CN113505042A

CN113505042A - Dynamic monitoring method, device, equipment and storage medium for server memory

Info

Publication number: CN113505042A
Application number: CN202110854823.0A
Authority: CN
Inventors: 邹萌萍; 赵永田; 胡继强; 类铭辰
Original assignee: Industrial and Commercial Bank of China Ltd ICBC
Current assignee: Industrial and Commercial Bank of China Ltd ICBC
Priority date: 2021-07-28
Filing date: 2021-07-28
Publication date: 2021-10-15

Abstract

The specification relates to a server memory monitoring technology in the financial field or other fields, and provides a server memory dynamic monitoring method, a device, equipment and a storage medium, wherein the method comprises the following steps: acquiring the overall change trend of the memory utilization rate of a target server in a first time period, and acquiring the number of memory utilization rate subintervals covered by the memory utilization rate of the target server in a second time period; when the overall change trend of the memory usage rate is an ascending trend or the number of the memory usage rate subintervals reaches a fragmentation threshold, judging whether the target server has a sudden increase of the memory usage rate in the second time period; and when the target server has the sudden increase of the memory utilization rate in the second time period, determining the memory monitoring result of the target server according to the overall change trend of the memory utilization rate and the memory utilization rate in the second time period. The embodiment of the specification improves the accuracy and timeliness of the monitoring of the server cluster memory.

Description

Dynamic monitoring method, device, equipment and storage medium for server memory

Technical Field

The present disclosure relates to server memory monitoring technologies in the financial field or other fields, and in particular, to a method, an apparatus, a device, and a storage medium for dynamically monitoring a server memory.

Background

In recent years, server cluster size has seen explosive growth; meanwhile, the use of performance indexes such as server memory and the like also becomes a crucial concern. At present, the existing server memory monitoring method is as follows: the method is realized by comparing the memory utilization rate of each server with a set threshold; wherein, the memory usage threshold value can be different for different application servers. However, considering the characteristics of the memory data, the sporadic memory usage rate is high, or the memory usage rate is always stable and a high value may not be an abnormal phenomenon. Therefore, the monitoring accuracy of the existing server memory monitoring scheme is not high; the monitoring requirement of the server cluster in large scale cannot be met, and improvement is urgently needed.

Disclosure of Invention

An object of the embodiments of the present disclosure is to provide a method, an apparatus, a device, and a storage medium for dynamically monitoring a server memory, so as to improve the accuracy of monitoring a server cluster memory.

In order to achieve the above object, in one aspect, an embodiment of the present specification provides a method for dynamically monitoring a server memory, including:

acquiring the overall change trend of the memory utilization rate of a target server in a first time period, and acquiring the number of memory utilization rate subintervals covered by the memory utilization rate of the target server in a second time period;

when the overall change trend of the memory usage rate is an ascending trend or the number of the memory usage rate subintervals reaches a fragmentation threshold, judging whether the target server has a sudden increase of the memory usage rate in the second time period;

and when the target server has the sudden increase of the memory utilization rate in the second time period, determining the memory monitoring result of the target server according to the overall change trend of the memory utilization rate and the memory utilization rate in the second time period.

In an embodiment of this specification, the obtaining of the overall change trend of the memory usage rate of the target server in the first time period includes:

acquiring the memory utilization rate of the target server in the first time period;

and inputting the memory utilization rate in the first time period into a preset trend checking algorithm to obtain the overall change trend of the memory utilization rate of the target server in the first time period.

In an embodiment of this specification, the obtaining the number of memory usage rate subintervals covered by the memory usage rate of the target server in the second time period includes:

acquiring the memory utilization rate of the target server in the second time period;

determining the coverage range of the memory utilization rate in the second time period;

and determining the number of the memory usage subintervals covered by the coverage in the memory usage subinterval set.

In an embodiment of this specification, the determining whether there is a sudden increase in memory usage rate of the target server in the second time period includes:

determining a sliding window difference sequence of the memory usage rate of the target server in the second time period;

generating a plurality of sliding window subsequences according to the sliding window difference sequence;

determining a sum of sliding window difference values within each sliding window subsequence;

when at least one sliding window subsequence in the sliding window subsequences meets a preset condition, confirming that the target server has a sudden increase of the memory usage rate in the second time period;

wherein the preset conditions include:

the difference value of the sliding window positioned at the last position in the sliding window subsequence is larger than a first threshold value, and the sum value of the difference values of the sliding windows in the sliding window subsequence is larger than a second threshold value.

In an embodiment of this specification, the determining a memory monitoring result of the target server according to the overall change trend of the memory usage and the memory usage in the second time period includes:

determining the slope of the overall change trend of the memory utilization rate;

determining a first mean value of sliding window difference values in the sliding window difference value sequence corresponding to the second time period, and determining a second mean value of sliding window difference values in the sliding window difference value sequence corresponding to the appointed second time period;

and when the slope is greater than a slope threshold value and the first average value is greater than the second average value, determining that the memory of the target server is abnormal.

determining a first standard deviation of the sliding window difference value in the sliding window difference value sequence corresponding to the second time period, and determining a second standard deviation of the sliding window difference value in the sliding window difference value sequence corresponding to the appointed second time period;

and when the slope is greater than a slope threshold value and the first standard deviation is greater than the second standard deviation, determining that the memory of the target server is abnormal.

In an embodiment of the present specification, the determining a slope of the overall change trend of the memory usage includes:

fitting a variation curve of the memory utilization rate in the first time period by using a least square method;

and determining the slope of the starting point and the ending point of the change curve to be used as the slope of the overall change trend of the memory utilization rate.

In an embodiment of the present description, the first period comprises the last two weeks.

In an embodiment of the present specification, the second period of time comprises the last three hours.

In an embodiment of the present specification, the specified second period comprises the last three hours of the last week.

On the other hand, an embodiment of the present specification further provides a server memory dynamic monitoring apparatus, including:

the acquisition module is used for acquiring the overall variation trend of the memory utilization rate of the target server in a first time period and acquiring the number of memory utilization rate subintervals covered by the memory utilization rate of the target server in a second time period;

the judging module is used for judging whether the target server has sudden increase of the memory utilization rate in the second time period when the overall change trend of the memory utilization rate is an ascending trend or the number of the memory utilization rate subintervals reaches a fragmentation threshold;

and the determining module is used for determining the memory monitoring result of the target server according to the overall change trend of the memory utilization rate and the memory utilization rate in the second time period when the memory utilization rate of the target server suddenly increases in the second time period.

In another aspect, the embodiments of the present specification further provide a computer device, which includes a memory, a processor, and a computer program stored on the memory, and when the computer program is executed by the processor, the computer program executes the instructions of the above method.

In another aspect, the present specification further provides a computer storage medium, on which a computer program is stored, and the computer program is executed by a processor of a computer device to execute the instructions of the method.

As can be seen from the technical solutions provided in the embodiments of the present specification, the overall change trend of the memory usage rate of the server may be obtained, and when the overall change trend is an increasing trend, whether a sudden increase of the memory usage rate exists in the server is determined, and then a memory monitoring result of the server is determined according to the overall change trend of the memory usage rate and the sudden increase of the memory usage rate; due to the fact that the overall change trend and sudden increase of the memory utilization rate are comprehensively considered, compared with a mode that the state of the server memory is judged directly according to a threshold value in the traditional technology, the dynamic monitoring method for the server memory is more accurate. Moreover, in the embodiment of the present specification, only when the overall variation trend is an increasing trend, whether the server has a sudden increase in the memory usage rate is determined, so that the calculation amount can be greatly reduced, and the timeliness of dynamic monitoring of the server memory is also improved.

Drawings

In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort. In the drawings:

FIG. 1 is a schematic diagram of a server memory dynamic monitoring system in some embodiments of the present description;

FIG. 2 is a flow diagram illustrating a method for dynamic monitoring of server memory in some embodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating memory usage subinterval partitioning in some embodiments of the present description;

FIG. 4 is a diagram illustrating the number of memory usage subintervals covered by memory usage in some embodiments of the present description;

FIG. 5 illustrates a schematic diagram of the calculation of self-growth and cumulative growth by some embodiments of the present description;

FIG. 6 is a block diagram of a dynamic server memory monitor device in some embodiments of the present disclosure;

FIG. 7 is a block diagram illustrating the architecture of a computer device in some embodiments of the present description.

[ description of reference ]

10. A data source;

20. a dynamic monitoring device for the server memory;

30. configuring a source;

40. an alarm display end;

61. an acquisition module;

62. a judgment module;

63. a determination module;

702. a computer device;

704. a processor;

706. a memory;

708. a drive mechanism;

710. an input/output interface;

712. an input device;

714. an output device;

716. a presentation device;

718. a graphical user interface;

720. a network interface;

722. a communication link;

724. a communication bus.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all of the embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step should fall within the scope of protection of the present specification.

Fig. 1 is a schematic structural diagram illustrating a dynamic server memory monitoring system in some embodiments. The server memory dynamic monitoring system is used for dynamically monitoring the memory state of the server cluster. The server cluster may be an application serverless cluster (e.g., a bank data center server cluster). The server memory dynamic monitoring system may include a data source 10, a server memory dynamic monitoring device 20, a configuration source 30 and an alarm display terminal 40. The dynamic server memory monitoring device 20 may obtain the memory usage rate data of the server cluster from the plurality of data sources 10, and process the memory usage rate data according to the preset processing logic, thereby obtaining the memory monitoring result of the server cluster, and may send the memory warning information to the warning display terminal 40 when the memory of a certain server or certain servers is/are abnormal, so as to be displayed to the relevant personnel through the warning display terminal 40. Based on the configuration source 30, the exception monitoring of the specific application, the specific node or the specific server in the server cluster can be realized.

In some embodiments, the data source 10 may include, for example, an Operating System Power Management (OSPM), a server resource monitoring tool (e.g., NMON), etc. The Configuration source 30 may include, for example, a Configuration Management Database (CMDB) or the like. The alarm displaying terminal 40 may include, for example, a user terminal device or a server monitoring system. The user terminal device may include, but is not limited to, a display, a desktop computer, a mobile terminal (i.e., a smart phone), a tablet computer, and/or a notebook computer.

The embodiment of the present specification provides a server memory dynamic monitoring method, which can be applied to the server memory dynamic monitoring device side. Referring to fig. 2, in some embodiments, the method for dynamically monitoring the memory of the server may include the following steps:

s201, obtaining the whole change trend of the memory usage rate of the target server in a first time period, and obtaining the number of memory usage rate subintervals covered by the memory usage rate of the target server in a second time period.

S202, when the overall change trend of the memory usage rate is an ascending trend or the number of the memory usage rate subintervals reaches a fragmentation threshold, judging whether a sudden increase of the memory usage rate exists in the target server in the second time period;

s203, when the target server has the sudden increase of the memory usage rate in the second time period, determining the memory monitoring result of the target server according to the whole change trend of the memory usage rate and the memory usage rate in the second time period.

In the embodiment of the present specification, the overall change trend of the memory usage rate of the server may be obtained, and when the overall change trend is an increasing trend, whether a sudden increase of the memory usage rate exists in the server is determined, and then a memory monitoring result of the server is determined according to the overall change trend of the memory usage rate and a sudden increase of the memory usage rate; due to the fact that the overall change trend and sudden increase of the memory utilization rate are comprehensively considered, compared with a mode that the state of the server memory is judged directly according to a threshold value in the traditional technology, the dynamic monitoring method for the server memory is more accurate. Moreover, in the embodiment of the present specification, only when the overall variation trend is an increasing trend, whether the server has a sudden increase in the memory usage rate is determined, so that the calculation amount can be greatly reduced, and the timeliness of dynamic monitoring of the server memory is also improved.

The target server refers to any server in the server cluster that is included in the memory monitoring range. In this embodiment, the first time period is a relatively long recent time period, so as to globally and integrally know the overall change trend of the target server in the relatively long recent time period. For example, in some embodiments, the first period may be the last two weeks (i.e., the last 14 days), i.e., the memory usage of the target server in the last two weeks may be obtained. The second time period is a relatively short recent time period so as to locally know the local variation trend of the target server in the relatively short recent time period. For example, in some embodiments, the second period may be the last three hours, that is, the memory usage of the target server in the last three hours may be obtained. It will be understood by those skilled in the art that the two weeks and three hours described above are merely exemplary, and in other embodiments of the present disclosure, the specific duration of the first period and the second period may be set as appropriate according to the needs, and the present disclosure is not limited thereto. However, regardless of the choice, the duration of the first period should be much greater than the duration of the second period in general.

In some embodiments, the obtaining of the overall change trend of the memory usage rate of the target server in the first time period may include:

(1) and acquiring the memory utilization rate of the target server in the first time period.

Since the first period is a relatively long recent period, the sampling and processing frequency can be reduced appropriately to reduce the computer resource consumption. For example, taking the first time interval as the last two weeks as an example, the memory usage rate of the target server in the last two weeks may be collected once a day; therefore, the overall change trend of the memory usage of the target server in the last two weeks can be calculated only once a day. Also, the collection and calculation once per day are only exemplary, and in other embodiments of the present disclosure, the collection and calculation frequency may be set as appropriate according to the need, which is not limited in the present disclosure.

In some embodiments, the overall change trend of the memory usage rate of the target server in the first time period may be obtained from a plurality of data sources, so that the limitation of a single data source may be avoided, and it is beneficial to obtain higher-quality memory usage rate data.

(2) And inputting the memory utilization rate in the first time period into a preset trend checking algorithm to obtain the overall change trend of the memory utilization rate of the target server in the first time period.

In some embodiments, the memory usage rate in the first time period is input into a Mann-Kendall trend checking algorithm, so that the overall change trend of the memory usage rate of the target server in the first time period can be obtained. The Mann-Kendall trend testing algorithm is a non-parametric testing method (the non-parametric testing method is also called as non-distribution testing), has the advantages that samples do not need to follow certain distribution, the interference of a few abnormal values is avoided, the Mann-Kendall trend testing algorithm is more suitable for type variables and sequence variables, and the calculation is simpler and more convenient. In other embodiments, the discrete data of the memory usage rate of the target server in the first time period may also be fitted to a memory usage rate variation curve by a curve fitting method, so that the overall variation trend of the memory usage rate of the target server in the first time period may also be obtained. The curve fitting may include, but is not limited to, a least squares fitting algorithm, for example. In this way, for all the servers in the server cluster that are included in the monitoring range, a memory usage rate change curve of each server in the first time period can be obtained in the above manner.

In this embodiment, in order to more intuitively express the change of the memory usage rate of the target server in the second time period, the memory usage rate interval (i.e. 0-100%) may be divided into a plurality of sub-intervals (or interval segments) in advance. The more subintervals covered by the memory utilization rate of the target server in the second time period indicate that the memory utilization rate fluctuation of the target server in the second time period is larger; the smaller the opposite. For example, in the exemplary embodiment shown in FIG. 3, the memory usage may be divided into 20 sub-intervals, and the 20 sub-intervals may form a set of memory usage sub-intervals, with adjacent sub-intervals differing by 5 percentages, such as [ 0%, 5% ], [ 6%, 10% ], [ 11% -15% ], …, [ 91% -95% ], [ 95% -100% ]. Wherein the numbers in FIG. 3 represent memory usage percentages; for example: 20 means 20%, 50 means 50%.

In some embodiments, the obtaining the number of memory usage subintervals covered by the memory usage of the target server in the second period of time may include:

(1) and acquiring the memory utilization rate of the target server in the second time period.

In order to improve the timeliness of the memory state monitoring, the sampling frequency for obtaining the memory usage rate of the target server in the second time period may be relatively high. For example, in one embodiment, the memory usage of the target server during the second period may be collected every several minutes.

(2) And determining the coverage range of the memory utilization rate in the second time period.

In the embodiment of the present specification, it is collected that the memory usage rate of the target server in the second period is some discrete values, and when the minimum value and the maximum value of the discrete values are determined by sorting the discrete values; and taking the minimum value and the maximum value as intervals formed by interval endpoints, namely the coverage range of the memory utilization rate of the target server in the second time interval. For example, in an exemplary embodiment, the maximum value and the minimum value of the acquired memory usage rate of the target server in the second time period are 59% and 20%, respectively, for the current sampling, [ 20%, 59% ] is the coverage of the memory usage rate of the target server in the second time period.

(3) And determining the number of the memory usage subintervals covered by the coverage in the memory usage subinterval set.

The whole interval (namely 0-100%) of the memory utilization rate is divided into a plurality of subintervals in advance, and the endpoint value of each subinterval is determined; on the basis of determining the coverage of the memory usage in the second time period, the number of memory usage subintervals covered by the coverage in the memory usage subinterval set may be calculated. For example, in the exemplary embodiment shown in fig. 4, the memory usage rate may be divided into 20 sub-intervals; the coverage range of the acquired memory usage rate of the target server in the second time period is 18% -37%; this 18% to 37% coverage is calculated to cover 5 memory usage sub-intervals of [ 15%, 20% ], [ 21%, 25% ], [ 26%, 30% ], [ 31%, 35% ], and [ 35%, 40% ]. Therefore, it can be determined that the number of memory usage subintervals covered by the 18% -37% coverage area in the set of memory usage subintervals is 5.

When the overall change trend of the memory utilization rate of the server is a descending trend or a stable trend, the short-term small fluctuation of the memory utilization rate generally cannot cause substantial influence on the server; considering that whether the calculated amount of the sudden increase of the memory usage rate of the target server exists in the second time period is large; therefore, when the overall variation trend of the memory usage rate is an ascending trend, or the number of the memory usage rate subintervals reaches the fragmentation threshold, whether the target server has the sudden increase of the memory usage rate in the second time interval is judged, so that the server which has the overall variation trend of the memory usage rate in a descending trend or a stable trend and the server which has the number of the memory usage rate subintervals which does not reach the fragmentation threshold do not need to participate in the sudden increase judgment of the memory usage rate, thereby greatly reducing the calculation amount on the basis of not reducing the memory monitoring accuracy and further considering the timeliness of the server memory monitoring. It should be noted that the above-mentioned stationary trend includes not only the overall or substantially horizontal memory usage curve, but also a periodic (or substantially periodic) curve (e.g. similar to a sine curve, etc.) whose amplitude does not exceed a certain value.

In some embodiments, the determining whether there is a sudden increase in the memory usage rate of the target server in the second time period may include:

(1) and determining a sliding window difference sequence of the memory utilization rate of the target server in the second time period.

In some embodiments, the memory usage of the target server during the second period of time may be a time series of a plurality of discrete data points arranged in a sample time order. A sliding window with a specified size can be preset, a discrete data point is used as a sliding step length, and then the difference value of the memory utilization rates at the two ends of the sliding window is calculated in a sliding mode; accordingly, a sliding window difference sequence of the memory utilization rate of the target server in the second time period can be obtained.

For example, taking the second time period as the last three hours as an example, assuming that the sampling frequency of the memory usage is 5 minutes (i.e., 12 times per hour), 36 memory usages (e.g., mem 1-mem 36 in fig. 5) of the target server can be obtained in the last three hours. By using 12 discrete data points as the sliding window size and one discrete data point as the sliding step size, 25 natural growth increments (e.g., Selfgrow 1-Selfgrow 25 in fig. 5) can be obtained by performing the sliding window calculation on these memory usage rates. Specifically, the method comprises the following steps: the 1 st natural growth increment Selfgrow1 can be calculated according to the formula Selfgrow 1-mem 12-mem 1; the 2 nd increment of natural growth Selfgrow2 can be calculated according to the formula Selfgrow 2-mem 13-mem 2; the 3 rd natural growth increment Selfgrow3 can be calculated according to the formula Selfgrow 3-mem 14-mem 3; in this recurrence, the 25 th natural growth increment Selfgrow25 can be calculated according to the formula Selfgrow 25-mem 36-mem 25.

Only one sliding window difference sequence, namely the sliding window difference sequence of the memory usage of the target server in the second time period, can be obtained by sequencing 25 natural growth increments Selfgrow 1-Selfgrow 25.

(2) And generating a plurality of sliding window subsequences according to the sliding window difference sequence.

In some embodiments, for the sliding window difference sequence obtained in the previous step, a sliding window with a specified size may also be preset, and a natural growth increment is used as a sliding step length, and then the natural growth increment in the sliding window is selected in a sliding manner, so that a plurality of sliding window subsequences may be obtained.

With continued reference to fig. 5, in an exemplary embodiment, for 25 natural growth increments Selfgrow 1-Selfgrow 25, if 12 natural growth increments are used as the sliding window size and one natural growth increment is used as the sliding step size, then by sliding the natural growth increments in the selected sliding window, the following sub-sequence of 14 sliding windows can be obtained.

{Selfgrow1，Selfgrow2，Selfgrow3，Selfgrow4，Selfgrow5，Selfgrow6，Selfgrow7，Selfgrow8，Selfgrow9，Selfgrow10，Selfgrow11，Selfgrow12}；

{Selfgrow2，Selfgrow3，Selfgrow4，Selfgrow5，Selfgrow6，Selfgrow7，Selfgrow8，Selfgrow9，Selfgrow10，Selfgrow11，Selfgrow12，Selfgrow13}；

{Selfgrow3，Selfgrow4，Selfgrow5，Selfgrow6，Selfgrow7，Selfgrow8，Selfgrow9，Selfgrow10，Selfgrow11，Selfgrow12，Selfgrow13，Selfgrow14}；

{Selfgrow4，Selfgrow5，Selfgrow6，Selfgrow7，Selfgrow8，Selfgrow9，Selfgrow10，Selfgrow11，Selfgrow12，Selfgrow13，Selfgrow14，Selfgrow15}；

{Selfgrow5，Selfgrow6，Selfgrow7，Selfgrow8，Selfgrow9，Selfgrow10，Selfgrow11，Selfgrow12，Selfgrow13，Selfgrow14，Selfgrow15，Selfgrow16}；

{Selfgrow6，Selfgrow7，Selfgrow8，Selfgrow9，Selfgrow10，Selfgrow11，Selfgrow12，Selfgrow13，Selfgrow14，Selfgrow15，Selfgrow16，Selfgrow17}；

{Selfgrow7，Selfgrow8，Selfgrow9，Selfgrow10，Selfgrow11，Selfgrow12，Selfgrow13，Selfgrow14，Selfgrow15，Selfgrow16，Selfgrow17，Selfgrow18}；

{Selfgrow8，Selfgrow9，Selfgrow10，Selfgrow11，Selfgrow12，Selfgrow13，Selfgrow14，Selfgrow15，Selfgrow16，Selfgrow17，Selfgrow18，Selfgrow19}；

{Selfgrow9，Selfgrow10，Selfgrow11，Selfgrow12，Selfgrow13，Selfgrow14，Selfgrow15，Selfgrow16，Selfgrow17，Selfgrow18，Selfgrow19，Selfgrow20}；

{Selfgrow10，Selfgrow11，Selfgrow12，Selfgrow13，Selfgrow14，Selfgrow15，Selfgrow16，Selfgrow17，Selfgrow18，Selfgrow19，Selfgrow20，Selfgrow21}；

{Selfgrow11，Selfgrow12，Selfgrow13，Selfgrow14，Selfgrow15，Selfgrow16，Selfgrow17，Selfgrow18，Selfgrow19，Selfgrow20，Selfgrow21，Selfgrow22}；

{Selfgrow12，Selfgrow13，Selfgrow14，Selfgrow15，Selfgrow16，Selfgrow17，Selfgrow18，Selfgrow19，Selfgrow20，Selfgrow21，Selfgrow22，Selfgrow23}；

{Selfgrow13，Selfgrow14，Selfgrow15，Selfgrow16，Selfgrow17，Selfgrow18，Selfgrow19，Selfgrow20，Selfgrow21，Selfgrow22，Selfgrow23，Selfgrow24}；

{Selfgrow14，Selfgrow15，Selfgrow16，Selfgrow17，Selfgrow18，Selfgrow19，Selfgrow20，Selfgrow21，Selfgrow22，Selfgrow23，Selfgrow24，Selfgrow25}；

(3) And determining the sum of the sliding window difference values in each sliding window subsequence.

In the embodiment of the present specification, the sliding window difference is a natural growth increment. For each sliding window subsequence, the sum of the naturally-increasing increments therein (i.e., the sum value) can be calculated.

For example, taking the above-mentioned one sliding window subsequence { selfgroww 1, selfgroww 2, selfgroww 3, selfgroww 4, selfgroww 5, selfgroww 6, selfgroww 7, selfgroww 8, selfgroww 9, selfgroww 10, selfgroww 11, and selfgroww 12} as an example, the sum of sliding window differences within the sliding window subsequence sumgorw 1 can be calculated by the formula sumgorw 1 ═ selfgroww 1+ selfgroww 2+ … + selfgroww 12. Wherein, the sum of the sliding window differences in each sliding window subsequence can be used as a cumulative increment (for example, sumgorow 1-sumgorow 14 in fig. 5). The number of memory usage subintervals covered by the memory usage of the target server in the second time period may qualitatively indicate the fluctuation of the target server in the second time period, but may not quantitatively reflect the size of the short-time fluctuation. The increase of the memory usage of the target server in short time can be reflected quantitatively through the accumulated increase increment.

(4) And when at least one sliding window subsequence in the sliding window subsequences meets a preset condition, confirming that the target server has a sudden increase of the memory utilization rate in the second time period.

In some embodiments, the preset condition may include: the difference value of the sliding window positioned at the last position in the sliding window subsequence is larger than a first threshold value, and the sum value of the difference values of the sliding windows in the sliding window subsequence is larger than a second threshold value. The sliding window difference at the end of the sliding window subsequence is the last natural growth increment in the sliding window subsequence, for example, the above-mentioned one sliding window subsequence { Selfgrow1, Selfgrow2, Selfgrow3, Selfgrow4, Selfgrow5, Selfgrow6, Selfgrow7, Selfgrow8, Selfgrow9, Selfgrow10, Selfgrow11, Selfgrow12}, and "Selfgrow 12" is the sliding window difference at the end of the sliding window subsequence. The first threshold may be a constant a; the second threshold may be constant

a and b can be determined according to the characteristics of the server; m is the sliding window size, i.e. the number of individual sliding window subsequences, e.g. when there are 12 naturally increasing increments in a sliding window subsequence, then m equals 12.

Based on the preset conditions, whether the trend of the memory usage rate of the target server changes in a short time is increased or decreased can be identified, the amplitude of the trend of the change in the short time can be identified, and whether the memory usage rate of the target server increases in the short time or not can be judged according to the trend, so that whether the memory usage rate of the target server increases in the short time or not can be accurately identified. Therefore, when at least one sliding window subsequence in the sliding window subsequences meets the preset condition, the target server can be confirmed to have a sudden increase of the memory usage rate in the second time period.

In some embodiments, the determining the memory monitoring result of the target server according to the overall change trend of the memory usage and the memory usage in the second time period may include:

(1) and determining the slope of the overall change trend of the memory utilization rate.

In some embodiments, a least square method may be used to fit a variation curve of the memory usage rate in the first period of time; then, the slope of the start point and the end point of the change curve (i.e. the slope between the start point and the end point in the first period) is calculated and is taken as the slope of the overall change trend of the memory usage rate.

(2) And determining a first mean value of sliding window difference values in the sliding window difference value sequence corresponding to the second time period, and determining a second mean value of sliding window difference values in the sliding window difference value sequence corresponding to the appointed second time period.

(3) When the slope is greater than a slope threshold value and the first average value is greater than the second average value, confirming that the memory of the target server is abnormal (namely the memory utilization rate is abnormal); otherwise, it may be determined that the memory of the target server is normal (i.e., the memory usage rate is normal).

In other embodiments, the determining the memory monitoring result of the target server according to the overall change trend of the memory usage and the memory usage in the second time period may also include:

(2) And determining a first standard deviation of the sliding window difference value in the sliding window difference value sequence corresponding to the second time period, and determining a second standard deviation of the sliding window difference value in the sliding window difference value sequence corresponding to the appointed second time period.

(3) When the slope is greater than a slope threshold value and the first standard deviation is greater than the second standard deviation, determining that the memory of the target server is abnormal (namely the memory utilization rate is abnormal); otherwise, it may be determined that the memory of the target server is normal (i.e., the memory usage rate is normal).

In this embodiment of the present specification, the aforementioned specified second time period may refer to a corresponding statistical synchronization period, and may be set appropriately as needed. For example, in an exemplary embodiment, the first period is the last two weeks and the second period is the last three hours; the specified second period of time may be the last three hours of the week (i.e., the last three hours of the week ago). If the current time is 12:00 at 23.7.7.1 years, the second time period is 9: 00-12: 00 at 23.7.7.1 years, and the second time period is 9: 00-12: 00 at 16.7.7.7.1 years.

In view of the periodic characteristics of the memory usage data in many scenarios (the server increases faster in the periodic traffic peak, and then automatically recovers and decreases), the embodiment of the present specification realizes that the periodic increase can be filtered from two aspects:

1) in the aspect of long-term slow increase, namely the slope of the overall change trend of the memory utilization rate in the first period of time; taking the first time period of two weeks as an example, when the overall change trend of the memory usage rate in the first time period is an ascending trend, even if there is a periodic fluctuation, it is necessary to pay attention to whether the recovery is complete; here, the recovery means that: each time the periodic reclamation is performed, whether the memory usage rate can be decreased to the previous memory usage rate baseline is determined, that is, the memory usage rate does not increase before and after the increase and decrease of the memory usage rate, in other words, the cumulative increase in the period is 0 (or less than the set).

2) In the aspect of short-term sudden increase, the service period of the current related application is mostly hours, days and weeks; taking the first time period as the last two weeks, the second time period as the last three hours, and the second time period as the last three hours of the last week as an example, the statistical indexes of the two time periods of "the current three hours" and "the last week corresponds to the three hours" are used to filter most of the periodic fluctuation, for example, if the current time period is in a sudden increase state, but the increase amplitude is generally similar or relatively smaller than that of the last time period, it can be regarded that the memory usage rate is normal.

In some embodiments, when it is determined that the memory of the target server is abnormal, the memory abnormality warning information may be sent to a warning display end (e.g., a user terminal, a monitoring system, etc.) in time to remind relevant people of paying attention to or handling the memory abnormality warning information. The sending of the memory abnormal alarm information to the alarm display terminal can be realized by means of mail notification, short message notification or event notification.

For example, taking the mail notification as an example, the server with abnormal memory can be sequentially advanced according to the "early warning type (such as abnormal memory, abnormal load balance) → application → cluster → IP → two weeks of memory data change chart" by sending an early warning mail to the Notes mailbox system, so as to notify the relevant operation and maintenance personnel and the relevant operating system personnel to perform troubleshooting and handling of the abnormal problem. For another example, taking the event notification as an example, the operation and maintenance duty may be notified to process the relevant memory alarm by sending the memory abnormal alarm information to the alarm event list of the monitoring system.

In other embodiments, when the memory abnormality warning information is sent to the warning display end, the sending frequency can be properly controlled according to the memory abnormality degree, so that the purpose that the related personnel can be effectively notified of the memory abnormality warning information and not be disturbed too much is achieved. For example, in an exemplary embodiment, the memory monitoring is performed by performing a total polling once per hour, the number of mails sent by the server in 12 hours may be calculated, and for the memory abnormal alarm information obtained by polling each time, the number of alarm mails sending the same memory abnormal alarm information in 12 hours may be recorded in the database. For an abnormal server which is suspected of having abnormal memory but has the total memory utilization rate not exceeding 80% and unobtrusive growth, an alarm mail can be sent only once within 12 hours to remind relevant personnel to analyze and process. Wherein, the same memory abnormal alarm information means: and (4) alarming for memory abnormity of the same property of the same server.

While the process flows described above include operations that occur in a particular order, it should be appreciated that the processes may include more or less operations that are performed sequentially or in parallel (e.g., using parallel processors or a multi-threaded environment).

Corresponding to the above method for memory usage rate in the second time period, an embodiment of the present disclosure further provides a dynamic server memory monitoring device, and referring to fig. 6, in some embodiments, the dynamic server memory monitoring device may include:

the obtaining module 61 may be configured to obtain an overall change trend of the memory usage rate of the target server in a first time period, and obtain the number of memory usage rate subintervals covered by the memory usage rate of the target server in a second time period;

the determining module 62 may be configured to determine whether there is a sudden increase in the memory usage rate of the target server in the second time period when the overall change trend of the memory usage rate is an increasing trend, or the number of the memory usage rate subintervals reaches a fragmentation threshold;

the determining module 63 may be configured to determine a memory monitoring result of the target server according to the overall change trend of the memory usage and the memory usage in the second time period when the memory usage of the target server suddenly increases in the second time period.

In some embodiment of the apparatus, the obtaining of the overall change trend of the memory usage rate of the target server in the first time period may include:

In some embodiment of the apparatus, the obtaining the number of memory usage subintervals covered by the memory usage of the target server in the second period of time may include:

In some embodiment of the apparatus, the determining whether there is a sudden increase in the memory usage rate of the target server in the second time period may include:

wherein the preset conditions include:

In some device embodiments, the determining the memory monitoring result of the target server according to the overall change trend of the memory usage and the memory usage in the second time period includes:

In some device embodiments, the determining the memory monitoring result of the target server according to the overall change trend of the memory usage and the memory usage in the second time period may include:

In some embodiments of the apparatus, the determining a slope of the overall trend of the memory usage includes:

In some device embodiments, the first period comprises the last two weeks.

In some device embodiments, the second period of time comprises the last three hours.

In some apparatus embodiments, the specified second period of time comprises the last three hours of the week.

In other embodiments, the method and the device for dynamically monitoring the server memory may further use the monitoring result for memory performance analysis of the server cluster. For example, taking performance analysis as an example, the monitoring result may be sent to a performance analysis platform to perform visual display on the memory performance (for example, early warning record and processing record of memory abnormality, memory real-time data, memory development trend, and the like).

In other embodiments, the method and the device for dynamically monitoring the server memory may further use the monitoring result to evaluate a load balancing condition of the server cluster; the method comprises the steps of actively estimating whether the cluster is abnormal in load balance or not by evaluating the memory condition of each server of the same cluster, and informing professional maintenance personnel to troubleshoot problems in time when an abnormal cluster is found.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functions of the various elements may be implemented in the same one or more software and/or hardware implementations of the present description.

Embodiments of the present description also provide a computer device. As shown in FIG. 7, in some embodiments of the present description, the computer device 702 may include one or more processors 704, such as one or more Central Processing Units (CPUs) or Graphics Processors (GPUs), each of which may implement one or more hardware threads. The computer device 702 may also include any memory 706 for storing any type of information such as code, settings, data, etc., and in one embodiment, a computer program stored on the memory 706 and executable on the processor 704, which when executed by the processor 704, may perform the instructions of the memory usage method during the second time period as described in any of the embodiments above. For example, and without limitation, the memory 706 can include any one or more of the following in combination: any type of RAM, any type of ROM, flash memory devices, hard disks, optical disks, etc. More generally, any memory may use any technology to store information. Further, any memory may provide volatile or non-volatile retention of information. Further, any memory may represent fixed or removable components of computer device 702. In one case, when the processor 704 executes associated instructions that are stored in any memory or combination of memories, the computer device 702 can perform any of the operations of the associated instructions. The computer device 702 also includes one or more drive mechanisms 708, such as a hard disk drive mechanism, an optical disk drive mechanism, or the like, for interacting with any memory.

Computer device 702 can also include input/output interface 710(I/O) for receiving various inputs (via input device 712) and for providing various outputs (via output device 714). One particular output mechanism may include a presentation device 716 and an associated graphical user interface 718 (GUI). In other embodiments, input/output interface 710(I/O), input device 712, and output device 714 may also not be included, as only one computer device in a network. Computer device 702 can also include one or more network interfaces 720 for exchanging data with other devices via one or more communication links 722. One or more communication buses 724 couple the above-described components together.

Communication link 722 may be implemented in any manner, such as over a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. Communication link 722 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc., governed by any protocol or combination of protocols.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products of some embodiments of the specification. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processor to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processor, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processor to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processor to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computer device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium which can be used to store information that can be accessed by a computer device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.

The embodiments of this specification may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The described embodiments may also be practiced in distributed computing environments where tasks are performed by remote processors that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

It should also be understood that, in the embodiment of the present specification, the term "and/or" is only one kind of association relation describing an associated object, and means that three kinds of relations may exist. For example, a and/or B, may represent: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A dynamic monitoring method for a server memory is characterized by comprising the following steps:

2. The method for dynamically monitoring the memory of the server according to claim 1, wherein the obtaining of the overall change trend of the memory usage rate of the target server in the first time period comprises:

3. The method for dynamically monitoring the memory of the server according to claim 1, wherein the obtaining the number of memory usage rate subintervals covered by the memory usage rate of the target server in the second period of time comprises:

4. The method for dynamically monitoring the memory of the server according to claim 1, wherein the determining whether the target server has a sudden increase in the memory usage rate in the second period of time includes:

wherein the preset conditions include:

5. The method for dynamically monitoring the memory of the server according to claim 4, wherein the determining the memory monitoring result of the target server according to the overall change trend of the memory usage and the memory usage in the second period of time includes:

6. The method for dynamically monitoring the memory of the server according to claim 5, wherein the determining the memory monitoring result of the target server according to the overall change trend of the memory usage and the memory usage in the second period of time includes:

7. The method for dynamically monitoring the memory of the server according to claim 1, wherein the determining the slope of the overall change trend of the memory usage rate comprises:

8. The method for dynamically monitoring memory in a server according to claim 1, wherein the first period comprises the last two weeks.

9. The method for dynamically monitoring memory of a server according to claim 1, wherein the second period of time comprises the last three hours.

10. The method for dynamically monitoring memory of a server according to claim 5 or 6, wherein the specified second period of time comprises the last three hours of the last week.

11. A dynamic monitoring device for a server memory is characterized by comprising:

12. A computer device comprising a memory, a processor, and a computer program stored on the memory, wherein the computer program, when executed by the processor, performs the instructions of the method of any one of claims 1-10.

13. A computer storage medium on which a computer program is stored, characterized in that the computer program, when being executed by a processor of a computer device, executes instructions of a method according to any one of claims 1-10.