CN117608976A - Application performance early warning method and device, terminal equipment and storage medium - Google Patents
Application performance early warning method and device, terminal equipment and storage medium Download PDFInfo
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Abstract
The invention discloses an application performance early warning method, an application performance early warning device, terminal equipment and a storage medium, and belongs to the technical field of application management. The method comprises the following steps: acquiring resource information of a target application; based on a preset early warning period, performing homonymy growth calculation according to the resource information to obtain homonymy growth values; and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning. The method carries out the homonymous increase calculation on the resource information of the acquired target application based on the early warning period, and sends out the application performance early warning when the calculated homonymous increase value exceeds the preset early warning ratio, so that the problem that the early warning on the change of the application performance period is not realized is solved, the early warning on the application performance is realized, and the method is suitable for early warning scenes of medium-long-term progressive performance change in application performance monitoring.
Description
Technical Field
The present invention relates to the field of application management technologies, and in particular, to an application performance early warning method, an application performance early warning device, a terminal device, and a storage medium.
Background
The monitoring indexes of the application performance mainly comprise request number, success rate, response time and the like, the application performance monitoring mainly comprises threshold monitoring or baseline monitoring of the monitoring indexes of the application performance, the threshold monitoring comprises monitoring that the success rate or the response rate is lower than a threshold in a monitoring period, and the baseline monitoring comprises monitoring that the request number or the response time of the monitoring indexes is deviated from a baseline in the monitoring period.
However, the traditional application performance early warning is only suitable for judging whether the application performance is abnormal in the current monitoring period, and is not suitable for application performance early warning scenes of periodic variation, so that hidden danger of long-term gradual variation in early warning cannot be caused.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The main purpose of the application is to provide an application performance early warning method, an application performance early warning device, terminal equipment and a storage medium, and aims to solve the problem that early warning for the period change of the application performance is not performed.
In order to achieve the above objective, the present application provides an application performance early warning method, which includes:
acquiring resource information of a target application;
based on a preset early warning period, performing homonymy growth calculation according to the resource information to obtain homonymy growth values;
and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning.
Optionally, the target application includes a plurality of application instances, and the step of obtaining the resource information of the target application includes:
acquiring resource monitoring data, wherein the resource monitoring data is obtained by carrying out resource monitoring on the target application through a preset resource monitoring platform;
according to the application examples, summarizing and calculating the resource utilization rate of the resource monitoring data to obtain an example summarizing and calculating result;
and according to the example summary calculation result and the request number of the resource monitoring data, generating the resource information of the target application.
Optionally, the step of summarizing the resource usage of the resource monitoring data according to the plurality of application instances to obtain an instance summarizing result includes:
acquiring the processor utilization rate and the memory utilization rate according to the resource utilization rate;
summarizing and calculating according to the processor specifications of the application examples and the corresponding processor utilization rates to obtain total processor utilization time;
summarizing and calculating according to the memory specifications and the corresponding memory utilization rates of the application examples to obtain the total memory utilization;
and obtaining an example summarizing calculation result according to the total memory use time and the total memory use amount.
Optionally, the step of obtaining the total processor usage time includes:
based on a preset monitoring period, calculating according to the processor specifications of the application instances and the corresponding processor utilization rates to obtain the processor utilization time of the application instances;
and accumulating the processor use time of the application examples to generate the total processor use time.
Optionally, the step of obtaining the total memory usage amount by performing summary calculation according to the memory specifications and the corresponding memory usage rates of the plurality of application instances includes:
calculating according to the memory specifications of the application instances and the corresponding memory utilization rates to obtain the memory utilization amounts of the application instances;
and accumulating the memory usage of the application examples to generate the total memory usage.
Optionally, the step of performing the homonymy growth calculation according to the resource information based on the preset early warning period to obtain the homonymy growth value includes:
acquiring an instance summary calculation result and a request number according to the resource information;
calculating according to the total processor use time and the request number in the example summary calculation result, and obtaining the single request processor use time;
calculating the total memory usage and the request number in the calculation result according to the example summary to obtain the single request memory usage;
and based on the early warning period, carrying out homonymy increase calculation according to the single request processor using time and the single request memory using amount, and obtaining a homonymy increase value.
Optionally, based on the early warning period, the step of performing a homonymy increase calculation according to the single request processor usage time and the single request memory usage amount, and the step of obtaining the homonymy increase value includes:
calculating the ratio according to the use time of the corresponding single request processor before the early warning period and the use time of the corresponding single request processor after the early warning period to obtain the period ratio of the processor;
calculating a ratio according to the corresponding single-request memory usage before the early warning period and the corresponding single-request memory usage after the early warning period to obtain a memory period ratio;
and obtaining a homonymy increment value according to the processor cycle ratio and the memory cycle ratio.
The embodiment of the application also provides an application performance early warning device, which comprises:
the resource information acquisition module is used for acquiring resource information of the target application;
the homonymy increase calculation module is used for carrying out homonymy increase calculation according to the resource information based on a preset early warning period to obtain a homonymy increase value;
and the application performance early warning module is used for initiating application performance early warning if the homonymous increment value exceeds a preset early warning ratio.
The embodiment of the application also provides a terminal device, which comprises a memory, a processor and an application performance early warning program stored in the memory and capable of running on the processor, wherein the application performance early warning program realizes the steps of the application performance early warning method when being executed by the processor.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores an application performance early-warning program, and the application performance early-warning program realizes the steps of the application performance early-warning method when being executed by a processor.
The application performance early warning method, the device, the terminal equipment and the storage medium provided by the embodiment of the application performance early warning method, the device, the terminal equipment and the storage medium acquire resource information of target application; based on a preset early warning period, performing homonymy growth calculation according to the resource information to obtain homonymy growth values; and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning. The method carries out the homonymous increase calculation on the resource information of the acquired target application based on the early warning period, and sends out the application performance early warning when the calculated homonymous increase value exceeds the preset early warning ratio, so that the problem that the early warning on the change of the application performance period is not realized is solved, the early warning on the application performance is realized, and the method is suitable for early warning scenes of medium-long-term progressive performance change in application performance monitoring.
Drawings
FIG. 1 is a schematic diagram of functional modules of a terminal device to which a performance early warning device is applied;
FIG. 2 is a flowchart illustrating a first exemplary embodiment of the performance pre-warning method applied in the present application;
FIG. 3 is a flow chart illustrating a second exemplary embodiment of the application of the performance pre-warning method of the present application;
FIG. 4 is a schematic diagram of the performance pre-warning method monitoring platform of the present application acquiring index data;
FIG. 5 is a schematic diagram of the trend of index data of the performance pre-warning method applied in the present application;
FIG. 6 is a schematic diagram of a summary result of resource utilization of an application instance of the application performance early warning method;
FIG. 7 is a flowchart illustrating a third exemplary embodiment of a performance pre-warning method according to the present application;
FIG. 8 is a schematic diagram of a single request for resource utilization using a performance pre-warning method of the present application;
fig. 9 is a schematic diagram of a single request resource utilization change trend applying the performance early warning method in the present application.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The main solutions of the embodiments of the present application are: acquiring resource information of a target application; based on a preset early warning period, performing homonymy growth calculation according to the resource information to obtain homonymy growth values; and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning. The method carries out the homonymous increase calculation on the resource information of the acquired target application based on the early warning period, and sends out the application performance early warning when the calculated homonymous increase value exceeds the preset early warning ratio, so that the problem that the early warning on the change of the application performance period is not realized is solved, the early warning on the application performance is realized, and the method is suitable for early warning scenes of medium-long-term progressive performance change in application performance monitoring.
In the embodiment of the application, the performance monitoring indexes of the related technical scheme mainly comprise request number, success rate, response time and the like. And the indexes are subjected to threshold value or baseline monitoring, so that whether the application performance is abnormal at present can be effectively judged. For example, threshold monitoring: and in the current monitoring period (such as 1 minute), if the monitoring index (such as success rate or response rate) is lower than the set threshold (such as 95%), judging that the monitoring index is abnormal. Baseline monitoring: in the current monitoring period (such as 1 minute), if the monitoring index (such as the request number or the response time) is deviated by more than 3 standard deviations from the baseline, the abnormality is judged. The method is only suitable for judging whether the application performance is abnormal in the current monitoring period, and early warning of the periodic variation of the application performance is not realized, so that hidden danger of long-term gradual variation in early warning cannot be caused.
Based on the above, the embodiment of the application provides a solution, which uses the single request resource utilization rate as a monitoring index and can early warn the hidden danger of long-term progressive change in the performance in the application performance monitoring.
Specifically, referring to fig. 1, fig. 1 is a schematic diagram of functional modules of a terminal device to which a performance early warning device is applied in the present application. The application performance early warning device can be a device which is independent of the terminal equipment and can perform application performance early warning, and the device can be borne on the terminal equipment in a form of hardware or software. The terminal equipment can be intelligent mobile equipment with application performance early warning functions such as a mobile phone and a tablet personal computer, and can also be fixed terminal equipment or a server with application performance early warning functions.
In this embodiment, the terminal device to which the application performance early warning device belongs at least includes an output module 110, a processor 120, a memory 130, and a communication module 140.
The memory 130 stores an operating system and an application performance pre-warning program, and the application performance pre-warning device can store the received and processed data information in the memory 130; the output module 110 may be a display screen, a speaker, etc. The communication module 140 may include a WIFI module, a mobile communication module, a bluetooth module, and the like, and communicates with an external device or a server through the communication module 140.
Wherein, the application performance pre-warning program in the memory 130 realizes the following steps when being executed by the processor:
acquiring resource information of a target application;
based on a preset early warning period, performing homonymy growth calculation according to the resource information to obtain homonymy growth values;
and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning.
Further, the application performance pre-warning program in the memory 130, when executed by the processor, further performs the following steps:
acquiring resource monitoring data, wherein the resource monitoring data is obtained by carrying out resource monitoring on the target application through a preset resource monitoring platform;
according to the application examples, summarizing and calculating the resource utilization rate of the resource monitoring data to obtain an example summarizing and calculating result;
and according to the example summary calculation result and the request number of the resource monitoring data, generating the resource information of the target application.
Further, the application performance pre-warning program in the memory 130, when executed by the processor, further performs the following steps:
acquiring the processor utilization rate and the memory utilization rate according to the resource utilization rate;
summarizing and calculating according to the processor specifications of the application examples and the corresponding processor utilization rates to obtain total processor utilization time;
summarizing and calculating according to the memory specifications and the corresponding memory utilization rates of the application examples to obtain the total memory utilization;
and obtaining an example summarizing calculation result according to the total memory use time and the total memory use amount.
Further, the application performance pre-warning program in the memory 130, when executed by the processor, further performs the following steps:
based on a preset monitoring period, calculating according to the processor specifications of the application instances and the corresponding processor utilization rates to obtain the processor utilization time of the application instances;
and accumulating the processor use time of the application examples to generate the total processor use time.
Further, the application performance pre-warning program in the memory 130, when executed by the processor, further performs the following steps:
calculating according to the memory specifications of the application instances and the corresponding memory utilization rates to obtain the memory utilization amounts of the application instances;
and accumulating the memory usage of the application examples to generate the total memory usage.
Further, the application performance pre-warning program in the memory 130, when executed by the processor, further performs the following steps:
acquiring an instance summary calculation result and a request number according to the resource information;
calculating according to the total processor use time and the request number in the example summary calculation result, and obtaining the single request processor use time;
calculating the total memory usage and the request number in the calculation result according to the example summary to obtain the single request memory usage;
and based on the early warning period, carrying out homonymy increase calculation according to the single request processor using time and the single request memory using amount, and obtaining a homonymy increase value.
Further, the application performance pre-warning program in the memory 130, when executed by the processor, further performs the following steps:
calculating the ratio according to the use time of the corresponding single request processor before the early warning period and the use time of the corresponding single request processor after the early warning period to obtain the period ratio of the processor;
calculating a ratio according to the corresponding single-request memory usage before the early warning period and the corresponding single-request memory usage after the early warning period to obtain a memory period ratio;
and obtaining a homonymy increment value according to the processor cycle ratio and the memory cycle ratio.
According to the scheme, the resource information of the target application is obtained; based on a preset early warning period, performing homonymy growth calculation according to the resource information to obtain homonymy growth values; and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning. The method carries out the homonymous increase calculation on the resource information of the acquired target application based on the early warning period, and sends out the application performance early warning when the calculated homonymous increase value exceeds the preset early warning ratio, so that the early warning problem that the application performance period homonymous increase change is not caused is solved, the early warning of the application performance is realized, and the method is suitable for early warning scenes of medium-long-term progressive performance change in application performance monitoring.
Based on the above terminal device architecture, but not limited to the above architecture, the method embodiments of the present application are presented.
Referring to fig. 2, fig. 2 is a flowchart of a first exemplary embodiment of applying a performance pre-warning method according to the present application. The application performance early warning method comprises the following steps:
step S10: and acquiring the resource information of the target application.
The execution subject of the method of the embodiment may be an application performance early warning device, or may be an application performance early warning terminal device or a server, and the embodiment uses the application performance early warning device as an example, where the application performance early warning device may be integrated on a terminal device with a data processing function.
And acquiring the resource information of the target application of the performance monitoring. The resource information can also be obtained by monitoring the target application by the application resource monitoring platform or receiving data by the resource monitoring API interface, wherein the resource information can comprise index data such as request number, success rate and response time, and resource utilization information such as a processor and a memory, and the method can help to know the running state and resource utilization condition of the application program.
Step S20: based on a preset early warning period, performing homonymy growth calculation according to the resource information, and obtaining a homonymy growth value.
Based on a preset early warning period, performing homonymy increase calculation according to the acquired resource information of the target application to obtain a homonymy increase value. The preset early warning period may be one of parameters that may be used as a condition factor for the calculation of the homonymy, and may specifically be a set time period, for example: each minute, hour, day or week, or may be an execution period of an application, a life cycle of an application or a program running at a certain stage, or the like. When the early warning period is set to a time period, the homonymous increment value represents the increment percentage of the current resource utilization compared with the previous period resource utilization, and is used for identifying the periodic, i.e. medium-long-term progressive abnormal change of the potential application performance.
Step S30: and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning.
Comparing the calculated homonymy increment value with a preset early warning ratio, if the homonymy increment value exceeds the preset early warning ratio, the system judges that the performance of the application program is abnormal, triggers the application performance early warning, can help operation and maintenance personnel to discover possible performance problems in time, and takes corresponding measures to solve the problems.
And setting an early warning period to calculate a homonymy increment value by acquiring the resource information of the application program, and comparing the homonymy increment value with a preset early warning ratio value so as to judge whether the performance of the application program has abnormal change or not. If an abnormal change occurs, an application performance pre-warning is triggered to take timely action to deal with the potential performance problem.
According to the scheme, the resource information of the target application is obtained; based on a preset early warning period, performing homonymy growth calculation according to the resource information to obtain homonymy growth values; and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning. The method carries out the homonymous increase calculation on the resource information of the acquired target application based on the early warning period, and sends out the application performance early warning when the calculated homonymous increase value exceeds the preset early warning ratio, so that the early warning problem that the application performance period homonymous increase change is not caused is solved, the early warning of the application performance is realized, and the method is suitable for early warning scenes of medium-long-term progressive performance change in application performance monitoring.
Referring to fig. 3, fig. 3 is a flowchart illustrating a second exemplary embodiment of the performance pre-warning method according to the present invention.
Based on the first embodiment, a second embodiment of the present application is presented, which differs from the first embodiment in that:
in this embodiment, the target application includes a plurality of application instances, and the step of obtaining the resource information of the target application includes:
step S101: acquiring resource monitoring data, wherein the resource monitoring data is obtained by carrying out resource monitoring on the target application through a preset resource monitoring platform;
step S102: according to the application examples, summarizing and calculating the resource utilization rate of the resource monitoring data to obtain an example summarizing and calculating result;
step S103: and according to the example summary calculation result and the request number of the resource monitoring data, generating the resource information of the target application.
Specifically, first, a preset resource monitoring platform monitors resources of a target application, and collects resource monitoring data related to an application program. The resource monitoring data may be obtained through an API or other monitoring tools, and specifically includes: performance index data such as request number, success rate and response time, and resource utilization information such as CPU processor utilization rate, memory utilization rate, disk IO and the like.
And then, according to a plurality of application examples of the target application, summarizing and calculating the resource utilization rate in the resource monitoring data to obtain an example summarizing and calculating result. The specific summary calculation process may be that the summary calculation result of the target application instance may be obtained by summing or averaging the resource usage rates of the application instances.
And finally, according to the example summary calculation result and the request number in the resource monitoring data, the system generates the resource information of the target application. The resource information of the target application may include a resource utilization rate, an overall resource utilization rate, a request number, and the like of each instance, where the resource utilization rate may include a processor utilization rate and a memory utilization rate, and is used to help evaluate performance and resource utilization conditions of the target application.
Further, as an implementation manner, the step of summarizing the resource usage of the resource monitoring data according to the plurality of application instances to obtain an instance summarizing result includes:
step S1021: acquiring the processor utilization rate and the memory utilization rate according to the resource utilization rate;
step S1022: summarizing and calculating according to the processor specifications of the application examples and the corresponding processor utilization rates to obtain total processor utilization time;
step S1023: summarizing and calculating according to the memory specifications and the corresponding memory utilization rates of the application examples to obtain the total memory utilization;
step S1024: and obtaining an example summarizing calculation result according to the total memory use time and the total memory use amount.
Specifically, firstly, according to the resource utilization rate in the resource monitoring data, the processor utilization rate and the memory utilization rate of a plurality of examples of the target application are obtained, and the processor utilization rate and the memory utilization rate are used for subsequent calculation and early warning judgment.
The system will then calculate the processor usage time for each application instance from the number of application instances for the target application using the processor specification and the processor usage rate for each application instance and aggregate the processor usage time for each application instance into a total processor usage time. The processor use time can be calculated by multiplying the processor use rate of each instance by the running time, so as to evaluate the resource utilization condition of the target application on the aspect of the processor.
Then, the system calculates the memory use time of each application instance by using the memory specification and the memory use rate of each application instance according to a plurality of application instances of the target application, and summarizes the memory use time of each application instance as the total memory use time, thereby evaluating the resource utilization condition of the target application in the aspect of memory.
And finally, obtaining an example summarizing calculation result of the target application according to the total memory use time and the total memory use amount, wherein the summarizing calculation result can be used for evaluating the overall resource utilization condition of the target application so as to perform application performance early warning and optimization.
Further, as an implementation manner, the step of obtaining the total processor usage time according to the processor specifications of the application instances and the corresponding processor usage rates includes:
step S10221: based on a preset monitoring period, calculating according to the processor specifications of the application instances and the corresponding processor utilization rates to obtain the processor utilization time of the application instances;
step S10222: and accumulating the processor use time of the application examples to generate the total processor use time.
Specifically, first, according to a preset monitoring period, and according to the processor specifications of the application instances and the corresponding processor utilization rates in the period, calculating the processor utilization time of each application instance. Wherein the processor usage time of the number of application instances may be calculated by multiplying the processor usage of each instance by the processor specification.
And finally, accumulating the processor use time of the application instances, thereby generating the total processor use time. Wherein the accumulation operation may be accomplished by adding the processor usage times of each instance.
Further, as an implementation manner, the step of obtaining the total memory usage amount by performing a summary calculation according to the memory specifications and the corresponding memory usage rates of the plurality of application instances includes:
step S10223: calculating according to the memory specifications of the application instances and the corresponding memory utilization rates to obtain the memory utilization amounts of the application instances;
step S10224: and accumulating the memory usage of the application examples to generate the total memory usage.
Specifically, first, the memory usage of each application instance is calculated according to the memory specifications and the memory usage of a plurality of application instances of the target application. The memory usage of each application instance may be calculated by multiplying the memory specification of each instance by its memory usage.
And finally, accumulating the memory usage of the application examples to generate the total memory usage. The system performs an accumulation operation on the memory usage of the application instances, so as to generate a total memory usage, and the specific accumulation operation can be completed by adding the memory usage of each instance.
Specifically, the present exemplary embodiment includes the following steps:
1. acquiring the request number Q of a target application every day;
2. computing system resources for all instances of a target applicationService condition, CPU service time T C And memory usage M M If multiple instances are deployed, they are accumulated by specification.
More specifically, as shown in fig. 4, fig. 4 is a schematic diagram of the performance early warning method of the present invention, where the method includes obtaining four index data, including a request number, a success rate and a response time, from a monitoring platform.
As shown in fig. 5, fig. 5 is a schematic diagram of a trend of change of index data of the performance early warning method according to the present invention, and it can be seen from a broken line trend obtained by visualizing the index data in the graph that the change of part of the index data is relatively gentle, and the monitoring is only performed in a period of time in a traditional scene of threshold monitoring and baseline monitoring, if the performance index does not exceed the monitoring index threshold in the period or the deviation from the baseline does not exceed the set range, the performance abnormality of the application is not identified, and the hidden trouble of gradual change outside the monitoring period or between the monitoring periods cannot be identified.
As shown in fig. 6, fig. 6 is a schematic diagram of a summary result of resource usage of application instances in the application performance early warning method of the present invention, and taking four application instances of a target application as examples, the summary calculation is performed on the resource usage of the four application instances, and a specific calculation formula is as follows:
1. total CPU usage time = Σ (CPU usage rate of each instance specification) total number of milliseconds per day (8640 x 10 x 4)
2. Total memory usage (KB) = Σ (each instance memory usage of 1024 x 1024 by specification)
According to the scheme, the resource monitoring data are obtained by carrying out resource monitoring on the target application through the preset resource monitoring platform; according to the application examples, summarizing and calculating the resource utilization rate of the resource monitoring data to obtain an example summarizing and calculating result; and according to the example summary calculation result and the request number of the resource monitoring data, generating the resource information of the target application. And acquiring the resource monitoring data of the target application through a preset resource monitoring platform, summarizing and calculating to finally generate the resource information of the target application, and helping to know the performance and resource utilization condition of the application program, thereby carrying out early warning and optimization on the application performance.
Referring to fig. 7, fig. 7 is a flowchart illustrating a third exemplary embodiment of the performance pre-warning method according to the present invention.
Based on the second embodiment, a third embodiment of the present application is presented, which differs from the second embodiment in that:
in this embodiment, the step of obtaining the homonymy increment value based on the preset early warning period by performing homonymy increment calculation according to the resource information includes:
step S201: acquiring an instance summary calculation result and a request number according to the resource information;
step S202: calculating according to the total processor use time and the request number in the example summary calculation result, and obtaining the single request processor use time;
step S203: calculating the total memory usage and the request number in the calculation result according to the example summary to obtain the single request memory usage;
step S204: and based on the early warning period, carrying out homonymy increase calculation according to the single request processor using time and the single request memory using amount, and obtaining a homonymy increase value.
Specifically, in order to obtain a homonymy increment value of the application performance early warning, firstly, according to the obtained resource information, an example summarizing calculation result and a request number in the resource information are obtained. The example summary calculation result may include a total of processor use time, a total of memory use amount, and the like.
And then, calculating the average use time of a single request on the processor according to the total processor use time and the request number in the example summary calculation result. Wherein the total processor usage time may be divided by the number of requests to obtain a single requested processor usage time.
And then, according to the total memory usage and the request number in the example summary calculation result, calculating the average usage of a single request on the memory. The total memory usage may be divided by the number of requests to obtain the memory usage of a single request.
Finally, the system compares the processor use time and the memory use amount of a single request with corresponding data of a previous period based on a preset early warning period. The same-ratio increment value can be calculated by comparing the single request resource use condition of the current period with the condition of the previous period, and the same-ratio increment value is used for evaluating whether the resource use condition abnormally increases.
Further, as an implementation manner, the step of obtaining the homonymy increment value based on the early warning period and according to the single request processor usage time and the single request memory usage amount by performing homonymy increment calculation includes:
step S2041: calculating the ratio according to the use time of the corresponding single request processor before the early warning period and the use time of the corresponding single request processor after the early warning period to obtain the period ratio of the processor;
step S2042: calculating a ratio according to the corresponding single-request memory usage before the early warning period and the corresponding single-request memory usage after the early warning period to obtain a memory period ratio;
step S2043: and obtaining a homonymy increment value according to the processor cycle ratio and the memory cycle ratio.
Specifically, firstly, calculating the ratio of the service time of a single request processor before and after an early warning period to obtain the period ratio of the processor. The obtained processor cycle ratio represents the change condition of the processor use time between the target application cycles by dividing the processor use time after the early warning cycle by the processor use time before the early warning cycle, for example, when the early warning cycle is a week, the result obtained by calculating the ratio can be the ratio of the increase change compared with the processor use time of the target application on the same day of the last week.
And then, calculating the ratio of the single request memory usage before the early warning period and after the early warning period to obtain the memory period ratio. The obtained memory period ratio represents the change condition of the memory usage amount between the target application periods by dividing the memory usage amount after the early warning period by the memory usage amount before the early warning period, for example, in the case that the early warning period is one week, the result obtained by calculating the ratio may be the ratio of the increase change compared with the memory usage amount of the target application on the same day of the last week.
And finally, obtaining a homonymy increment value according to the processor cycle ratio and the memory cycle ratio. The homonymy increment value represents the variation trend of the use time of the processor and the use amount of the memory in the early warning period. The specific early warning can judge whether the use condition of the resource is abnormally increased or not by comparing the processor cycle ratio and the memory cycle ratio in the same-ratio increasing value with the preset early warning ratio, and the application performance early warning is sent out when the early warning ratio is exceeded. The processor cycle ratio and the memory cycle ratio can be combined to calculate and form a new index, namely the same-ratio increment value, and the application performance early warning can be performed according to the new index and the preset early warning ratio.
More specifically, as shown in fig. 8, fig. 8 is a schematic diagram of a single request resource usage rate by applying a performance early warning method according to the present invention, and a specific calculation formula of the single request resource usage rate may be calculated according to a total CPU usage time and a total memory usage amount and a request number, where a specific calculation formula is as follows:
1. single request CPU usage time = total CPU usage time/number of requests
2. Single request memory usage = total memory usage/number of requests
As shown in fig. 9, fig. 9 is a schematic diagram of a trend of changing the utilization rate of a single request resource in the application performance early warning method of the present invention, and from the above trend diagram, it can be seen that the number of requests is decreasing, and the utilization rate of the single request resource is increasing, which indicates that the application performance is deteriorating, and there is a hidden danger of memory overflow.
Taking 10 months and 6 days as an example, the single request CPU use time of the day is 7.1ms, which is increased by 69% compared with the same day (4.2 ms of 9 months and 29 days) in the last week and is increased by 34% compared with the average value of 5.3ms of 9 months and 29 days-10 months and 5 days in the last week; the single request memory usage on the same day is 12KB, which is increased by 97% compared with the same day (6.1 KB on 9 months and 29 days) on the last week, and is increased by 50% compared with the average value of 8KB on the last week (9 months and 29 days-10 months and 5 days). In this trend, the resource usage of each instance will quickly reach the alert value as the number of requests remains stable or resumes growing. Wherein, the abnormal judgment condition of single request resource utilization rate: an increase in the index of more than 30% is abnormal compared to the mean value of the same day or week.
According to the scheme, the embodiment obtains an instance summary calculation result and the request number according to the resource information; calculating according to the total processor use time and the request number in the example summary calculation result, and obtaining the single request processor use time; calculating the total memory usage and the request number in the calculation result according to the example summary to obtain the single request memory usage; and based on the early warning period, carrying out homonymy increase calculation according to the single request processor using time and the single request memory using amount, and obtaining a homonymy increase value. According to the provided resource information and the preset early warning period, the processor using time and the memory using amount of a single request are calculated, and a homonymous increase value is obtained by using a homonymous increase calculation method so as to evaluate the change condition of the resource using condition.
In addition, the embodiment of the application also provides an application performance early warning device, which comprises:
the resource information acquisition module is used for acquiring resource information of the target application;
the homonymy increase calculation module is used for carrying out homonymy increase calculation according to the resource information based on a preset early warning period to obtain a homonymy increase value;
and the application performance early warning module is used for initiating application performance early warning if the homonymous increment value exceeds a preset early warning ratio.
The present embodiment realizes the principle and implementation process of applying performance early warning, please refer to the above embodiments, and the description thereof is omitted herein.
In addition, the embodiment of the application also provides a terminal device, which comprises a memory, a processor and an application performance early-warning program stored in the memory and capable of running on the processor, wherein the application performance early-warning program realizes the steps of the application performance early-warning method when being executed by the processor.
Because the application performance early warning program is executed by the processor, all the technical schemes of all the embodiments are adopted, and therefore, the application performance early warning program at least has all the beneficial effects brought by all the technical schemes of all the embodiments, and the application performance early warning program is not described in detail herein.
In addition, the embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores an application performance early-warning program, and the application performance early-warning program realizes the steps of the application performance early-warning method when being executed by a processor.
Because the application performance early warning program is executed by the processor, all the technical schemes of all the embodiments are adopted, and therefore, the application performance early warning program at least has all the beneficial effects brought by all the technical schemes of all the embodiments, and the application performance early warning program is not described in detail herein.
Compared with the prior art, the application performance early warning method, the device, the terminal equipment and the storage medium provided by the embodiment of the application performance early warning method, the device, the terminal equipment and the storage medium are used for acquiring the resource information of the target application; based on a preset early warning period, performing homonymy growth calculation according to the resource information to obtain homonymy growth values; and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning. The method carries out the homonymous increase calculation on the resource information of the acquired target application based on the early warning period, and sends out the application performance early warning when the calculated homonymous increase value exceeds the preset early warning ratio, so that the early warning problem that the application performance period homonymous increase change is not caused is solved, the early warning of the application performance is realized, and the method is suitable for early warning scenes of medium-long-term progressive performance change in application performance monitoring.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. The application performance early warning method is characterized by comprising the following steps of:
acquiring resource information of a target application;
based on a preset early warning period, performing homonymy growth calculation according to the resource information to obtain homonymy growth values;
and if the homonymy increment value exceeds a preset early warning ratio, initiating application performance early warning.
2. The application performance pre-warning method according to claim 1, wherein the target application includes a plurality of application instances, and the step of obtaining the resource information of the target application includes:
acquiring resource monitoring data, wherein the resource monitoring data is obtained by carrying out resource monitoring on the target application through a preset resource monitoring platform;
according to the application examples, summarizing and calculating the resource utilization rate of the resource monitoring data to obtain an example summarizing and calculating result;
and according to the example summary calculation result and the request number of the resource monitoring data, generating the resource information of the target application.
3. The application performance early warning method according to claim 2, wherein the step of performing summary calculation on the resource usage rate of the resource monitoring data according to the plurality of application instances to obtain an instance summary calculation result includes:
acquiring the processor utilization rate and the memory utilization rate according to the resource utilization rate;
summarizing and calculating according to the processor specifications of the application examples and the corresponding processor utilization rates to obtain total processor utilization time;
summarizing and calculating according to the memory specifications and the corresponding memory utilization rates of the application examples to obtain the total memory utilization;
and obtaining an example summarizing calculation result according to the total memory use time and the total memory use amount.
4. The application performance pre-warning method according to claim 3, wherein the step of obtaining the total processor usage time by performing a summary calculation according to the processor specifications and the corresponding processor usage rates of the plurality of application instances includes:
based on a preset monitoring period, calculating according to the processor specifications of the application instances and the corresponding processor utilization rates to obtain the processor utilization time of the application instances;
and accumulating the processor use time of the application examples to generate the total processor use time.
5. The application performance early warning method according to claim 3, wherein the step of obtaining the total memory usage amount by performing a summary calculation according to the memory specifications and the corresponding memory usage rates of the plurality of application instances includes:
calculating according to the memory specifications of the application instances and the corresponding memory utilization rates to obtain the memory utilization amounts of the application instances;
and accumulating the memory usage of the application examples to generate the total memory usage.
6. The application performance early warning method according to claim 3, wherein the step of performing a homonymous increase calculation based on the resource information based on a preset early warning period, and obtaining a homonymous increase value includes:
acquiring an instance summary calculation result and a request number according to the resource information;
calculating according to the total processor use time and the request number in the example summary calculation result, and obtaining the single request processor use time;
calculating the total memory usage and the request number in the calculation result according to the example summary to obtain the single request memory usage;
and based on the early warning period, carrying out homonymy increase calculation according to the single request processor using time and the single request memory using amount, and obtaining a homonymy increase value.
7. The application performance early warning method according to claim 6, wherein the step of obtaining the homonymy increment value by performing homonymy increment calculation according to the single request processor usage time and the single request memory usage amount based on the early warning period includes:
calculating the ratio according to the use time of the corresponding single request processor before the early warning period and the use time of the corresponding single request processor after the early warning period to obtain the period ratio of the processor;
calculating a ratio according to the corresponding single-request memory usage before the early warning period and the corresponding single-request memory usage after the early warning period to obtain a memory period ratio;
and obtaining a homonymy increment value according to the processor cycle ratio and the memory cycle ratio.
8. An application performance pre-warning device, the device comprising:
the resource information acquisition module is used for acquiring resource information of the target application;
the homonymy increase calculation module is used for carrying out homonymy increase calculation according to the resource information based on a preset early warning period to obtain a homonymy increase value;
and the application performance early warning module is used for initiating application performance early warning if the homonymous increment value exceeds a preset early warning ratio.
9. A terminal device, characterized in that the terminal device comprises: a memory, a processor and an application performance pre-warning program stored on the memory and executable on the processor, the application performance pre-warning program being configured to implement the steps of the application performance pre-warning method according to any one of claims 1 to 7.
10. A storage medium having stored thereon an application performance pre-warning program which, when executed by a processor, implements the steps of the application performance pre-warning method according to any one of claims 1 to 7.
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