CN115378859A - Method, apparatus, device, medium and product for determining limit state information - Google Patents
Method, apparatus, device, medium and product for determining limit state information Download PDFInfo
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- CN115378859A CN115378859A CN202210996530.0A CN202210996530A CN115378859A CN 115378859 A CN115378859 A CN 115378859A CN 202210996530 A CN202210996530 A CN 202210996530A CN 115378859 A CN115378859 A CN 115378859A
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
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Abstract
The application discloses a method, a device, equipment, a medium and a product for determining extreme state information, relates to the field of computers, and further relates to the technical field of software testing. The specific implementation scheme is as follows: acquiring a sample instance set of each application; for each sample instance in each sample instance set, performing the following pressure test steps: forwarding the initial value of the online traffic to the sample instance within a single time period; determining index data for the sample instance over a single time period; in response to the fact that the index data meet the preset fusing condition, determining that the pressure test is finished, and obtaining a pressure test result; determining extreme state information of the sample instance based on the pressure test result; and determining the limit state information corresponding to each sample instance set based on the limit state information of each sample instance. The implementation mode can improve the determination accuracy of the extreme state information.
Description
Technical Field
The present disclosure relates to the field of computers, and more particularly to the field of software testing techniques, and more particularly to methods, apparatus, devices, media and products for determining extreme state information.
Background
At present, under a cloud service environment, capacity expansion or capacity reduction is often performed dynamically based on a load condition, so that dynamic allocation of resources is realized, and the utilization rate of the resources can be improved to the greatest extent.
In this regard, it is important to determine the extreme state of the load in order to evaluate the load situation.
Disclosure of Invention
The present disclosure provides a method, apparatus, device, medium, and article of manufacture for determining extreme state information.
According to a first aspect, there is provided a method for determining extreme state information, comprising: acquiring a sample instance set of each application; for each sample instance in each sample instance set, performing the following pressure test steps: forwarding the initial value of the online traffic to the sample instance within a single time period; determining index data for the sample instance over a single time period; in response to the fact that the index data meet the preset fusing condition, determining that the pressure test is finished, and obtaining a pressure test result; determining extreme state information of the sample instance based on the pressure test result; and determining the extreme state information corresponding to each sample instance set based on the extreme state information of each sample instance.
According to a second aspect, there is provided an apparatus for determining extreme state information, comprising: a set acquisition unit configured to acquire a set of sample instances of respective applications; the sample case set processing unit is configured to be used for carrying out pressure testing on each sample case in the sample case set and determining limit state information of each sample case; the set information determining unit is configured to determine limit state information corresponding to each sample instance set based on the limit state information of each sample instance; the instance information determination unit is further configured to: for each sample instance in each sample instance set, performing the following pressure test steps: forwarding the initial value of the online traffic to the sample instance within a single time period; determining metric data for the sample instance over a single time period; in response to the fact that the index data meet the preset fusing condition, determining that the pressure test is finished, and obtaining a pressure test result; based on the pressure test results, the extreme state information for the sample instance is determined.
According to a third aspect, there is provided an electronic device performing a method for determining extreme state information, comprising: one or more computing units; a storage unit for storing one or more programs; when the one or more programs are executed by the one or more computing units, the one or more computing units are caused to implement the method for determining extreme state information as described in any of the above.
According to a fourth aspect, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method for determining limit state information as any one of the above.
According to a fifth aspect, a computer program product is provided, comprising a computer program which, when being executed by a computing unit, carries out the method for determining extreme state information as set forth in any of the above.
According to the technology of the application, the method for determining the extreme state information is provided, the extreme state information of the sample example can be obtained by obtaining the sample example set of each application and carrying out pressure test on each sample example in the sample example set, and the extreme state information corresponding to the sample example set is further determined and obtained. In the process, the extreme state information which accords with the actual application scene can be determined by determining the sample instance set of the application and carrying out pressure test on the sample instance, so that the determination accuracy of the extreme state information can be improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is an exemplary system architecture diagram in which one embodiment of the present application may be applied;
FIG. 2 is a flow diagram of one embodiment of a method for determining extreme state information according to the present application;
FIG. 3 is a schematic illustration of an application scenario of a method for determining extreme state information according to the present application;
FIG. 4 is a flow diagram of another embodiment of a method for determining extreme state information according to the present application;
FIG. 5 is a flow diagram of another embodiment of a method for determining extreme state information according to the present application;
FIG. 6 is a block diagram illustrating one embodiment of an apparatus for determining extreme state information according to the present application;
FIG. 7 is a block diagram of an electronic device used to implement a method for determining extreme state information of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
Fig. 1 is an exemplary system architecture diagram according to a first embodiment of the present disclosure, illustrating an exemplary system architecture 100 to which embodiments of the method for determining extreme state information of the present application may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, and 103 may be electronic devices such as a mobile phone, a computer, and a tablet, and each application may be installed in the terminal devices 101, 102, and 103, where the applications are respectively deployed in corresponding servers. In the case that the present disclosure is applied to a cloud computing scenario, the servers are cloud computing servers, each cloud computing server may form a cluster in the form of a plurality of containers, and provide corresponding application services based on the container cluster.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices including, but not limited to, televisions, smart phones, tablet computers, e-book readers, car-mounted computers, laptop portable computers, desktop computers, and the like. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the electronic apparatuses listed above. It may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services) or as a single piece of software or software module. And is not particularly limited herein.
The server 105 may be a server providing various services, for example, may obtain application information of each application that needs to perform resource allocation in the terminal devices 101, 102, and 103, obtain a sample instance set of each application based on the application information, obtain limit state information corresponding to each sample instance set by performing a pressure test on each sample instance in the sample instance set, and allocate resources corresponding to each application based on the limit state information.
The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server 105 is software, it may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.
It should be noted that the method for determining the extreme state information provided in the embodiment of the present application may be executed by the terminal devices 101, 102, and 103, or may be executed by the server 105. Accordingly, the means for determining the extreme state information may be provided in the terminal devices 101, 102, 103, or in the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of a method for determining extreme state information according to the present application is shown. The method for determining the extreme state information of the embodiment comprises the following steps:
In this embodiment, an executing entity (for example, the server 105 or the terminal devices 101, 102, and 103 in fig. 1) may determine each application that needs to allocate resources, and then sample each application from all instances of the application to obtain a partial instance of the application as a sample instance set of the application. The sample instance set is used for carrying out pressure test on the extracted application instance, so that the limit state of the application in actual use can be estimated, and resource allocation is carried out based on the limit state. An instance refers to a concrete object created from an abstract template in a computer program, and the concrete object is expressed in a corresponding code segment. Wherein, the program code corresponding to each application comprises a plurality of instances. Optionally, when sampling the application and determining the sample instance set of each application, a sampling ratio may be preset, the number of instances to be extracted is determined according to the total number of the instances of the application and the sampling ratio, and then sample instances matching the number of the instances are randomly extracted to form the sample instance set. It can be understood that the more the number of the sample instances extracted, the more accurate the estimated limit state based on the sample instance set, but the larger the data calculation amount, and in practical application, the relationship between the number of the sample instances extracted, the balance data calculation amount and the accuracy of the estimated limit state can be selected according to different use requirements.
In this embodiment, the pressure testing step is a single-instance pressure test, and the time periods may be preset, and the on-line traffic of the initial value is forwarded to a single sample instance in each time period. The forwarding mode can be realized by performing firewall port forwarding on the sample example based on chaotic engineering. Thereafter, the index data of the sample instance is monitored over a time period. And the execution main body is preset with a fusing condition, wherein the fusing condition is used for judging whether the sample example reaches a limit state, namely, under the condition that the index data meets the fusing condition, the sample example can not normally provide service, and at the moment, the pressure test is determined to be finished, and a pressure test result is obtained. The pressure test result may include, but is not limited to, a cycle number of the pressure test, a maximum flow rate of the indicator data in a time period before the fusing condition is satisfied, a maximum resource utilization rate, a pressure test duration, and other information.
And each sample instance set comprises a plurality of sample instances, and the extreme state information of the sample instances can be determined by performing pressure test on the sample instances. The extreme state information is used for describing information such as the maximum flow and the maximum resource utilization rate which can be borne by the sample instance. The pressure test refers to that the flow is continuously increased for the example, the operation condition of the example in the flow increasing process is monitored until the example cannot normally operate, and therefore the maximum flow, the maximum resource utilization rate, the maximum user concurrency number and other limit state information which can be borne by the example and contains various information are obtained.
Optionally, in the process of performing the pressure test, the flow of the online user may be directed to the sample case performing the test, and the flow of the untested case may be directed to the sample case performing the test, so as to increase the flow value. For the case of diverting the in-line user traffic to the sample instance under test, it is preferable to use a single instance test, i.e., divert the in-line user traffic to a single sample instance for each pressure test. Compared with multi-instance testing, the method can reduce the influence on the online user and improve the testing safety. Pressure tests can also be directly carried out on a plurality of sample examples at the same time, the determination rate of the extreme state information can be improved, and the test safety is influenced. In actual use, different pressure testing modes can be selected according to actual use requirements, and the embodiment does not limit the pressure testing modes.
And step 203, determining the extreme state information of the sample instance based on the pressure test result.
In this embodiment, the pressure test result may include information such as a maximum flow and a maximum resource utilization rate of the index data in a time period before the fusing condition is satisfied, and based on the pressure test result, the maximum flow and the maximum resource utilization rate of the sample instance in the time period before the fusing condition is determined, and the maximum flow and the maximum resource utilization rate may be used as the limit state information of the sample instance.
And step 204, determining the limit state information corresponding to each sample instance set based on the limit state information of each sample instance.
In this embodiment, after obtaining the limit status information of all sample instances of each applied sample instance set, the limit status information may be summarized to obtain the limit status information corresponding to each sample instance set. Because the extreme state information of each sample instance can contain various index data, such as the maximum flow, the maximum resource utilization rate and the maximum user concurrency number, the data of each sample instance can be directly subjected to data processing modes such as averaging or determining a median, so that comprehensive data capable of comprehensively reflecting the data of each sample instance in the sample instance set is obtained and is determined as the extreme state information corresponding to the sample instance set.
Optionally, determining the extreme state information corresponding to each sample instance set based on the extreme state information of each sample instance may include the following steps: for each sample instance set, sorting the extreme state information of each sample instance of the sample instance set, wherein the extreme state information comprises the maximum flow and the maximum resource utilization rate; specifically, the maximum flow of each sample instance can be sequenced according to the sequence of the maximum flow from high to low, the maximum flow of a preset number before and after the median of the sequencing result is taken, and the average value is calculated to obtain the comprehensive maximum flow; sequencing the maximum resource utilization rate of each sample example according to the sequence of the maximum resource utilization rate from high to low, taking the maximum resource utilization rates of preset number before and after the median of the sequencing result, and calculating an average value to obtain the comprehensive maximum resource utilization rate; and determining the integrated maximum flow and the integrated maximum resource utilization rate as the limit state information corresponding to the sample instance set.
Optionally, the following steps may also be performed: and allocating resources corresponding to each application based on the limit state information corresponding to each sample instance set. And each sample instance set corresponds to a corresponding application, and resources can be allocated to the corresponding application based on the limit state information corresponding to the sample instance set. Specifically, the resource occupation state of the application may be determined based on the extreme state information of the sample instance set and the actual state information of the application, and the resource allocation to the application may be decreased or increased based on the resource occupation state. Where a resource may be a cluster of application servers, and in a cloud computing environment, the resource may be multiple containers in a cluster environment. Allocating resources includes at least increasing or decreasing the number of servers, the number of containers.
With continued reference to fig. 3, a schematic illustration of one application scenario of the method for determining extreme state information according to the present application is shown. In the application scenario of fig. 3, three different applications, namely, application a, application B, and application C, may be used to determine the limit state information according to a single application as a granularity. Specifically, a sample instance set a, a sample instance set B, and a sample instance set C corresponding to the applications a, B, and C are determined, respectively. Then, respectively carrying out pressure tests on the sample examples 1 and 2 in the sample example set A to obtain corresponding extreme state information 1 and 2; respectively carrying out pressure tests on the sample examples 3 and 4 in the sample example set B to obtain corresponding extreme state information 3 and 4; and respectively carrying out pressure tests on the sample examples 5 and 6 in the sample example set C to obtain corresponding limit state information 5 and 6. Then, the limit state information 1 and 2 are integrated to obtain limit state information A, the limit state information 3 and 4 are integrated to obtain limit state information B, and the limit state information 5 and 6 are integrated to obtain limit state information C. And then allocating the resources of the application A based on the extreme state information A, allocating the resources of the application B based on the extreme state information B, and allocating the resources of the application C based on the extreme state information C.
According to the method for determining the extreme state information provided by the embodiment of the application, the extreme state information of the sample example can be obtained by obtaining the sample example set of each application and performing pressure test on each sample example in the sample example set, the extreme state information corresponding to the sample example set is further determined and obtained, and then resources are allocated based on the extreme state information corresponding to each set. In the process, the limit state information conforming to the actual application scene can be determined by determining the sample example set of the application and performing pressure test on the sample examples, and the accuracy of resource allocation can be improved based on the more accurate resource allocation basis.
With continued reference to FIG. 4, a flow 400 of another embodiment of a method for determining extreme state information according to the present application is shown. As shown in fig. 4, the method for determining the limit state information of the present embodiment may include the steps of:
In this embodiment, please refer to the detailed description of step 201 for the detailed description of step 401, which is not repeated herein.
In this embodiment, please refer to the detailed description of step 202 for the detailed description of step 402, which is not repeated herein.
In some optional implementations of this embodiment, the indicator data includes at least instance stability indicator data and application stability indicator data; and the preset fusing conditions are as follows: the example stability indicator data is in a first numerical range; and/or the application stability indicator data is in the second numerical interval.
In this implementation, the instance stability indicator data is used to describe stability characteristics of the sample instance, and the application stability indicator data is used to describe stability characteristics of the application. In particular, example stability indicator data may include, but is not limited to, latency, resource utilization, traffic, service level agreements, and application stability indicator data may include, but is not limited to, service level agreements for services, stability of services and upstream and downstream links, stability of link core services. Further, the example stability index data in the first numerical interval indicates that the example is unstable, and the application stability index data in the second numerical interval indicates that the service is unstable. By adopting the index data of the example and the service stability, the limit states of the example and the service stability can be determined, and the limit state information is richer and more comprehensive. Specifically, the stability index data has different first value intervals for different examples. If for the time delay, the first value interval is an interval larger than the delay peak value in one week of the history; for the resource utilization rate, the first numerical interval is greater than a preset resource utilization rate threshold value; for a service level agreement, the first interval of values is below a preset level. The service level agreement is used for describing the availability level of the service requirement, and the smaller the availability level is, the worse the availability of the instance is. Specifically, for different application stability index data, it may be selected that the preset fusing condition is satisfied as long as any application stability index data is in the second numerical range. That is, the instance stability indicator data being in the first value interval indicates that the sample instance is already in an unstable state; and if the application stability index data is in the second numerical value interval, the application is in an unstable state, and the triggering fusing condition is confirmed.
In some optional implementations of this embodiment, the following steps may also be performed: acquiring example stability index data and application stability index data corresponding to each time point in a sliding window with preset duration; determining an example stability index data average value and an application stability index data average value based on example stability index data and application stability index data corresponding to each time point; in response to determining that the example stability indicator data is in the first numerical interval, determining a first number of times that the example stability indicator data is in the first numerical interval; in response to determining that the application stability indicator data is in the second numerical interval, determining a second number of times that the application stability indicator data is in the second numerical interval; and in response to determining that the first number is greater than a preset first number threshold, the second number is greater than a preset second number threshold, the example stability index data average is greater than a first average threshold, and/or the application stability index data average is greater than a second average threshold, determining that the index data meets a preset fusing condition.
In the implementation manner, the duration of the sliding window can be set in a user-defined manner according to requirements, and the sliding window can continuously move forwards based on time points to obtain a plurality of time periods, and the steps are executed for each time period. The sliding window includes a plurality of time points, and index data is acquired at each time point, where time intervals between the time points may be equal or unequal, which is not limited in this embodiment. Then, since the index data includes multiple types of data, such as example stability index data and application stability index data, multiple types of index data may be included in the example stability index data, and multiple types of index data may also be included in the application stability index data. It may be determined whether unstable data exists in the first value interval or the second value interval among the data, and if so, the number of times the unstable data exists in the first value interval or the second value interval. The number of times may be continuously exceeding the number of times in the first numerical interval or the second numerical interval, or may also be a discontinuous accumulated number of times, which is not limited in this embodiment. And if the times are greater than the preset times threshold value, indicating that the index data meet the fusing condition. Or, an average value of the example stability index data corresponding to each time point can be calculated to obtain an example stability index data average value; and calculating the average value of the application stability index data corresponding to each time point to obtain the average value of the application stability index data. Because the example stability index data and the application stability index data contain various types of data, the average value of the example stability index data or the application stability index data under each data type can be calculated based on each data type, the average value is compared with the average value threshold, and if the average value threshold is exceeded, the index data meet the fusing condition.
For example, if the preset time duration is 120 seconds, the time intervals between the time points are equal and are 6 seconds, both the first value interval and the second value interval exceed 108%, both the first average value threshold and the second average value threshold are 90%, and the preset time threshold is 1, that is, the average value of the example stability index data exceeds 90%, the average value of the application stability index data exceeds 90%, the example stability index data at a single time point exceeds 108%, and/or the application stability index data at a single time point exceeds 108% within the preset time duration, the fusing condition is triggered. Wherein, the preset multiple between the threshold corresponding to the first numerical interval and the second numerical interval and the average threshold is 1.2.
In some optional implementations of this embodiment, in response to determining that the indicator data meets the preset fusing condition, determining that the pressure test is ended to obtain a pressure test result, including: and determining that the pressure test is finished in response to the fact that the index data meet the preset fusing condition, and determining a pressure test result based on the index data of the last time period.
In this implementation manner, after the pressure test is finished, the index data at this time is data of the current time period, and a previous time period relative to the current time period may be determined, and then the index data of the previous time period is determined, that is, the pressure test result is determined based on the index data before fusing.
And 403, in response to the fact that the index data do not meet the preset fusing condition, updating the initial value according to a preset value increasing mode, and continuing to execute the pressure testing step.
In this embodiment, the preset value increasing manner may include, but is not limited to, increasing a fixed value each time, increasing a fixed multiple value each time, gradually decreasing an increasing value, gradually increasing a value that needs to be increased, and the like, which is not limited in this embodiment. And in response to the fact that the index data do not meet the preset fusing condition, determining that the pressure test in one time period is completed, and continuing to execute the pressure test step after updating the initial value, which is equivalent to performing the pressure test in the next time period.
At step 404, extreme state information for the sample instance is determined based on the pressure test results.
In this embodiment, the pressure test result may include information such as a maximum flow and a maximum resource utilization rate of the index data in a time period before the fusing condition is satisfied, and based on the pressure test result, the maximum flow and the maximum resource utilization rate of the sample instance in the time period before the fusing condition is determined, and the maximum flow and the maximum resource utilization rate may be used as the limit state information of the sample instance.
In this embodiment, please refer to the detailed description of step 203 for the detailed description of step 405, which is not repeated herein.
For each application, the actual state information of the application is obtained, step 406.
In this embodiment, the actual status information is used to describe the current actual status information of the application, such as current traffic and current resource occupancy.
In this embodiment, the current traffic may be compared with the maximum traffic in the limit status information, and the current resource occupancy may be compared with the maximum resource occupancy in the limit status information, so as to obtain the comparison result. The comparison result is used for indicating the size relationship between the current flow and the maximum flow in the limit state information and the size relationship between the current resource occupancy rate and the maximum resource occupancy rate in the limit state information. Optionally, a fluctuation range may also be set for the maximum traffic and the maximum resource occupancy, for example eighty percent, so as to compare the current traffic with eighty percent of the maximum traffic and compare the current resource occupancy with eighty percent of the maximum resource occupancy.
And step 408, based on the comparison result, performing capacity expansion operation or capacity reduction operation on the initial cluster resource of the application.
In this embodiment, if the current traffic is less than the maximum traffic in the limit status information or the current resource occupancy is less than the maximum resource occupancy in the limit status information, the capacity reduction operation may be performed on the applied initial cluster resource; if the current flow is larger than the maximum flow in the limit state information or the current resource occupancy rate is larger than the maximum resource occupancy rate in the limit state information, the capacity expansion operation can be performed on the applied initial cluster resources. Or, if the current traffic is less than eighty percent of the maximum traffic or the current resource occupancy is less than eighty percent of the maximum resource occupancy, the capacity reduction operation may be performed on the applied initial cluster resource.
The method for determining the extreme state information provided by the embodiment of the application can also set the fusing condition based on two aspects of the example stability index data and the application stability index data, so that the fusing judgment is more accurate, and the accuracy of resource allocation is further improved. And the average value of the index data of the sliding window can be calculated, and whether the fusing condition is triggered or not is dually judged by combining the index data corresponding to each time point in the sliding window, so that two aspects of the average data condition and the emergency data condition are fully considered, and the accuracy of resource allocation is further improved. And the actual state information based on the application is compared with the limit state information, so that the capacity expansion or the capacity contraction can be realized, the elastic capacity expansion and the capacity contraction are realized, and the resource allocation is more flexible.
With continued reference to FIG. 5, a flow 500 of another embodiment of a method for determining extreme state information according to the present application is shown. As shown in fig. 5, the method for determining extreme state information according to this embodiment is applied to an intelligent recommendation scenario, and may specifically include the following steps:
In this embodiment, an execution subject (e.g., a server) may generate an elastic scaling scheme for each application for a set of applications that need to generate a resource allocation scheme. Wherein, the application set needing the recommended resource allocation scheme can comprise a plurality of different types of applications.
In this embodiment, please refer to the detailed description of step 201 for the specific manner of sampling each application to obtain each sample instance set, which is not described herein again.
In this embodiment, the execution subject may obtain the extreme state information corresponding to each sample instance set by executing steps 202 to 203. The extreme state information may include maximum traffic and extreme resource utilization, among others.
In this embodiment, the execution subject may summarize the maximum traffic and the limit resource utilization of each sample instance set corresponding to each application, such as calculating an average value, calculating a median, and the like, so as to determine the maximum traffic and the limit resource utilization corresponding to each application.
And 505, monitoring the actual flow and the actual resource utilization rate of each application in the application set in real time, determining to perform capacity reduction on the corresponding application under the condition that the actual flow is less than the maximum flow and/or the actual resource utilization rate is less than the limit resource utilization rate, and determining to perform capacity expansion on the corresponding application under the condition that the actual flow is greater than the maximum flow and/or the actual resource utilization rate is greater than the limit resource utilization rate.
In this embodiment, the execution main body may also monitor the actual traffic and the actual resource utilization rate of each application in real time, compare the actual traffic with the maximum traffic, and compare the actual resource utilization rate with the limit resource utilization rate. For the application of which the actual flow is less than the maximum flow and/or the actual resource utilization rate is less than the limit resource utilization rate, determining that the resource allocation scheme of the application is capacity reduction, and for the application of which the actual flow is greater than the maximum flow and/or the actual resource utilization rate is greater than the limit resource utilization rate, determining that the resource allocation scheme of the application is capacity expansion.
In this embodiment, the resource allocation scheme may include a result of expansion and contraction capacity corresponding to each application, for example, if the application set includes applications a, B, and C, the resource allocation scheme may be expansion of the application a, contraction capacity of the application B, and contraction capacity of the application C.
The method for determining extreme state information provided by the above embodiment of the present application may further generate a resource allocation scheme for an application set including each application in an intelligent recommendation scenario, and recommend the resource allocation scheme. The related technical personnel can execute the capacity expansion and reduction operation on each application according to the resource allocation scheme recommended by the execution main body by selecting the resource allocation scheme.
With further reference to fig. 6, as an implementation of the method shown in the above-mentioned figures, the present application provides an embodiment of an apparatus for determining extreme state information, which corresponds to the embodiment of the method shown in fig. 2, and which is particularly applicable to various servers.
As shown in fig. 6, the apparatus 600 for determining extreme state information of the present embodiment includes: a set acquisition unit 601, an instance information determination unit 602, a set information determination unit 603, and a resource allocation unit 604.
The set acquisition unit 601 is configured to acquire a set of sample instances of each application.
The example information determining unit 602 is configured to, for each sample example set, perform a pressure test on each sample example in the sample example set, and determine extreme state information of each sample example.
A set information determining unit 603 configured to determine limit state information corresponding to each sample instance set based on the limit state information of each sample instance.
The instance information determination unit 602 is further configured to: for each sample instance in each sample instance set, performing the following pressure test steps: forwarding the initial value of the online traffic to the sample instance within a single time period; determining index data for the sample instance over a single time period; in response to the fact that the index data meet the preset fusing condition, determining that the pressure test is finished, and obtaining a pressure test result; based on the pressure test results, the limit state information for the sample instance is determined.
In some optional implementations of this embodiment, the apparatus further includes: and a value updating unit configured to update the initial value in a preset value increasing manner and continue to perform the pressure testing step in response to determining that the index data does not satisfy the preset fusing condition.
In some optional implementations of this embodiment, the indicator data includes at least instance stability indicator data and application stability indicator data; and the preset fusing conditions are as follows: the example stability indicator data is in a first numerical range; and/or the application stability indicator data is in the second numerical interval.
In some optional implementations of the present embodiment, the instance information determining unit 602 is further configured to: acquiring the example stability index data and the application stability index data corresponding to each time point in a sliding window with preset duration; determining an example stability index data average value and an application stability index data average value based on the example stability index data and the application stability index data corresponding to each time point; in response to determining that the example stability indicator data is in the first numerical interval, determining a first number of times that the example stability indicator data is in the first numerical interval; in response to determining that the application stability indicator data is within the second numerical interval, determining a second number of times that the application stability indicator data is within the second numerical interval; determining that the indicator data satisfies the preset fusing condition in response to determining that the first count is greater than a preset first count threshold, the second count is greater than a preset second count threshold, the instance stability indicator data average is greater than a first average threshold, and/or the application stability indicator data average is greater than a second average threshold.
In some optional implementations of the present embodiment, the instance information determining unit 602 is further configured to: and determining that the pressure test is finished in response to the fact that the index data meet the preset fusing condition, and determining a pressure test result based on the index data of the last time period.
It should be understood that the units 601 to 604, respectively, recited in the apparatus 600 for determining extreme state information correspond to the respective steps in the method described with reference to fig. 2. Thus, the operations and features described above for the method for allocating resources are also applicable to the apparatus 600 and the units included therein, and are not described herein again.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present application.
FIG. 7 shows a block diagram of an electronic device 700 for implementing a method for determining extreme state information of an embodiment of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 7, the device 700 comprises a computing unit 701, which may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM) 702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM 703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user may provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel or sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (12)
1. A method for determining extreme state information, comprising:
acquiring a sample instance set of each application;
for each sample instance in each sample instance set, performing the following pressure testing steps: forwarding the online traffic of the initial value to the sample instance within a single time period; determining index data for the sample instance over a single time period; in response to the fact that the index data meet the preset fusing condition, determining that the pressure test is finished, and obtaining a pressure test result;
determining extreme state information of the sample instance based on the pressure test result;
and determining the extreme state information corresponding to each sample instance set based on the extreme state information of each sample instance.
2. The method of claim 1, wherein the method further comprises:
and in response to the fact that the index data do not meet the preset fusing condition, updating the initial value according to a preset value increasing mode, and continuing to execute the pressure testing step.
3. The method of claim 1, wherein the metric data includes at least instance stability metric data and application stability metric data; and the preset fusing condition is as follows:
the example stability indicator data is in a first numerical interval; and/or
The application stability indicator data is in a second numerical interval.
4. The method of claim 3, wherein the method further comprises:
acquiring the example stability index data and the application stability index data corresponding to each time point in a sliding window with preset duration;
determining an example stability index data average value and an application stability index data average value based on the example stability index data and the application stability index data corresponding to each time point;
in response to determining that the example stability indicator data is in the first numerical interval, determining a first number of times that the example stability indicator data is in the first numerical interval;
in response to determining that the application stability indicator data is within the second numerical interval, determining a second number of times that the application stability indicator data is within the second numerical interval;
determining that the indicator data satisfies the preset fusing condition in response to determining that the first count is greater than a preset first count threshold, the second count is greater than a preset second count threshold, the instance stability indicator data average is greater than a first average threshold, and/or the application stability indicator data average is greater than a second average threshold.
5. The method of claim 1, wherein the determining that the stress test is ended in response to determining that the indicator data meets a preset fusing condition, resulting in a stress test result, comprises:
and determining that the pressure test is finished in response to the fact that the index data meet the preset fusing condition, and determining the pressure test result based on the index data of the last time period.
6. An apparatus for determining extreme state information, comprising:
a set acquisition unit configured to acquire a set of sample instances of respective applications;
the sample case set processing unit is configured to be used for carrying out pressure testing on each sample case in the sample case set and determining limit state information of each sample case;
the set information determining unit is configured to determine limit state information corresponding to each sample instance set based on the limit state information of each sample instance;
the instance information determination unit is further configured to:
for each sample instance in each sample instance set, performing the following pressure test steps: forwarding the initial value of the online traffic to the sample instance within a single time period; determining metric data for the sample instance over a single time period; in response to the fact that the index data meet the preset fusing condition, determining that the pressure test is finished, and obtaining a pressure test result;
and determining the extreme state information of the sample example based on the pressure test result.
7. The apparatus of claim 6, wherein the apparatus further comprises:
a value updating unit configured to update the initial value in a preset value increasing manner and continue to perform the pressure testing step in response to determining that the index data does not satisfy the preset fusing condition.
8. The apparatus of claim 6, wherein the metric data includes at least instance stability metric data and application stability metric data; and
the preset fusing conditions are as follows:
the example stability indicator data is in a first numerical range; and/or
The application stability indicator data is in a second numerical interval.
9. The apparatus of claim 8, wherein the instance information determination unit is further configured to:
acquiring the example stability index data and the application stability index data corresponding to each time point in a sliding window with preset duration;
determining an example stability index data average value and an application stability index data average value based on the example stability index data and the application stability index data corresponding to each time point;
in response to determining that the example stability indicator data is within the first numerical interval, determining a first number of times that the example stability indicator data is within the first numerical interval;
in response to determining that the application stability indicator data is within the second numerical interval, determining a second number of times that the application stability indicator data is within the second numerical interval;
determining that the indicator data satisfies the preset fusing condition in response to determining that the first count is greater than a preset first count threshold, the second count is greater than a preset second count threshold, the instance stability indicator data average is greater than a first average threshold, and/or the application stability indicator data average is greater than a second average threshold.
10. The apparatus of claim 6, wherein the instance information determination unit is further configured to:
and determining that the pressure test is finished in response to the fact that the index data meet the preset fusing condition, and determining the pressure test result based on the index data of the last time period.
11. An electronic device that performs a method for determining extreme state information, comprising:
at least one computing unit; and
a storage unit communicatively coupled to the at least one computing unit; wherein, the first and the second end of the pipe are connected with each other,
the storage unit stores instructions executable by the at least one computing unit to enable the at least one computing unit to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
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| CN113114504B (en) | 2022-08-30 |
| CN113114504A (en) | 2021-07-13 |
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