CN111901172B - Application service monitoring method and system based on cloud computing environment - Google Patents
Application service monitoring method and system based on cloud computing environmentDownload PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0677—Localisation of faults
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/22—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks comprising specially adapted graphical user interfaces [GUI]
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
- H04L41/5003—Managing SLA; Interaction between SLA and QoS
- H04L41/5009—Determining service level performance parameters or violations of service level contracts, e.g. violations of agreed response time or mean time between failures [MTBF]
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/04—Processing captured monitoring data, e.g. for logfile generation
- H04L43/045—Processing captured monitoring data, e.g. for logfile generation for graphical visualisation of monitoring data
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
Description
Technical Field
The invention relates to the field of government cloud environment analysis, in particular to an application service monitoring method and system based on a cloud computing environment.
Background
With the rapid development and maturity of cloud computing, more and more user data are migrated to a cloud computing cloud server, and in addition, the application service scale is gradually expanded due to the cloud policy of government departments, so that great challenges are brought to the management and maintenance of application services of all government cloud centers, and unified monitoring and management application are imperative.
In the face of huge and complex network environment under cloud computing, on the premise of avoiding influencing the use of clients, timely discovery of application services when faults occur becomes particularly important, feedback is carried out only when the clients cannot normally use the network environment in the past, related personnel can conduct check processing, the obstacle clearing process is relatively complex, and the user experience of the clients and the processing efficiency of operation and maintenance personnel are greatly influenced. Therefore, how to perform centralized supervision, analysis and visual display on the state and performance information of the application service, and the like, and ensure that the application service fault in the cloud environment is rapidly located is a technical problem to be solved at present.
Disclosure of Invention
The technical task of the invention is to provide an application service monitoring method and system based on a cloud computing environment, which are used for solving the problems of centralized supervision, analysis and visual display of state and performance information of application services and the like and ensuring quick positioning of application service faults in the cloud environment.
The technical task of the invention is realized in the following way, and the application service monitoring method based on the cloud computing environment comprises the following steps:
s1, detecting application service by adopting a multi-source detection mode;
s2, deploying an aggregation application service monitoring client in an OpenCenter environment;
s3, deploying a local application service monitoring client on a collector of the government cloud center;
s4, running the application service clients deployed on the convergence and the local in a timing task mode, and periodically monitoring the transition of the application service state;
s5, the application service monitoring client side pushes the alarm to the alarm system message queue from the application service which normally changes the service state into abnormal state;
s6, the application service monitoring client pushes and clears the alarm to an alarm system message queue when the abnormal service state is converted into normal application service;
s7, displaying abnormal alarms pushed by the application service monitoring client and carried performance data in a visual mode of an alarm list by the foreground page, and accurately and quickly analyzing the current service state through the performance data of the application service;
s8, the OpenCenter convergence application service monitoring client performs abnormal data verification with the local application service monitoring client of each government cloud center.
Preferably, the detection of the application service in the step S1 by adopting a multi-source detection method is specifically as follows:
s101, detecting the internal environment and judging whether the internal environment is smooth or not:
(1) if the internal detection is not successful, locating as the state reason of the application itself;
(2) if the internal detection is clear, taking network reasons into consideration, executing step S102 next;
s102, checking network reasons: starting from the nat conversion, the nat converts the external network address into the internal network address through the router or firewall;
s103, judging whether conversion exists by acquiring a nat conversion table on the router or the firewall:
(1) if so, positioning the problem as an extranet problem;
(2) if the problem does not exist, positioning the problem to the intranet problem;
in the step S2, a converged application service monitoring client is deployed in an OpenCenter environment as a monitoring center to centrally and uniformly control government cloud center application services of all nanotubes, and the concurrent processing performance is reminded in a multithreading mode, wherein the concurrent processing is to ensure that the monitoring period is within 5 minutes, divide every 100 application services into separate sub-program detection processes, and execute all sub-programs concurrently, thereby effectively ensuring the high efficiency of the processing;
and an application service monitoring client additionally provided with an intranet monitoring mode is deployed on the acquisition machine in the step S3, and when the condition that the reference service runs normally but the program detection is abnormal due to network factors of unconfigured routing occurs on the acquisition machine, a cloud center ntp server is used as a front-end processor agent to execute a command through elastic configuration of a relevant configuration file, so that the high availability of the program is ensured.
Preferably, the timing task manner in the step S4 means that the client performs application service monitoring at a timing with granularity of 5 minutes;
the transition of the service state in the step S4 includes a transition between an abnormal state and a normal state; wherein the abnormal state includes an application service state abnormality (pages 400, 404, etc.) and an application service timeout abnormality (connection timeout, resolution timeout);
preferably, the abnormal application service in step S5 means that in the same period, if the detection is normal, the detection is repeated until 3 times, and the client records the final abnormal result to the cache; in order to prevent the influence of network fluctuation and other reasons, when 3 continuous periods are abnormal, pushing the alarm, wherein the 3 continuous periods still are abnormal and record continuous times, but the alarm is not repeatedly sent;
the application service monitoring client in step S6 compares whether the normal application service is in the abnormal service cache or not:
if yes, pushing the clearing alarm to an alarm system message queue for alarm clearing, recording the maximum continuous abnormal times and clearing the current continuous abnormal times, and when the next continuous times of the application service reach the maximum continuous abnormal times again, sending the alarm again;
if not, the method is skipped normally.
Preferably, the monitoring process of the OpenCenter converged application service monitoring client in the step S8 is specifically as follows:
deploying an application service monitoring program on an OpenCenter converged application service monitoring client;
flexibly configuring application service type information to be monitored and information of alarm pushing; the application service type information comprises a domain name and an external network ip address;
thirdly, detecting the domain name by using a curl command, returning to the state code 200 to normally pass, and judging whether to continuously monitor 3 times of abnormality when returning to abnormality, so as to prevent the cause interference of network fluctuation:
(1) if yes, executing the step (IV);
(2) if not, jumping to the step (nine);
(IV) judging whether the anomaly type is an application service state anomaly or an application service timeout anomaly:
(1) if the application service status is abnormal (i.e., there is a specific exception return code 400 or 404), then performing step (eight);
(2) if the application service timeout is abnormal (connection timeout, analysis timeout, etc.) or the state returns to the application service of 000, executing the step (fifth);
(V) detecting the domain name again by a wget command;
(VI), dynamically detecting the overtime condition by adopting an atomic suppression mode by the wget, and judging whether the overtime condition is abnormal or not:
(1) if yes, executing the step (seventh);
(2) if not, regarding the application service of which the Curl is abnormal and the wget is normal as normal processing, wherein the initial timeout time is 15s, and when the detection is carried out for 5s for 3 times continuously and every time, the service performance is considered to be problematic (the user experience is affected), and the step (nine) is skipped;
seventhly, detecting the domain name overtime abnormality again by using a curl to the external network ip address, exploring whether application service is unavailable due to the analysis problem, and simulating and logging the use command to monitor the state of the application service when detecting whether the application service is available after logging is required; judging whether to monitor 3 times of abnormality continuously:
(1) if yes, executing the step (eight);
(2) if not, jumping to the step (eight);
pushing alarm information, namely pushing and clearing alarms to an alarm system message queue when the abnormal application service information is cached each time and detected as normal next time, and zeroing the current continuous abnormal times;
and (ninth), ending.
Preferably, the monitoring process of the local application service monitoring client of the government cloud center in the step S8 is specifically as follows:
(1) An application service monitoring program is deployed at each government cloud center local application service monitoring client;
(2) Flexibly configuring application service types to be monitored, wherein the application service types comprise domain names, external network ip addresses and internal network ip addresses; when the intranet detection is affected due to the route configuration, additionally configuring a cloud center ntp server as a front-end processor calling command to detect;
(3) Detecting a domain name by using a curl command, returning the state code 200 to normally pass, and judging whether to continuously monitor 3 times of abnormality when returning to abnormality, so as to prevent the cause interference of network fluctuation:
(1) if yes, executing the step (4);
(2) if not, jumping to the step (10);
(4) Judging whether the anomaly type is an application service state anomaly or an application service timeout anomaly:
(1) if the application service status is abnormal (i.e. there is a specific exception return code 400 or 404), then step (9) is performed;
(2) if the application service timeout is abnormal (connection timeout, analysis timeout, etc.) or the state returns to the application service of 000, executing the step (5);
(5) Detecting the domain name again by a wget command;
(6) Dynamically detecting the overtime condition by adopting an atomic suppression mode, and judging whether the overtime condition is abnormal or not:
(1) if yes, executing the step (7);
(2) if not, regarding the application service of which the Curl is abnormal and the wget is normal as normal processing, wherein the initial timeout time is 15s, and when the detection is carried out for 5s for 3 times continuously and every time, the service performance is considered to be problematic (the user experience is affected), and the step (9) is skipped;
(7) Detecting the domain name overtime abnormality by using a curl again for the external network ip address, exploring whether application service is unavailable due to the analysis problem, and simulating and logging in a command to monitor the state of the application service when detecting whether the application service is available after logging in is required; judging whether to monitor 3 times of abnormality continuously:
(1) if yes, executing the step (8);
(2) if not, jumping to the step (9);
(8) Performing intranet detection by using a curl, and judging whether the intranet is abnormal three times continuously:
(1) if yes, executing the step (9);
(2) if not, executing the step (9);
(9) Pushing alarm information, namely pushing and clearing alarms to an alarm system message queue when the abnormal application service information is cached for each time and detected as normal next time, and zeroing the current continuous abnormal times;
(10) And ending.
In the application service detection process, the granularity of the monitoring time is 5 minutes, the current abnormal times (normal default is 0 and the abnormalities are accumulated) and the historical maximum abnormal times (normal default is 3 and the abnormalities are accumulated) of the cache are detected each time, and when the historical maximum abnormal times are not reached, the alarm is not pushed and only the current times are accumulated; when the current times of abnormal application services are greater than or equal to the historical maximum times, pushing alarms to an alarm system message queue, and accumulating the current and historical abnormal times at the same time.
More preferably, the abnormal data verification between the OpenCenter converged application service monitoring client in the step S8 and the local application service monitoring client of each government cloud center is specifically as follows:
the OpenCenter converged application service monitoring client and the local application service monitoring client of the government cloud center execute monitoring programs at the same granularity, and when abnormal alarms are detected, the OpenCenter converged application service monitoring client and the local application service monitoring client can communicate in real time, and whether the OpenCenter converged application service monitoring client and the local application service monitoring client are the same abnormal application service is compared:
when abnormality is detected at the same time, normally pushing abnormal application alarm information;
when one part detects the abnormality and the other part does not detect the abnormality, the operation and maintenance personnel are informed to conduct investigation, and the alarm accuracy is ensured.
An application service monitoring system based on cloud computing environment, the system comprises,
the detection unit is used for detecting the application service in a multi-source detection mode;
the convergence deployment unit is used for deploying the convergence application service monitoring client in the OpenCenter environment;
the local deployment unit is used for deploying the local application service monitoring client on the acquisition machine of the government cloud center;
the periodic monitoring unit is used for deploying the application service clients on the convergence and the local to run in a timed task mode and periodically monitoring the transition of the application service state;
the alarm pushing unit is used for pushing the alarm to the alarm system message queue from the application service monitoring client side for normally converting the service state into the abnormal service state;
the alarm clearing unit is used for pushing and clearing alarms to an alarm system message queue from the application service monitoring client side for converting the abnormal service state into normal application service;
the visualization unit is used for displaying abnormal alarms and carried performance data pushed by the application service monitoring client in a visualization mode of the alarm list on the foreground page, and accurately and quickly analyzing the current service state through the performance data of the application service;
the verification unit is used for carrying out abnormal data verification on the OpenCenter converged application service monitoring client and the local application service monitoring client of each government cloud center; the method comprises the following steps:
after the OpenCenter convergence application service monitoring client detects the abnormality, checking whether the corresponding local cloud center detects the same abnormal condition or not when pushing an alarm:
if yes, normally pushing an alarm;
if not, notifying corresponding operation and maintenance personnel to check and treat, and ensuring the accuracy of the abnormal information.
An electronic device, comprising: a memory and at least one processor;
wherein the memory stores computer-executable instructions;
the at least one processor executes the computer-executable instructions stored by the memory, causing the at least one processor to perform an application service monitoring method in a cloud-based computing environment as described above.
A computer readable storage medium having stored therein computer executable instructions that when executed by a processor perform an application service monitoring method in a cloud-based computing environment as described above.
The application service monitoring method and system based on the cloud computing environment have the following advantages:
the invention can continuously detect the application service state throughout the day through application service monitoring, find abnormality and process under the condition that the client does not sense, or can ensure that the client is informed in advance to improve the user experience, rather than waiting for the feedback of the client to know afterward and leak repair;
secondly, an application service monitoring program is deployed in a government cloud center, so that the problem that the application service cannot be found in time when the application service is abnormal in the government cloud environment is solved, and the reasons, positions and the like of the fault problem can be rapidly positioned according to the pushed alarm information and performance data;
the method and the system can automatically analyze the quality and the state of the application service in the government cloud environment, can automatically push the alarm aiming at the generation of abnormal conditions, can automatically trigger the alarm clearing mechanism after the abnormal recovery, and have high sensitivity and high accuracy.
Drawings
The invention is further described below with reference to the accompanying drawings.
FIG. 1 is a flow diagram of an application service monitoring method based on a cloud computing environment;
FIG. 2 is a flow chart of OpenCenter converged application service monitoring client monitoring;
FIG. 3 is a block flow diagram of local application service monitoring client monitoring in a government cloud center;
FIG. 4 is a schematic diagram of the nat mapping principle;
FIG. 5 is an interface screenshot of an alarm list presentation;
fig. 6 is a schematic diagram of an OpenCenter converged application service monitoring client performing abnormal data verification with a local application service monitoring client of each government cloud center.
Detailed Description
The application service monitoring method and system based on the cloud computing environment of the present invention are described in detail below with reference to the accompanying drawings and specific embodiments.
Example 1:
as shown in fig. 1, the application service monitoring method based on the cloud computing environment of the present invention specifically comprises the following steps:
s1, detecting application service by adopting a multi-source detection mode; the method comprises the following steps:
s101, detecting the internal environment and judging whether the internal environment is smooth or not:
(1) if the internal detection is not successful, locating as the state reason of the application itself;
(2) if the internal detection is clear, taking network reasons into consideration, executing step S102 next;
s102, checking network reasons: starting from the nat conversion, the nat converts the external network address into the internal network address through the router or firewall;
s103, judging whether conversion exists by acquiring a nat conversion table on the router or the firewall:
(1) if so, positioning the problem as an extranet problem;
(2) if the problem does not exist, the problem is positioned to the intranet problem.
As shown in fig. 4, the mapping principle of nat is that legal ip addresses are respectively interconnected with external network and nat mapping, and nat mapping is interconnected with internal network.
S2, deploying an aggregation application service monitoring client in an OpenCenter environment, intensively and uniformly controlling government cloud center application services of all nanotubes as a monitoring center, reminding concurrent processing performance in a multithreading mode, wherein the concurrent processing is to ensure that the monitoring period is within 5 minutes, dividing every 100 application services into independent subprograms for detection processing, and executing all subprograms concurrently, thereby effectively ensuring the high efficiency of processing;
s3, deploying a local application service monitoring client on a collector of the government cloud center; an application service monitoring client in an intranet monitoring mode is additionally arranged on the acquisition machine, and when the condition that the reference service runs normally but the program detection is abnormal due to network factors of unconfigured routing occurs on the acquisition machine, a cloud center ntp server is used as a front-end processor agent to execute a command through elastic configuration of a related configuration file, so that high availability of the program is ensured.
S4, running the application service clients deployed on the convergence and the local in a timing task mode, and periodically monitoring the transition of the application service state; the timing task mode is that the client side executes application service monitoring at regular time with granularity of 5 minutes; the transition of the service state includes a transition between the abnormal state and the normal state; wherein the abnormal state includes an application service state abnormality (pages 400, 404, etc.) and an application service timeout abnormality (connection timeout, resolution timeout);
s5, the application service monitoring client side pushes the alarm to the alarm system message queue from the application service which normally changes the service state into abnormal state; the abnormal application service means that in the same period, if the detection is normal, the abnormal application service passes, if the detection is abnormal, the detection is repeated for 3 times, and the client records the final abnormal result to the cache; in order to prevent the influence of network fluctuation and other reasons, when 3 continuous periods are abnormal, pushing the alarm, wherein the 3 continuous periods still are abnormal and record continuous times, but the alarm is not repeatedly sent;
s6, the application service monitoring client pushes and clears the alarm to an alarm system message queue when the abnormal service state is converted into normal application service; wherein the application service monitoring client will compare whether this normal application service is in the abnormal service cache:
if yes, pushing the clearing alarm to an alarm system message queue for alarm clearing, recording the maximum continuous abnormal times and clearing the current continuous abnormal times, and when the next continuous times of the application service reach the maximum continuous abnormal times again, sending the alarm again;
if not, the method is skipped normally.
S7, displaying abnormal alarms pushed by the application service monitoring client and carried performance data in a visual mode of an alarm list by the foreground page, and accurately and quickly analyzing the current service state through the performance data of the application service; as shown in fig. 5, the page shows the following specific functions:
(1) the operation and maintenance personnel can check the application service alarm and detailed information in any time period through the provided Web interface; the detailed information comprises an abnormal application service name, a domain name, an external network ip address, an abnormal application service type, a possible reason and the like;
(2) the front page can manually clear the abnormal alarm by operation and maintenance personnel.
S8, the OpenCenter convergence application service monitoring client performs abnormal data verification with the local application service monitoring client of each government cloud center.
As shown in fig. 2, the monitoring process of the OpenCenter converged application service monitoring client specifically includes:
deploying an application service monitoring program on an OpenCenter converged application service monitoring client;
flexibly configuring application service type information to be monitored and information of alarm pushing; the application service type information comprises a domain name and an external network ip address;
thirdly, detecting the domain name by using a curl command, returning to the state code 200 to normally pass, and judging whether to continuously monitor 3 times of abnormality when returning to abnormality, so as to prevent the cause interference of network fluctuation:
(1) if yes, executing the step (IV);
(2) if not, jumping to the step (nine);
(IV) judging whether the anomaly type is an application service state anomaly or an application service timeout anomaly:
(1) if the application service status is abnormal (i.e., there is a specific exception return code 400 or 404), then performing step (eight);
(2) if the application service timeout is abnormal (connection timeout, analysis timeout, etc.) or the state returns to the application service of 000, executing the step (fifth);
(V) detecting the domain name again by a wget command;
(VI), dynamically detecting the overtime condition by adopting an atomic suppression mode by the wget, and judging whether the overtime condition is abnormal or not:
(1) if yes, executing the step (seventh);
(2) if not, regarding the application service of which the Curl is abnormal and the wget is normal as normal processing, wherein the initial timeout time is 15s, and when the detection is carried out for 5s for 3 times continuously and every time, the service performance is considered to be problematic (the user experience is affected), and the step (nine) is skipped;
seventhly, detecting the domain name overtime abnormality again by using a curl to the external network ip address, exploring whether application service is unavailable due to the analysis problem, and simulating and logging the use command to monitor the state of the application service when detecting whether the application service is available after logging is required; judging whether to monitor 3 times of abnormality continuously:
(1) if yes, executing the step (eight);
(2) if not, jumping to the step (eight);
pushing alarm information, namely pushing and clearing alarms to an alarm system message queue when the abnormal application service information is cached each time and detected as normal next time, and zeroing the current continuous abnormal times;
and (ninth), ending.
As shown in fig. 3, the monitoring process of the local application service monitoring client of the government cloud center is specifically as follows:
(1) An application service monitoring program is deployed at each government cloud center local application service monitoring client;
(2) Flexibly configuring application service types to be monitored, wherein the application service types comprise domain names, external network ip addresses and internal network ip addresses; when the intranet detection is affected due to the route configuration, additionally configuring a cloud center ntp server as a front-end processor calling command to detect;
(3) Detecting a domain name by using a curl command, returning the state code 200 to normally pass, and judging whether to continuously monitor 3 times of abnormality when returning to abnormality, so as to prevent the cause interference of network fluctuation:
(1) if yes, executing the step (4);
(2) if not, jumping to the step (10);
(4) Judging whether the anomaly type is an application service state anomaly or an application service timeout anomaly:
(1) if the application service status is abnormal (i.e. there is a specific exception return code 400 or 404), then step (9) is performed;
(2) if the application service timeout is abnormal (connection timeout, analysis timeout, etc.) or the state returns to the application service of 000, executing the step (5);
(5) Detecting the domain name again by a wget command;
(6) Dynamically detecting the overtime condition by adopting an atomic suppression mode, and judging whether the overtime condition is abnormal or not:
(1) if yes, executing the step (7);
(2) if not, regarding the application service of which the Curl is abnormal and the wget is normal as normal processing, wherein the initial timeout time is 15s, and when the detection is carried out for 5s for 3 times continuously and every time, the service performance is considered to be problematic (the user experience is affected), and the step (9) is skipped;
(7) Detecting the domain name overtime abnormality by using a curl again for the external network ip address, exploring whether application service is unavailable due to the analysis problem, and simulating and logging in a command to monitor the state of the application service when detecting whether the application service is available after logging in is required; judging whether to monitor 3 times of abnormality continuously:
(1) if yes, executing the step (8);
(2) if not, jumping to the step (9);
(8) Performing intranet detection by using a curl, and judging whether the intranet is abnormal three times continuously:
(1) if yes, executing the step (9);
(2) if not, executing the step (9);
(9) Pushing alarm information, namely pushing and clearing alarms to an alarm system message queue when the abnormal application service information is cached for each time and detected as normal next time, and zeroing the current continuous abnormal times;
(10) And ending.
In the application service detection process, the granularity of the monitoring time is 5 minutes, the current abnormal times (normal default is 0 and the abnormalities are accumulated) and the historical maximum abnormal times (normal default is 3 and the abnormalities are accumulated) of the cache are detected each time, and when the historical maximum abnormal times are not reached, the alarm is not pushed and only the current times are accumulated; when the current times of abnormal application services are greater than or equal to the historical maximum times, pushing alarms to an alarm system message queue, and accumulating the current and historical abnormal times at the same time.
As shown in fig. 6, the abnormal data verification between the OpenCenter converged application service monitoring client and the local application service monitoring client of each government cloud center is specifically as follows:
the OpenCenter converged application service monitoring client and the local application service monitoring client of the government cloud center execute monitoring programs at the same granularity, and when abnormal alarms are detected, the OpenCenter converged application service monitoring client and the local application service monitoring client can communicate in real time, and whether the OpenCenter converged application service monitoring client and the local application service monitoring client are the same abnormal application service is compared:
when abnormality is detected at the same time, normally pushing abnormal application alarm information;
when one part detects the abnormality and the other part does not detect the abnormality, the operation and maintenance personnel are informed to conduct investigation, and the alarm accuracy is ensured.
Example 2:
the invention relates to an application service monitoring system based on cloud computing environment, which comprises,
the detection unit is used for detecting the application service in a multi-source detection mode;
the convergence deployment unit is used for deploying the convergence application service monitoring client in the OpenCenter environment;
the local deployment unit is used for deploying the local application service monitoring client on the acquisition machine of the government cloud center;
the periodic monitoring unit is used for deploying the application service clients on the convergence and the local to run in a timed task mode and periodically monitoring the transition of the application service state;
the alarm pushing unit is used for pushing the alarm to the alarm system message queue from the application service monitoring client side for normally converting the service state into the abnormal service state;
the alarm clearing unit is used for pushing and clearing alarms to an alarm system message queue from the application service monitoring client side for converting the abnormal service state into normal application service;
the visualization unit is used for displaying abnormal alarms and carried performance data pushed by the application service monitoring client in a visualization mode of the alarm list on the foreground page, and accurately and quickly analyzing the current service state through the performance data of the application service;
the verification unit is used for carrying out abnormal data verification on the OpenCenter converged application service monitoring client and the local application service monitoring client of each government cloud center; the method comprises the following steps:
after the OpenCenter convergence application service monitoring client detects the abnormality, checking whether the corresponding local cloud center detects the same abnormal condition or not when pushing an alarm:
if yes, normally pushing an alarm;
if not, notifying corresponding operation and maintenance personnel to check and treat, and ensuring the accuracy of the abnormal information.
Example 3:
the embodiment of the invention also provides electronic equipment, which comprises: a memory and a processor;
wherein the memory stores computer-executable instructions;
one processor executes the computer-executable instructions stored by the memory, causing the one processor to perform the application service monitoring method in a cloud-based computing environment as in embodiment 1.
Example 6:
the embodiment of the invention also provides a computer readable storage medium, wherein a plurality of instructions are stored, and the instructions are loaded by a processor, so that the processor executes the application service monitoring method based on the cloud computing environment in any embodiment of the invention. Specifically, a system or apparatus provided with a storage medium on which a software program code realizing the functions of any of the above embodiments is stored, and a computer (or CPU or MPU) of the system or apparatus may be caused to read out and execute the program code stored in the storage medium.
In this case, the program code itself read from the storage medium may realize the functions of any of the above-described embodiments, and thus the program code and the storage medium storing the program code form part of the present invention.
Examples of storage media for providing program code include floppy disks, hard disks, magneto-optical disks, optical disks (e.g., CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-R based application service monitoring methods and systems M, DVD-RW, DVD+RW) in a cloud computing environment, magnetic tapes, nonvolatile memory cards, and ROMs. Alternatively, the program code may be downloaded from a server computer by a communication network.
Further, it should be apparent that the functions of any of the above-described embodiments may be implemented not only by executing the program code read out by the computer, but also by causing an operating system or the like operating on the computer to perform part or all of the actual operations based on the instructions of the program code.
Further, it is understood that the program code read out by the storage medium is written into a memory provided in an expansion board inserted into a computer or into a memory provided in an expansion unit connected to the computer, and then a CPU or the like mounted on the expansion board or the expansion unit is caused to perform part and all of actual operations based on instructions of the program code, thereby realizing the functions of any of the above embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (9)
1. The application service monitoring method based on the cloud computing environment is characterized by comprising the following steps of:
s1, detecting application service by adopting a multi-source detection mode; the method comprises the following steps:
s101, detecting the internal environment and judging whether the internal environment is smooth or not:
(1) if the internal detection is not successful, locating as the state reason of the application itself;
(2) if the internal detection is clear, taking network reasons into consideration, executing step S102 next;
s102, checking network reasons: starting from the nat conversion, the nat converts the external network address into the internal network address through the router or firewall;
s103, judging whether conversion exists by acquiring a nat conversion table on the router or the firewall:
(1) if so, positioning the problem as an extranet problem;
(2) if the problem does not exist, positioning the problem to the intranet problem;
s2, deploying an aggregation application service monitoring client in an OpenCenter environment;
s3, deploying a local application service monitoring client on a collector of the government cloud center;
s4, the application service monitoring clients deployed on the aggregation and the local are operated in a timing task mode, and the application service state is periodically monitored;
s5, the application service monitoring client side pushes the alarm to the alarm system message queue from the application service which normally changes the service state into abnormal state;
s6, the application service monitoring client pushes and clears the alarm to an alarm system message queue when the abnormal service state is converted into normal application service;
s7, displaying abnormal alarms pushed by the application service monitoring client and carried performance data in a visual mode of an alarm list by the foreground page, and accurately and quickly analyzing the current service state through the performance data of the application service;
s8, the OpenCenter convergence application service monitoring client performs abnormal data verification with the local application service monitoring client of each government cloud center; the method comprises the following steps:
the OpenCenter converged application service monitoring client and the local application service monitoring client of the government cloud center execute monitoring programs at the same granularity, and when abnormal alarms are detected, the OpenCenter converged application service monitoring client and the local application service monitoring client can communicate in real time, and whether the OpenCenter converged application service monitoring client and the local application service monitoring client are the same abnormal application service is compared:
when abnormality is detected at the same time, normally pushing abnormal application alarm information;
when one party detects the abnormality and the other party does not detect the abnormality, the operation and maintenance personnel are notified to conduct investigation, and the alarm accuracy is ensured.
2. The method for monitoring application services in cloud computing environment according to claim 1, wherein in step S2, an converged application service monitoring client is deployed in an OpenCenter environment as a monitoring center to centrally and uniformly manage all the government cloud center application services of the nanotubes, and the concurrent processing performance is reminded in a multithreading manner;
and an application service monitoring client additionally provided with an intranet monitoring mode is deployed on the acquisition machine in the step S3, and when the condition that the application service runs normally but the program detection is abnormal due to network factors of unconfigured routing occurs on the acquisition machine, a cloud center ntp server is used as a front-end processor agent to execute a command through elastically configuring a relevant configuration file.
3. The method for monitoring application services in a cloud computing environment according to claim 1, wherein the timing task manner in step S4 means that the client performs application service monitoring at a timing with granularity of 5 minutes;
the transition of the service state in the step S4 includes a transition between an abnormal state and a normal state; the abnormal state comprises abnormal state of the application service and abnormal overtime state of the application service.
4. The method for monitoring application services based on cloud computing environment according to claim 1, wherein the abnormal application services in step S5 means that in the same period, if the detection is normal, the detection is repeated until 3 times, and the client records the final abnormal result to the cache; when 3 continuous periods are abnormal, pushing the alarm, wherein the 3 continuous periods still are abnormal, recording continuous times, and not repeatedly sending the alarm;
the application service monitoring client in step S6 compares whether the normal application service is in the abnormal service cache or not:
if yes, pushing the clearing alarm to an alarm system message queue for alarm clearing, recording the maximum continuous abnormal times and clearing the current continuous abnormal times, and when the next continuous times of the application service reach the maximum continuous abnormal times again, sending the alarm again;
if not, the method is skipped normally.
5. The application service monitoring method based on the cloud computing environment according to claim 1, wherein the OpenCenter converged application service monitoring client monitoring process in step S8 is specifically as follows:
deploying an application service monitoring program on an OpenCenter converged application service monitoring client;
secondly, configuring application service type information to be monitored and information of alarm pushing; the application service type information comprises a domain name and an external network ip address;
(III) detecting the domain name by using a curl command, returning to the state code 200 to normally pass, and judging whether to continuously monitor 3 times of abnormality when abnormality is returned:
(1) if yes, executing the step (IV);
(2) if not, jumping to the step (nine);
(IV) judging whether the anomaly type is an application service state anomaly or an application service timeout anomaly:
(1) if the application service state is abnormal, executing the step (eight);
(2) if the application service is abnormal in overtime or the state returns to the application service with 000, executing the step (fifth);
(V) detecting the domain name again by a wget command;
(VI), dynamically detecting the overtime condition by adopting an atomic suppression mode by the wget, and judging whether the overtime condition is abnormal or not:
(1) if yes, executing the step (seventh);
(2) if not, regarding the application service of which the Curl is abnormal and the wget is normal as normal processing, wherein the initial timeout time is 15s, and when the detection is abnormal or the detection is carried out every 5s of continuous 3 times, the service performance is considered to be problematic, and the step (nine) is skipped;
seventhly, detecting the domain name overtime abnormality again by using a curl to the external network ip address, exploring whether application service is unavailable due to the analysis problem, and simulating and logging the use command to monitor the state of the application service when detecting whether the application service is available after logging is required; judging whether to monitor 3 times of abnormality continuously:
(1) if yes, executing the step (eight);
(2) if not, jumping to the step (eight);
pushing alarm information, namely pushing and clearing alarms to an alarm system message queue when the abnormal application service information is cached each time and detected as normal next time, and zeroing the current continuous abnormal times;
and (ninth), ending.
6. The method for monitoring application services in cloud computing environment according to claim 1, wherein the monitoring process of the local application service monitoring client of the government cloud center in step S8 is specifically as follows:
(1) An application service monitoring program is deployed at each government cloud center local application service monitoring client;
(2) Configuring application service types to be monitored, wherein the application service types comprise domain names, external network ip addresses and internal network ip addresses; when the intranet detection is affected due to the route configuration, additionally configuring a cloud center ntp server as a front-end processor calling command to detect;
(3) Detecting the domain name by using a curl command, returning the state code 200 to normally pass, and judging whether to continuously monitor 3 times of abnormality when abnormality is returned:
(1) if yes, executing the step (4);
(2) if not, jumping to the step (10);
(4) Judging whether the anomaly type is an application service state anomaly or an application service timeout anomaly:
(1) if the application service state is abnormal, executing the step (9);
(2) if the application service is abnormal in overtime or the state returns to the application service with 000, executing the step (5);
(5) Detecting the domain name again by a wget command;
(6) Dynamically detecting the overtime condition by adopting an atomic suppression mode, and judging whether the overtime condition is abnormal or not:
(1) if yes, executing the step (7);
(2) if not, regarding the application service of which the Curl is abnormal and the wget is normal as normal processing, wherein the initial timeout time is 15s, and when the detection is abnormal or the detection is carried out every 5s of continuous 3 times, the service performance is considered to be problematic, and the step (9) is skipped;
(7) Detecting the domain name overtime abnormality by using a curl again for the external network ip address, exploring whether application service is unavailable due to the analysis problem, and simulating and logging in a command to monitor the state of the application service when detecting whether the application service is available after logging in is required; judging whether to monitor 3 times of abnormality continuously:
(1) if yes, executing the step (8);
(2) if not, jumping to the step (9);
(8) Performing intranet detection by using a curl, and judging whether the intranet is abnormal three times continuously:
(1) if yes, executing the step (9);
(2) if not, executing the step (9);
(9) Pushing alarm information, namely pushing and clearing alarms to an alarm system message queue when the abnormal application service information is cached for each time and detected as normal next time, and zeroing the current continuous abnormal times;
(10) Ending;
in the application service detection process, the granularity of the monitoring time is 5 minutes, the current abnormal times and the historical maximum abnormal times are cached for each detection, and when the historical maximum abnormal times are not reached, the current times are only accumulated without pushing the alarm; when the current times of abnormal application services are greater than or equal to the historical maximum times, pushing alarms to an alarm system message queue, and accumulating the current and historical abnormal times at the same time.
7. An application service monitoring system based on cloud computing environment is characterized in that the system comprises,
the detection unit is used for detecting the application service in a multi-source detection mode; the application service is detected by adopting a multi-source detection mode, and the detection is specifically as follows:
s101, detecting the internal environment and judging whether the internal environment is smooth or not:
(1) if the internal detection is not successful, locating as the state reason of the application itself;
(2) if the internal detection is clear, taking network reasons into consideration, executing step S102 next;
s102, checking network reasons: starting from the nat conversion, the nat converts the external network address into the internal network address through the router or firewall;
s103, judging whether conversion exists by acquiring a nat conversion table on the router or the firewall:
(1) if so, positioning the problem as an extranet problem;
(2) if the problem does not exist, positioning the problem to the intranet problem;
the convergence deployment unit is used for deploying the convergence application service monitoring client in the OpenCenter environment;
the local deployment unit is used for deploying the local application service monitoring client on the acquisition machine of the government cloud center;
the periodic monitoring unit is used for deploying the application service monitoring clients on the convergence and the local area and running in a timed task mode and periodically monitoring the transition of the application service state;
the alarm pushing unit is used for pushing the alarm to the alarm system message queue from the application service monitoring client side for normally converting the service state into the abnormal service state;
the alarm clearing unit is used for pushing and clearing alarms to an alarm system message queue from the application service monitoring client side for converting the abnormal service state into normal application service;
the visualization unit is used for displaying abnormal alarms and carried performance data pushed by the application service monitoring client in a visualization mode of the alarm list on the foreground page, and accurately and quickly analyzing the current service state through the performance data of the application service;
the verification unit is used for carrying out abnormal data verification on the OpenCenter converged application service monitoring client and the local application service monitoring client of each government cloud center; the method comprises the following steps:
after the OpenCenter convergence application service monitoring client detects the abnormality, checking whether the corresponding local cloud center detects the same abnormal condition or not when pushing an alarm:
if yes, normally pushing an alarm;
if not, notifying corresponding operation and maintenance personnel to check and treat, and ensuring the accuracy of the abnormal information.
8. An electronic device, comprising: a memory and at least one processor;
wherein the memory stores computer-executable instructions;
the at least one processor executing computer-executable instructions stored in the memory causes the at least one processor to perform the application service monitoring method in a cloud-based computing environment as recited in any of claims 1-6.
9. A computer-readable storage medium having stored therein computer-executable instructions that, when executed by a processor, implement the method for monitoring application services in a cloud-based computing environment of any of claims 1 to 6.
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| US20240054231A1 (en)* | 2022-08-15 | 2024-02-15 | Microsoft Technology Licensing, Llc | Cloud-agnostic code analysis |
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| CN115664990A (en)* | 2022-10-09 | 2023-01-31 | 浪潮云信息技术股份公司 | Monitoring data aggregation and processing method in government affair cloud scene |
| CN116383208B (en)* | 2023-03-30 | 2025-09-26 | 浪潮云信息技术股份公司 | A method, device, equipment and storage medium for data aggregation at multiple time granularities |
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