first capacity obtaining unit, configured to, if the test environment operates normally, synchronously amplify the limit capacity value according to the number of production sub-servers included in the production environment to obtain a total capacity of the production environment;
and the second capacity acquisition unit is used for acquiring the total test capacity of the test environment and scaling the total test capacity in equal proportion according to the limit capacity value, the test limit capacity value, the number of the production sub-servers and the number of the test sub-servers to obtain the total production environment capacity if the test environment cannot normally run.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the production environment capacity detection method according to any one of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to perform the production environment capacity detection method according to any one of claims 1 to 7.
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