CN112783745A - Cluster data monitoring method, device, system and storage medium - Google Patents
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Abstract
The application provides a cluster data monitoring method, a device, a system and a storage medium. The monitoring method comprises the following steps: acquiring first monitoring data corresponding to a target service cluster; for each sub-service cluster, determining the service volume of each sub-service cluster according to the cluster identifier of the sub-service cluster; and determining the health state of each sub-service cluster according to the service quantity of each sub-service cluster. According to the method and the device, through the cluster identification of the sub-business cluster, the second monitoring data of the sub-business cluster are extracted from the target service cluster, the service volume of each sub-business cluster is determined according to the second monitoring data, the health state of the sub-business cluster is further determined, the monitoring of the service volume of each sub-business cluster in the target service cluster is achieved, the health state of each sub-business cluster is judged and displayed according to the service volume of each sub-business cluster, all data of each sub-business cluster in the target service cluster are further improved, and the data monitoring effect and the practicability are further improved.
Description
Technical Field
The present application relates to the field of data monitoring technologies, and in particular, to a method, an apparatus, a system, and a storage medium for monitoring cluster data.
Background
With the development of society and the progress of times, in the current daily life, the monitoring of business is basically mature, wherein the monitoring process is divided into several processes of data acquisition, submission, storage, presentation, exception and alarm, but the current business monitoring can only monitor the service data in the service cluster, can only perform the integral data monitoring of the service cluster, and cannot monitor the data of each single sub-business cluster in the service cluster, so that the health state of the monitored data and all the data of the cluster to which the monitored data belongs cannot be judged.
Disclosure of Invention
In view of this, an object of the present application is to provide a method, an apparatus, a system, and a storage medium for monitoring cluster data, where the method extracts second monitoring data of a sub-service cluster from a target service cluster through a cluster identifier of the sub-service cluster, and determines a service volume of each sub-service cluster according to the second monitoring data, thereby determining a health state of the sub-service cluster, so as to monitor the service volume of each sub-service cluster in the target service cluster, judge the health state of each sub-service cluster according to the service volume of each sub-service cluster, and display all data of each sub-service cluster in the target service cluster, thereby further improving an effect and a practicability of data monitoring.
The application mainly comprises the following aspects:
in a first aspect, an embodiment of the present application provides a method for monitoring cluster data, where the method for monitoring cluster data includes:
acquiring first monitoring data corresponding to a target service cluster; the target service cluster comprises a plurality of different sub-service clusters; the first monitoring data carries cluster identifications belonging to different sub-service clusters;
for each sub-service cluster, extracting second monitoring data of the sub-service cluster from the first monitoring data according to the cluster identifier of the sub-service cluster;
determining the service volume of each sub-service cluster according to the second monitoring data of each sub-service cluster;
and determining the health state of each sub-service cluster according to the service quantity of each sub-service cluster.
In a possible implementation manner, before obtaining the first monitoring data corresponding to the target service cluster, the monitoring method further includes:
acquiring initial monitoring data corresponding to a target service cluster;
and extracting first monitoring data corresponding to the target service cluster from the initial monitoring data according to a preset format rule.
In a possible implementation manner, the determining the service volume of each sub service cluster according to the second monitoring data of each sub service cluster includes:
determining the service quantity of each server in each sub-service cluster according to the second monitoring data of each sub-service cluster;
and accumulating the service quantity of each server in each sub-service group according to each sub-service group to determine the service quantity of each sub-service group.
In a possible implementation manner, the determining, according to the second monitoring data of each sub-service cluster, a service amount of each server in each sub-service cluster includes:
determining service index data of each server in each sub-service cluster according to the second monitoring data of each sub-service cluster; the service index is used for identifying the service type operated by each server;
and determining the service quantity of each server in each sub-service group according to the service index data of each server.
In a possible implementation manner, for each of the sub-service clusters, the determining the health status of each of the sub-service clusters according to the service volume of each of the sub-service clusters includes:
judging whether the service volume of the sub-service cluster is within a preset service volume threshold range of the sub-service cluster according to the service volume of the sub-service cluster;
if so, determining that the sub-service cluster is in a healthy state;
if not, each sub-service cluster is in an unhealthy state.
In a second aspect, an embodiment of the present application further provides a monitoring platform, where the monitoring platform includes:
the first acquisition module is used for acquiring first monitoring data corresponding to the target service cluster; the target service cluster comprises a plurality of different sub-service clusters; the first monitoring data carries cluster identifications belonging to different sub-service clusters;
an extraction module, configured to, for each sub-service cluster, extract second monitoring data of the sub-service cluster from the first monitoring data according to a cluster identifier of the sub-service cluster;
a first determining module, configured to determine, according to the second monitoring data of each sub-service cluster, a service volume of each sub-service cluster;
and the second determining module is used for determining the service volume of each sub-service cluster and determining the health state of each sub-service cluster.
In a possible implementation, the monitoring platform further includes:
the second acquisition module is used for acquiring initial monitoring data corresponding to the target service cluster;
and the third determining module is used for extracting the first monitoring data corresponding to the target service cluster from the initial monitoring data according to a preset format rule.
In a possible implementation manner, the first determining module is specifically configured to:
determining the service quantity of each server in each sub-service cluster according to the second monitoring data of each sub-service cluster;
and accumulating the service quantity of each server in each sub-service group according to each sub-service group to determine the service quantity of each sub-service group.
In a third aspect, an embodiment of the present application further provides a monitoring system for cluster data, where in any possible implementation manner of the first aspect, the monitoring platform and the service acquisition platform are provided;
the service acquisition platform is used for acquiring initial monitoring data corresponding to a target service cluster and sending the initial monitoring data to the monitoring platform;
and the monitoring platform is used for determining first monitoring data from initial monitoring data corresponding to a target service cluster, extracting second monitoring data of the sub-service clusters from the first monitoring data according to cluster identifiers of the sub-service clusters, determining the service quantity of each sub-service cluster according to the second monitoring data of each sub-service cluster, and determining the health state of each sub-service cluster according to the service quantity of each sub-service cluster.
In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to perform the steps of the monitoring method as described above.
Compared with the group data monitoring method in the prior art, the group data monitoring method, the device, the system and the storage medium provided by the embodiment of the application extract the second monitoring data of the sub-service cluster from the target service cluster through the cluster identifier of the sub-service cluster, determine the service quantity of each sub-service cluster according to the second monitoring data, further determine the health state of the sub-service cluster, realize the monitoring of the service quantity of each sub-service cluster in the target service cluster, judge the health state of each sub-service cluster according to the service quantity of each sub-service cluster, and display all data of each sub-service cluster in the target service cluster, thereby further improving the data monitoring effect and the practicability.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 shows a flowchart of a method for monitoring cluster data according to an embodiment of the present application;
fig. 2 is a flowchart illustrating another cluster data monitoring method provided in an embodiment of the present application;
fig. 3 shows a schematic structural diagram of a monitoring platform provided in an embodiment of the present application;
FIG. 4 is a schematic structural diagram of another monitoring platform provided in the embodiment of the present application;
fig. 5 shows a schematic structural diagram of a monitoring system for cluster data provided in an embodiment of the present application.
In the figure:
10-a monitoring system; 300-a monitoring platform; 310-a first obtaining module; 320-an extraction module; 330-a first determination module; 340-a second determination module; 350-a second obtaining module; 360-a third determination module; 400-service collection platform.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. Every other embodiment that can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present application falls within the protection scope of the present application.
Firstly, research shows that the current service monitoring can only monitor service data in a service cluster, can only perform overall data monitoring of the service cluster, and cannot monitor data of each single sub-service cluster in the service cluster, so that the health state of the monitored data and all data of the cluster to which the monitored data belongs cannot be judged.
Based on this, an embodiment of the present application provides a method, where second monitoring data of a sub-service cluster is extracted from a target service cluster through a cluster identifier of the sub-service cluster, and a service volume of each sub-service cluster is determined according to the second monitoring data, so as to determine a health state of the sub-service cluster, thereby implementing monitoring of the service volume of each sub-service cluster in the target service cluster, and according to the service volume of each sub-service cluster, the health state of each sub-service cluster is determined and all data of each sub-service cluster in the target service cluster is displayed, thereby further improving the effect and the practicability of data monitoring.
Referring to fig. 1, fig. 1 is a flowchart of a cluster data monitoring method according to an embodiment of the present disclosure. As shown in fig. 1, a method for monitoring cluster data provided in the embodiment of the present application includes the following steps:
s101, acquiring first monitoring data corresponding to a target service cluster; the target service cluster comprises a plurality of different sub-service clusters; the first monitoring data carries cluster identifiers belonging to different sub-service clusters.
In this step, the target service cluster is a specific service cluster selected by a user, the target service cluster includes a plurality of different sub-service clusters, and the first monitoring data carries cluster identifiers belonging to different sub-service clusters.
Here, the service cluster refers to a plurality of servers running the same program to form a high-availability cluster, the sub-service cluster refers to a cluster consisting of a plurality of servers under the same cluster, service codes running on each server under the same cluster are the same, and the cluster identifier is a cluster service name of the sub-service cluster.
The cluster identifier may specifically include large service platforms, such as hundredths, Tencent, Jingdong, and Ali.
Optionally, before obtaining the first monitoring data corresponding to the target service cluster, the monitoring method further includes:
and acquiring initial monitoring data corresponding to the target service cluster.
Here, the initial monitoring data corresponding to the target service cluster submitted by the service agent is received through the interface, and the service agent acquires the initial monitoring data from each remote service program.
And extracting first monitoring data corresponding to the target service cluster from the initial monitoring data according to a preset format rule.
Here, the preset format rule is a JSON format rule, the integrity of the initial monitoring data is judged according to the JSON format rule, the initial monitoring data in the JSON format with the integrity is analyzed into a java format, and the first monitoring data in the initial monitoring data is determined.
S102, aiming at each sub-service cluster, extracting second monitoring data of the sub-service cluster from the first monitoring data according to the cluster identification of the sub-service cluster.
In this step, according to the cluster identifier of the sub-service cluster, second monitoring data of the sub-service cluster is extracted from the first monitoring data, specifically, second monitoring data related to the cluster identifier type of the sub-service cluster is extracted from the first monitoring data.
The cluster identifier is a cluster service name of the sub-service cluster, and the cluster identifier may specifically include each large service platform, such as Baidu, Tencent, Jingdong, and Ali.
S103, determining the service volume of each sub-service cluster according to the second monitoring data of each sub-service cluster.
In this step, according to the second monitoring data of each sub-service cluster, the service volume of each sub-service cluster is accumulated and calculated, the data is stored to the latest frame of data, and the previous data is deleted, so that redundancy and complexity are avoided.
Here, the sub-service cluster retains only the latest health status and data of the service.
S104, determining the health state of each sub-service cluster according to the service quantity of each sub-service cluster.
And judging whether the service volume of the sub-service cluster is within the preset service volume threshold range of the sub-service cluster according to the service volume of the sub-service cluster.
Here, it is preferred to set a preset service volume threshold of the sub-service cluster, determine the size of the service volume of the sub-service cluster and the size of the preset service volume threshold range of the service cluster, and determine whether the service volume of the sub-service cluster is within the preset service volume threshold range of the sub-service cluster.
Here, the preset service amount threshold of each sub-service cluster may be set to be the same preset service amount threshold range, and similarly, the preset service amount threshold range of the sub-service cluster may also be set to be different threshold ranges according to different sub-service clusters.
And then, summarizing and displaying the service quantity of the sub-service cluster according to the classification of the found cluster identification.
If so, determining that the sub-service cluster is in a healthy state.
If not, each sub-service cluster is in an unhealthy state.
Here, the service volume of the sub-service cluster exceeding the preset service volume threshold range of the sub-service cluster is subjected to alarm processing.
The alarm processing mode comprises voice reminding, acousto-optic reminding, remote control APP program reminding and the like.
Here, when the number of times of warning reaches the preset number of times of warning, the administrator is notified in the form of mail through the preset warning rule to perform warning.
Compared with the monitoring method in the prior art, the monitoring method for the cluster data extracts the second monitoring data of the sub-business cluster from the target service cluster through the cluster identifier of the sub-business cluster, determines the service quantity of each sub-business cluster according to the second monitoring data, further determines the health state of the sub-business cluster, achieves monitoring of the service quantity of each sub-business cluster in the target service cluster, judges the health state of each sub-business cluster according to the service quantity of each sub-business cluster, and displays all data of each sub-business cluster in the target service cluster, and further improves the data monitoring effect and the practicability.
Referring to fig. 2, fig. 2 is a flowchart of a monitoring method for cluster data according to another embodiment of the present application. As shown in fig. 2, a monitoring method for cluster data provided in an embodiment of the present application includes the following steps:
s201, acquiring first monitoring data corresponding to a target service cluster; the target service cluster comprises a plurality of different sub-service clusters; the first monitoring data carries cluster identifiers belonging to different sub-service clusters.
S202, aiming at each sub-service cluster, extracting second monitoring data of the sub-service cluster from the first monitoring data according to the cluster identification of the sub-service cluster.
S203, determining the service quantity of each server in each sub-service cluster according to the second monitoring data of each sub-service cluster.
In this step, service index data of each server in each sub-service cluster is determined according to the second monitoring data of each sub-service cluster; the service index is used for identifying the service type operated by each server.
Here, the service index may be specifically but not limited to a user connection number, and the service index is a service type for identifying various types of operation of each server.
Optionally, the service volume of each server in each sub-service group is determined according to the service index data of each server.
Here, the service amount of each server in each sub service group under the service index data is determined according to the service index data of each server.
S204, according to each sub-service group, accumulating the service quantity of each server in each sub-service group, and determining the service quantity of each sub-service group.
In this step, the accumulated calculation process is to accumulate the total count of the data values under the service index data in the sub-service clusters, and determine the service volume of each sub-service cluster according to the total count.
S205, determining the health state of each sub-service cluster according to the service quantity of each sub-service cluster.
The descriptions of S201 to S202 and S205 may refer to the descriptions of S101 to S102 and S104, and the same technical effect can be achieved, which is not described in detail herein.
Compared with the data monitoring method in the prior art, the method for monitoring the integrated data extracts the second monitoring data of the sub-service cluster from the target service cluster through the cluster identifier of the sub-service cluster, determines the service quantity of each sub-service cluster according to the second monitoring data, further determines the health state of the sub-service cluster, achieves monitoring of the service quantity of each sub-service cluster in the target service cluster, judges the health state of each sub-service cluster according to the service quantity of each sub-service cluster, and displays all data of each sub-service cluster in the target service cluster, and further improves the data monitoring effect and the practicability.
Referring to fig. 3 and 4, fig. 3 is a schematic structural diagram of a monitoring platform according to an embodiment of the present disclosure, and fig. 4 is a schematic structural diagram of another monitoring platform according to an embodiment of the present disclosure. As shown in fig. 3, the monitoring platform 300 includes:
a first obtaining module 310, configured to obtain first monitoring data corresponding to a target service cluster; the target service cluster comprises a plurality of different sub-service clusters; the first monitoring data carries cluster identifiers belonging to different sub-service clusters.
An extracting module 320, configured to, for each sub-service cluster, extract second monitoring data of the sub-service cluster from the first monitoring data according to the cluster identifier of the sub-service cluster.
The first determining module 330 is configured to determine the service volume of each sub-service cluster according to the second monitoring data of each sub-service cluster.
Optionally, the first determining module 330 is specifically configured to:
and determining the service quantity of each server in each sub-service cluster according to the second monitoring data of each sub-service cluster.
And accumulating the service quantity of each server in each sub-service group according to each sub-service group to determine the service quantity of each sub-service group.
Optionally, the determining the service volume of each server in each sub service cluster according to the second monitoring data of each sub service cluster includes:
determining service index data of each server in each sub-service cluster according to the second monitoring data of each sub-service cluster; the service index is used for identifying the service type operated by each server.
And determining the service quantity of each server in each sub-service group according to the service index data of each server.
The second determining module 340 is configured to determine the health status of each sub-service cluster according to the service volume of each sub-service cluster.
Optionally, the second determining module 340 is specifically configured to:
and judging whether the service volume of the sub-service cluster is within the preset service volume threshold range of the sub-service cluster according to the service volume of the sub-service cluster.
If so, determining that the sub-service cluster is in a healthy state.
If not, each sub-service cluster is in an unhealthy state.
Compared with the monitoring platform in the prior art, the monitoring platform provided by the embodiment of the application extracts the second monitoring data of the sub-business cluster from the target service cluster through the cluster identifier of the sub-business cluster, determines the service quantity of each sub-business cluster according to the second monitoring data, and further determines the health state of the sub-business cluster, so that the monitoring of the service quantity of each sub-business cluster in the target service cluster is realized, the health state of each sub-business cluster is judged and displayed according to the service quantity of each sub-business cluster, and the data monitoring effect and the practicability are further improved.
Further, as shown in fig. 4, the monitoring platform 300 includes:
and a second obtaining module 350, configured to obtain initial monitoring data corresponding to the target service cluster.
The third determining module 360 is configured to extract, according to a preset format rule, first monitoring data corresponding to the target service cluster from the initial monitoring data.
A first obtaining module 310, configured to obtain first monitoring data corresponding to a target service cluster; the target service cluster comprises a plurality of different sub-service clusters; the first monitoring data carries cluster identifiers belonging to different sub-service clusters.
An extracting module 320, configured to, for each sub-service cluster, extract second monitoring data of the sub-service cluster from the first monitoring data according to the cluster identifier of the sub-service cluster.
The first determining module 330 is configured to determine the service volume of each sub-service cluster according to the second monitoring data of each sub-service cluster.
The second determining module 340 is configured to determine the health status of each sub-service cluster according to the service volume of each sub-service cluster.
The embodiment of the application provides a monitoring platform, and compared with a monitoring platform in the prior art, the application extracts second monitoring data of a sub-business cluster from a target service cluster through a cluster identifier of the sub-business cluster, determines the service quantity of each sub-business cluster according to the second monitoring data, and further determines the health state of the sub-business cluster, so that the monitoring of the service quantity of each sub-business cluster in the target service cluster is realized, the health state of each sub-business cluster is judged and displayed according to the service quantity of each sub-business cluster, and the data monitoring effect and the practicability are further improved.
Referring to fig. 5, fig. 5 is a schematic structural diagram of a group data monitoring system according to an embodiment of the present disclosure. As shown in fig. 5, the monitoring system 10 includes the monitoring platform 300 and the service collection platform 400 as described in fig. 1 and 2.
The service acquisition platform 400 is configured to acquire initial monitoring data corresponding to a target service cluster and send the initial monitoring data to the monitoring platform.
The monitoring platform 300 is configured to determine first monitoring data from initial monitoring data corresponding to a target service cluster, extract second monitoring data of the sub-service cluster from the first monitoring data according to a cluster identifier of the sub-service cluster, determine a service volume of each sub-service cluster according to the second monitoring data of each sub-service cluster, and determine a health state of each sub-service cluster according to the service volume of each sub-service cluster.
Compared with the data monitoring system in the prior art, the group data monitoring system provided by the embodiment of the application extracts the second monitoring data of the sub-service cluster from the target service cluster through the cluster identifier of the sub-service cluster, determines the service quantity of each sub-service cluster according to the second monitoring data, further determines the health state of the sub-service cluster, realizes the monitoring of the service quantity of each sub-service cluster in the target service cluster, judges the health state of each sub-service cluster and displays all data of each sub-service cluster in the target service cluster according to the service quantity of each sub-service cluster, and further improves the data monitoring effect and the practicability.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the monitoring method in the method embodiments shown in fig. 1 and fig. 2 may be executed.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. A monitoring method of cluster data is applied to a monitoring platform, and is characterized in that the monitoring method comprises the following steps:
acquiring first monitoring data corresponding to a target service cluster; the target service cluster comprises a plurality of different sub-service clusters; the first monitoring data carries cluster identifications belonging to different sub-service clusters;
for each sub-service cluster, extracting second monitoring data of the sub-service cluster from the first monitoring data according to the cluster identifier of the sub-service cluster;
determining the service volume of each sub-service cluster according to the second monitoring data of each sub-service cluster;
and determining the health state of each sub-service cluster according to the service quantity of each sub-service cluster.
2. The monitoring method according to claim 1, wherein before obtaining the first monitoring data corresponding to the target service cluster, the monitoring method further comprises:
acquiring initial monitoring data corresponding to a target service cluster;
and extracting first monitoring data corresponding to the target service cluster from the initial monitoring data according to a preset format rule.
3. The monitoring method according to claim 1, wherein the determining the service volume of each sub-service cluster according to the second monitoring data of each sub-service cluster comprises:
determining the service quantity of each server in each sub-service cluster according to the second monitoring data of each sub-service cluster;
and accumulating the service quantity of each server in each sub-service group according to each sub-service group to determine the service quantity of each sub-service group.
4. The monitoring method according to claim 3, wherein the determining the service volume of each server in each sub service cluster according to the second monitoring data of each sub service cluster comprises:
determining service index data of each server in each sub-service cluster according to the second monitoring data of each sub-service cluster; the service index is used for identifying the service type operated by each server;
and determining the service quantity of each server in each sub-service group according to the service index data of each server.
5. The monitoring method according to claim 1, wherein for each of the sub-service clusters, the determining the health status of each of the sub-service clusters according to the service volume of each of the sub-service clusters comprises:
judging whether the service volume of the sub-service cluster is within a preset service volume threshold range of the sub-service cluster according to the service volume of the sub-service cluster;
if so, determining that the sub-service cluster is in a healthy state;
if not, each sub-service cluster is in an unhealthy state.
6. A monitoring platform, comprising:
the first acquisition module is used for acquiring first monitoring data corresponding to the target service cluster; the target service cluster comprises a plurality of different sub-service clusters; the first monitoring data carries cluster identifications belonging to different sub-service clusters;
an extraction module, configured to, for each sub-service cluster, extract second monitoring data of the sub-service cluster from the first monitoring data according to a cluster identifier of the sub-service cluster;
a first determining module, configured to determine, according to the second monitoring data of each sub-service cluster, a service volume of each sub-service cluster;
and the second determining module is used for determining the service volume of each sub-service cluster and determining the health state of each sub-service cluster.
7. The monitoring platform of claim 6, further comprising:
the second acquisition module is used for acquiring initial monitoring data corresponding to the target service cluster;
and the third determining module is used for extracting the first monitoring data corresponding to the target service cluster from the initial monitoring data according to a preset format rule.
8. The monitoring platform of claim 6, wherein the first determining module is specifically configured to:
determining the service quantity of each server in each sub-service cluster according to the second monitoring data of each sub-service cluster;
and accumulating the service quantity of each server in each sub-service group according to each sub-service group to determine the service quantity of each sub-service group.
9. A monitoring system for cluster data, comprising a monitoring platform according to any one of claims 6 to 8 and a service acquisition platform;
the service acquisition platform is used for acquiring initial monitoring data corresponding to a target service cluster and sending the initial monitoring data to the monitoring platform;
and the monitoring platform is used for determining first monitoring data from initial monitoring data corresponding to a target service cluster, extracting second monitoring data of the sub-service clusters from the first monitoring data according to cluster identifiers of the sub-service clusters, determining the service quantity of each sub-service cluster according to the second monitoring data of each sub-service cluster, and determining the health state of each sub-service cluster according to the service quantity of each sub-service cluster.
10. A computer-readable storage medium, having stored thereon a computer program which, when being executed by a processor, carries out the steps of the monitoring method according to any one of the preceding claims 1 to 5.
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Application publication date: 20210511 |