Data processing method and device based on service registration center, and program product

Abstract

The invention discloses a data processing method and device based on a service registration center and a program product. Relates to the field of financial science and technology, and the method comprises the steps: obtaining monitoring parameters, which comprise N preset thresholds and a data collection frequency; based on the data acquisition frequency, acquiring state data of a registration center cluster to obtain target state data, the target state data including instance data of a service instance and M kinds of resource occupation data; based on the target state data and N preset thresholds, analyzing the running state of the registration center cluster to obtain an analysis result; and when the analysis result indicates that the registration center cluster is abnormal, generating early warning prompt information. Through the method and the device, the problem that the early warning efficiency is low due to the fact that whether the service registration center cluster is abnormal or not is analyzed and manual early warning is carried out by adopting a mode of manually checking the operation data of the service registration center cluster in related technologies is solved.

Description

Technical Field

[0001] The present application relates to the field of financial technology, and specifically, to a data processing method, device and program product based on a service registration center. Background Art

[0002] Currently, the service discovery framework implements dynamic management and calling of services by having service providers register service information with a registration center and service consumers subscribe to and obtain service information from the registration center.

[0003] In the related art, there are mainly the following ways to detect the health status of the service registry cluster (a cluster built based on the service discovery framework): Method 1, manually check the status of the server, instance registration status, heartbeat status and other information of the service registry cluster in the monitoring page, and manually judge whether the operation status of the service registry cluster is in a healthy state. Method 2, monitor the instance status through the monitoring page, and manually judge whether the operation status of the service registry cluster is in a healthy state according to the instance status.

[0004] However, the monitoring page only provides basic information (for example, server status, instance registration status, heartbeat status, etc.). In large-scale clusters, when there are many instances, the page refreshes slowly, affecting monitoring efficiency. In addition, manual viewing and manual triggering of warnings have low warning efficiency. In addition, complex operating status judgments require certain experience and expertise, which increases labor costs.

[0005] Currently, no effective solution has been proposed to solve the problem of low early warning efficiency by manually checking the operation data of the service registration center cluster, analyzing whether the service registration center cluster is abnormal and issuing manual early warnings in related technologies. Summary of the invention

[0006] The main purpose of this application is to provide a data processing method, device and program product based on a service registration center to solve the problem of low warning efficiency in the related technology of manually checking the operating data of the service registration center cluster, analyzing whether the service registration center cluster is abnormal and issuing manual warnings.

[0007] In order to achieve the above-mentioned purpose, according to one aspect of the present application, a data processing method based on a service registration center is provided. The method includes: obtaining monitoring parameters, wherein the monitoring parameters at least include: N preset thresholds, data collection frequency, the monitoring parameters are adjusted based on a preset adjustment strategy, and N is a positive integer; based on the data collection frequency, the status data of the registration center cluster is collected to obtain target status data, wherein the registration center cluster includes: a cluster constructed by a service registration and discovery component, the target status data includes: instance data of a service instance, M types of resource occupancy data, and the M types of resource occupancy data include at least one of the following: CPU usage rate, memory occupancy ratio; based on the target status data and the N preset thresholds, the operating status of the registration center cluster is analyzed to obtain an analysis result; when the analysis result indicates that the registration center cluster is abnormal, an early warning prompt information is generated.

[0008] Furthermore, the N preset thresholds include: a preset instance threshold associated with the instance data, a preset resource threshold and a preset score threshold associated with each type of resource occupancy data. Based on the target state data and the N preset thresholds, the operating state of the registration center cluster is analyzed to obtain an analysis result, and also include: comparing each type of resource occupancy data with the preset resource threshold associated with the resource occupancy data to obtain a comparison result; scoring the target state data based on a preset scoring rule to obtain a target score value; based on the comparison result, the target score value, the preset instance threshold and the instance data, the operating state of the registration center cluster is analyzed to obtain the analysis result.

[0009] Further, the instance data includes: the number and instance status of service instances in the registration center cluster, wherein the instance status is used to indicate whether the service instance can work, and based on the comparison result, the target score value, the preset instance threshold and the instance data, the running status of the registration center cluster is analyzed to obtain the analysis result, including: when the comparison result indicates that any of the resource occupancy data exceeds the preset resource threshold associated with the resource occupancy data, determining that the analysis result indicates that there is an abnormality in the running status of the registration center cluster; when the number of service instances in the registration center cluster is lower than the preset instance threshold, determining that the analysis result indicates that there is an abnormality in the running status of the registration center cluster; when the instance status of any service instance indicates that the service instance cannot work, determining that the analysis result indicates that there is an abnormality in the running status of the registration center cluster; when the target score value is lower than the preset score threshold, determining that the analysis result indicates that there is an abnormality in the running status of the registration center cluster.

[0010] Furthermore, scoring the target status data based on a preset scoring rule to obtain a target score value also includes: determining a score value of the instance data based on the preset scoring rule to obtain a first score value; determining a score value of each type of resource occupancy data based on the preset scoring rule to obtain M second score values; and performing a weighted calculation on the first score value and the M second score values ​​based on a preset weight to obtain the target score value.

[0011] Furthermore, the monitoring parameters are adjusted in the following manner: calculating the change rate of the target state data to obtain a change rate set, wherein the change rate set includes: the change rate of the number of service instances in the registration center cluster, the change rate of M types of resource occupancy data; based on the change rate set, adjusting the monitoring parameters.

[0012] Furthermore, based on the change rate set, the monitoring parameters are adjusted, including: when the change rate of the number of service instances in the registration center cluster is greater than a preset change rate threshold, increasing the data collection frequency in the monitoring parameters according to a preset ratio; when the change rate of the number of service instances in the registration center cluster is not greater than the preset change rate threshold, reducing the data collection frequency in the monitoring parameters according to the preset ratio.

[0013] Furthermore, the N preset thresholds are obtained in the following manner: obtaining status data of the registration center cluster in an abnormal state during a historical time period to obtain first status data; obtaining status data of the registration center cluster in a normal state during a historical time period to obtain second status data; and determining the N preset thresholds based on the first status data and the second status data.

[0014] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a data processing device based on a service registration center is provided. The device includes: an acquisition unit, used to acquire monitoring parameters, wherein the monitoring parameters at least include: N preset thresholds, data collection frequency, the monitoring parameters are adjusted based on a preset adjustment strategy, and N is a positive integer; a collection unit, used to collect the status data of the registration center cluster based on the data collection frequency, and obtain target status data, wherein the registration center cluster includes: a cluster constructed by a service registration and discovery component, and the target status data includes: instance data of a service instance, M types of resource occupancy data, and the M types of resource occupancy data include at least one of the following: CPU usage rate, memory occupancy ratio; an analysis unit, used to analyze the operating status of the registration center cluster based on the target status data and the N preset thresholds, and obtain an analysis result; a generation unit, used to generate an early warning prompt message when the analysis result indicates that the registration center cluster is abnormal.

[0015] Furthermore, the N preset thresholds include: a preset instance threshold associated with the instance data, a preset resource threshold and a preset score threshold associated with each type of resource occupancy data, and the analysis unit includes: a comparison subunit, used to compare each type of resource occupancy data with the preset resource threshold associated with the resource occupancy data to obtain a comparison result; a scoring subunit, used to score the target status data based on preset scoring rules to obtain a target score value; and an analysis subunit, used to analyze the operating status of the registration center cluster based on the comparison result, the target score value, the preset instance threshold and the instance data to obtain the analysis result.

[0016] Further, the instance data includes: the number and instance status of service instances in the registration center cluster, wherein the instance status is used to indicate whether the service instance can work, and the analysis subunit includes: a first determination module, used to determine that the analysis result indicates that there is an abnormality in the running state of the registration center cluster when the comparison result indicates that any of the resource occupancy data exceeds a preset resource threshold associated with the resource occupancy data; a second determination module, used to determine that the analysis result indicates that there is an abnormality in the running state of the registration center cluster when the number of service instances in the registration center cluster is lower than the preset instance threshold; a third determination module, used to determine that the analysis result indicates that there is an abnormality in the running state of the registration center cluster when the instance status of any service instance indicates that the service instance cannot work; a fourth determination module, used to determine that the analysis result indicates that there is an abnormality in the running state of the registration center cluster when the target score value is lower than the preset score threshold.

[0017] Furthermore, the scoring subunit includes: a fifth determination module, used to determine the score value of the instance data based on the preset scoring rule to obtain a first score value; a processing module, used to determine the score value of each type of resource occupancy data based on the preset scoring rule to obtain M second score values; a calculation module, used to perform weighted calculation on the first score value and the M second score values ​​based on preset weights to obtain the target score value.

[0018] Furthermore, the monitoring parameters are adjusted through the following sub-units: a calculation sub-unit, used to calculate the change rate of the target state data to obtain a change rate set, wherein the change rate set includes: the change rate of the number of service instances in the registration center cluster, the change rate of M types of resource occupancy data; an adjustment sub-unit, used to adjust the monitoring parameters based on the change rate set.

[0019] Furthermore, the adjustment sub-unit includes: an increase module, which is used to increase the data collection frequency in the monitoring parameter according to a preset ratio when the change rate of the instance number of service instances in the registration center cluster is greater than a preset change rate threshold; and a decrease module, which is used to reduce the data collection frequency in the monitoring parameter according to the preset ratio when the change rate of the instance number of service instances in the registration center cluster is not greater than the preset change rate threshold.

[0020] Furthermore, the N preset thresholds are obtained through the following sub-units: a first acquisition sub-unit, used to obtain status data of the registration center cluster in an abnormal state during a historical time period, and obtain first status data; a second acquisition sub-unit, used to obtain status data of the registration center cluster in a normal state during a historical time period, and obtain second status data; a determination sub-unit, used to determine the N preset thresholds based on the first status data and the second status data.

[0021] According to another aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the data processing method based on the service registration center.

[0022] According to another aspect of the present application, an electronic device is provided, comprising: a memory storing an executable program; and a processor for running the program, wherein the data processing method based on the service registration center is executed when the program is running.

[0023] According to another aspect of the present application, a computer program product is provided, comprising computer instructions, which implement the steps of the data processing method based on the service registration center when executed by a processor.

[0024] In an embodiment of the present application, monitoring parameters are obtained, wherein the monitoring parameters include at least: N preset thresholds, a data collection frequency, and the monitoring parameters are adjusted based on a preset adjustment strategy, where N is a positive integer; based on the data collection frequency, status data of a registration center cluster is collected to obtain target status data, wherein the registration center cluster includes: a cluster constructed by a service registration and discovery component, the target status data includes: instance data of a service instance, M types of resource occupancy data, the M types of resource occupancy data include at least one of the following: a utilization rate of a central processing unit, a memory occupancy ratio; based on the target status data and N preset thresholds, the operating status of the registration center cluster is analyzed to obtain an analysis result; when the analysis result indicates that the registration center cluster is abnormal, an early warning prompt message is generated, thereby solving the technical problem of low early warning efficiency in the related art of manually checking the operating data of the service registration center cluster, analyzing whether the service registration center cluster is abnormal and performing manual early warning.

[0025] In the present invention, by automatically collecting instance data and resource occupancy data of the registration center cluster according to monitoring parameters, and analyzing whether there are any abnormalities in the operating status of the registration center cluster, and generating early warning prompt information when there are any abnormalities, the purpose of automatic monitoring and early warning of the operating status of the registration center cluster is achieved, thereby achieving the technical effect of improving the early warning efficiency of the abnormal status of the registration center cluster. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings constituting a part of the present application are used to provide a further understanding of the present application. The illustrative embodiments and descriptions of the present application are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0027] Figure 1 A hardware structure block diagram of a computer terminal for implementing a data processing method based on a service registration center is shown;

[0028] Figure 2 is a flow chart of a data processing method based on a service registration center provided according to an embodiment of the present application;

[0029] Figure 3 is a schematic diagram of a data processing device based on a service registration center provided according to an embodiment of the present application;

[0030] Figure 4 It is a structural block diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0032] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] It should be noted that the data processing method and device based on the service registration center in the present application can be used in the financial technology field to monitor the operating status of the service registration center, and can also be used in any field other than the financial technology field to monitor the operating status of the service registration center. The present application does not limit the application field of the data processing method and device based on the service registration center.

[0034] It should be noted that the collected information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this application are information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data are in compliance with relevant laws, regulations and standards, necessary confidentiality measures are taken, and public order and good customs are not violated, and corresponding operation entrances are provided for users to choose to authorize or refuse. For example, an interface is set up between this system and relevant users or institutions to provide users with corresponding operation entrances for users to choose to agree or refuse the results of automated decision-making; if the user chooses to refuse, the expert decision-making process will be entered.

[0035] Example 1

[0036] According to an embodiment of the present application, a method embodiment of a data processing method based on a service registration center is also provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0037] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 The hardware structure block diagram of a computer terminal (or mobile device) for implementing a data processing method based on a service registration center is shown. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more (102a, 102b, ..., 102n are used to illustrate) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0038] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0039] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the data processing method based on the service registration center in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, realizing the above-mentioned data processing method based on the service registration center. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0040] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0041] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0042] Under the above operating environment, this application provides Figure 2 The data processing method based on the service registration center is shown. Figure 2 It is a flowchart of the data processing method based on the service registration center according to Example 1 of the present application.

[0043] Step S201, obtaining monitoring parameters, wherein the monitoring parameters at least include: N preset thresholds, data collection frequency, the monitoring parameters are adjusted based on a preset adjustment strategy, and N is a positive integer.

[0044] The above-mentioned monitoring parameters may include: N preset thresholds and data collection frequency. The above-mentioned monitoring parameters can be adjusted based on preset adjustment strategies. For example, the data collection frequency can be adjusted according to the change rate of the status data of the collected service registration center cluster (referred to as the registration center cluster), and the N preset thresholds can be adjusted according to different time periods, etc., to improve the accuracy of the monitoring results of the operating status of the service registration center cluster.

[0045] In an optional example, a URL list of a registration center server (used to register information of all servers in the cluster center) may be set, and monitoring parameters may also be configured, such as monitoring frequency (5 seconds), thresholds, and the like.

[0046] Step S202, based on the data collection frequency, collect the status data of the registration center cluster to obtain the target status data, wherein the registration center cluster includes: a cluster constructed by the service registration and discovery components, the target status data includes: instance data of the service instance, M types of resource occupancy data, the M types of resource occupancy data include at least one of the following: the utilization rate of the central processing unit, the memory occupancy ratio.

[0047] The above-mentioned registration center cluster may include: a cluster built by service registration and discovery components, for example, a cluster built based on a service discovery framework. The above-mentioned target status data may include but is not limited to: instance data of service instances, M types of resource occupancy data, network latency, API (application programming interface) call success rate of the registration center cluster within a certain time window, etc. The instance data of service instances may include but is not limited to: the number of service instances, the status of service instances. The status of service instances may include but is not limited to: UP (healthy), DOWN (unhealthy), STARTING (starting), NO_STATUS (no status), etc. The M types of resource occupancy data may include but are not limited to: central processing unit (CPU) usage, memory occupancy (corresponding to memory occupancy ratio), disk space and other resource usage.

[0048] In this embodiment, all applications currently registered on the server in the registration center cluster and their instance information (corresponding to instance data) can be obtained through an HTTP GET request (a request used to obtain resources or data from a server). The newly obtained instance information can also be compared with the instance information obtained last time to detect whether there are new, modified or deleted instances.

[0049] Step S203: Analyze the operation status of the registration center cluster based on the target status data and N preset thresholds to obtain an analysis result.

[0050] In this embodiment, each data in the target status data can be compared with the corresponding preset threshold value, and the target status data can also be scored according to the preset scoring rules to obtain a comprehensive score value of the target status data and analyze whether the operating status of the registration center cluster is abnormal (or whether it is in a healthy state) based on the comparison result and the score value to obtain the analysis result.

[0051] In an optional example, the network delay mentioned above can be detected by periodically sending network detection packets and detecting whether there is a delay in the response time.

[0052] Step S204: when the analysis result indicates that there is an abnormality in the registration center cluster, generate warning prompt information.

[0053] In this embodiment, when the analysis result indicates that the registration center cluster is abnormal, an early warning prompt information may be generated to prompt that the operation status of the registration center cluster is abnormal.

[0054] Through the above steps, in this embodiment, the instance data and resource usage data of the registration center cluster are automatically collected according to the monitoring parameters, and the operation status of the registration center cluster is analyzed to see if there is an abnormality. In the case of an abnormality, an early warning prompt information is generated, so as to achieve the purpose of automatic monitoring and early warning of the operation status of the registration center cluster, thereby achieving the technical effect of improving the early warning efficiency of the abnormal state of the registration center cluster. This solves the technical problem of low early warning efficiency in the related art of manually checking the operation data of the service registration center cluster, analyzing whether the service registration center cluster is abnormal and issuing a manual early warning.

[0055] Optionally, in the data processing method based on the service registration center provided in the embodiment of the present application, the N preset thresholds include: a preset instance threshold associated with the instance data, a preset resource threshold and a preset score threshold associated with each resource occupancy data, and based on the target state data and the N preset thresholds, analyzing the running state of the registration center cluster to obtain an analysis result, further comprising: comparing each resource occupancy data with the preset resource threshold associated with the resource occupancy data to obtain a comparison result; scoring the target state data based on a preset scoring rule to obtain a target score value; analyzing the running state of the registration center cluster based on the comparison result, the target score value, the preset instance threshold and the instance data to obtain an analysis result.

[0056] In this embodiment, each type of resource occupancy data can be compared with the preset resource threshold corresponding to the resource occupancy data to obtain the above-mentioned comparison result. The resource occupancy data and instance data in the target status data can also be scored according to the preset scoring rules, and the score value of the resource occupancy data and the score value of the instance data can be weighted to obtain the target score value. Then, based on the comparison result, the target score value, the preset instance threshold and the instance data, it is possible to analyze whether the operating status of the registration center cluster is in an abnormal state to obtain the analysis result.

[0057] By analyzing the target status data to analyze whether the operating status of the registration center cluster is abnormal, the purpose of automatically analyzing the operating status of the registration center cluster is achieved, and the technical effect of improving the analysis efficiency of the operating status of the registration center cluster is realized.

[0058] Optionally, in the data processing method based on the service registration center provided in the embodiment of the present application, the instance data includes: the number of service instances in the registration center cluster, and the instance status, wherein the instance status is used to indicate whether the service instance can work, and based on the comparison result, the target score value, the preset instance threshold and the instance data, the running status of the registration center cluster is analyzed to obtain the analysis result, including: when the comparison result indicates that any resource occupancy data exceeds the preset resource threshold associated with the resource occupancy data, determining that the analyzed result indicates that there is an abnormality in the running status of the registration center cluster; when the number of service instances in the registration center cluster is lower than the preset instance threshold, determining that the analysis result indicates that there is an abnormality in the running status of the registration center cluster; when the instance status of any service instance indicates that the service instance cannot work, determining that the analysis result indicates that there is an abnormality in the running status of the registration center cluster; when the target score value is lower than the preset score threshold, determining that the analysis result indicates that there is an abnormality in the running status of the registration center cluster.

[0059] The above instance status may include but is not limited to: UP (healthy), DOWN (unhealthy), STARTING (starting), NO_STATUS (no status), etc. When the instance status indicates that the service instance is DOWN (unhealthy), it may mean that the service instance cannot work.

[0060] In this embodiment, when the comparison result indicates that any resource occupancy data exceeds the preset resource threshold associated with the resource occupancy data, it can be determined that the analysis result indicates that there is an abnormality in the operating status of the registration center cluster; when the number of service instances in the registration center cluster is lower than the preset instance threshold, it can be determined that the analysis result indicates that there is an abnormality in the operating status of the registration center cluster; when the instance status of any service instance indicates that the service instance cannot work, for example, when the instance status of the service instance is DOWN (unhealthy), it can be determined that the analysis result indicates that there is an abnormality in the operating status of the registration center cluster; when the target score value is lower than the preset score threshold, it can also be determined that the analysis result indicates that there is an abnormality in the operating status of the registration center cluster.

[0061] In this embodiment, the target score values ​​of resource occupancy data, instance data and target status data are used to comprehensively determine whether the registration center cluster has an abnormality, thereby achieving the technical effect of improving the accuracy of the abnormality detection results of the registration center cluster.

[0062] In an optional example, when the network delay exceeds a preset time threshold, it can also be determined that there is an abnormality in the operation status of the registration center cluster.

[0063] Optionally, when the API (Application Programming Interface) call success rate of the registry center cluster is lower than a preset success rate threshold, it can also be determined that there is an abnormality in the operation state of the registry center cluster.

[0064] Optionally, in the data processing method based on the service registration center provided in the embodiment of the present application, the target status data is scored based on a preset scoring rule to obtain a target score value, and also includes: determining the score value of the instance data based on the preset scoring rule to obtain a first score value; determining the score value of each resource occupancy data based on the preset scoring rule to obtain M second score values; based on the preset weight, performing a weighted calculation on the first score value and the M second score values ​​to obtain the target score value.

[0065] In the above-mentioned preset scoring rules: each type of resource occupancy data corresponds to different score values ​​within different data ranges, and instance data may correspond to different score values ​​within different instance quantity ranges. In this embodiment, the score value of each type of resource occupancy data can be determined according to the data range corresponding to each type of resource occupancy data in the target state data in the preset scoring rules, and M second score values ​​are obtained. The score value of the instance data is determined according to the data range of the number of instances in the target state data in the preset scoring rules, and a first score value is obtained.

[0066] The above-mentioned preset weights may include: the weight of each resource occupancy data and the weight of the instance data. The first score value and the M second score values ​​can be weighted averaged according to the preset weights to obtain the target score value, thereby achieving the purpose of comprehensively evaluating the target status data of the registration center cluster.

[0067] Optionally, in the data processing method based on the service registration center provided in an embodiment of the present application, the monitoring parameters are adjusted in the following manner: calculate the change rate of the target state data to obtain a change rate set, wherein the change rate set includes: the change rate of the number of service instances in the registration center cluster, the change rate of M types of resource occupancy data; based on the change rate set, adjust the monitoring parameters.

[0068] In this embodiment, when the monitoring parameters are adjusted, the change rate of the target state data can be calculated. For example, for the change rate of the number of instances, the variable rate of the number of instances can be calculated based on the number of instances collected the most recently and the number of instances collected the most recently. Then, the data collection frequency can be adjusted according to the change rate of the target state data to improve the technical effect of the accuracy of the operation status detection results of the registration center cluster.

[0069] Optionally, in the data processing method based on the service registration center provided in the embodiment of the present application, the monitoring parameters are adjusted based on the change rate set, including: when the change rate of the number of service instances in the registration center cluster is greater than a preset change rate threshold, increasing the data collection frequency in the monitoring parameters according to a preset ratio; when the change rate of the number of service instances in the registration center cluster is not greater than a preset change rate threshold, reducing the data collection frequency in the monitoring parameters according to a preset ratio.

[0070] In order to improve the accuracy of the operating status monitoring results of the registration center cluster, when the change rate of the number of service instances in the registration center cluster is greater than the preset change rate threshold, the data collection frequency in the monitoring parameters can be increased according to the preset proportion; when the change rate of the number of service instances in the registration center cluster is not greater than the preset change rate threshold, the data collection frequency in the monitoring parameters can be reduced according to the preset proportion, thereby achieving the purpose of dynamically adjusting the data collection frequency.

[0071] Optionally, in the data processing method based on the service registration center provided in the embodiment of the present application, N preset thresholds are obtained in the following manner: obtaining status data of the registration center cluster in an abnormal state during a historical time period to obtain first status data; obtaining status data of the registration center cluster in a normal state during a historical time period to obtain second status data; based on the first status data and the second status data, determining N preset thresholds.

[0072] The above-mentioned historical time period may include: a period of time before the current moment. In this embodiment, the state data of the registration center cluster in an abnormal state and the state data of the registration center processing in a normal state can be collected, and the preset resource threshold associated with each resource occupancy data is set according to the minimum value of each resource occupancy data in the abnormal state and the maximum value of each resource occupancy data in the normal state, wherein the preset resource threshold associated with each resource occupancy data should be less than or equal to the minimum value and not exceed the maximum value. Similarly, the preset instance threshold associated with the instance data can be set according to the instance data in the abnormal state and the instance data in the normal state, thereby achieving the purpose of improving the accuracy of the setting of N preset thresholds and the technical effect of improving the accuracy of the results of the operation status analysis of the registration center.

[0073] It should be noted that an optional monitoring system may be used to execute the data processing method based on the service registration center of this embodiment, and the monitoring system may include:

[0074] Monitoring module: responsible for periodically calling the API of the registry center cluster to obtain instance information and compare the differences. By continuously comparing instance information, real-time monitoring of the operating status of the registry center cluster can be achieved.

[0075] Storage module: stores instance information and change records obtained each time. This includes saving data obtained from the registry cluster each time and recording detected status changes to provide data support for subsequent analysis and backtracking.

[0076] Alarm module: Alarms are issued for instance changes based on preset rules. This includes setting alarm conditions (such as the number of instances decreasing below a certain threshold) and triggering early warning prompts (such as sending emails or SMS notifications) based on the conditions.

[0077] The alarm logic of the monitoring system may include but is not limited to: (1) Instance quantity reduction alarm: Set a threshold for the number of instances. When it is detected that the number of instances registered in Eureka decreases below the threshold, an alarm is triggered. (2) Instance status change alarm: Monitor the status change of the instance. For example, when the instance changes from UP to DOWN, an alarm is triggered immediately. API call failure alarm: If multiple attempts to call the API fail in succession, it is judged that the server of the registration center cluster is abnormal and an alarm is triggered.

[0078] It should be noted that the instance quantity threshold (corresponding to the preset instance threshold) in the preset threshold of this embodiment can be set according to actual business needs. For example, if the number of instances of a key application is reduced to less than 3, an alarm is triggered.

[0079] API call failure threshold: You can set a threshold for the number of consecutive failures. For example, if there are five consecutive call failures, it is considered that the registration center cluster server is abnormal.

[0080] The data processing method based on the service registration center provided in the embodiment of the present application automatically collects the instance data and resource occupancy data of the registration center cluster according to the monitoring parameters, and analyzes whether the operation status of the registration center cluster is abnormal. In the case of abnormality, an early warning prompt information is generated, thereby achieving the purpose of automatic monitoring and early warning of the operation status of the registration center cluster, thereby achieving the technical effect of improving the early warning efficiency of the abnormal state of the registration center cluster. In addition, the technical problem of low early warning efficiency in the related technology of manually checking the operation data of the service registration center cluster, analyzing whether the service registration center cluster is abnormal and manually warning is solved.

[0081] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0082] Example 2

[0083] The embodiment of the present application also provides a data processing device based on a service registration center. It should be noted that the data processing device based on a service registration center in the embodiment of the present application can be used to execute the data processing method based on a service registration center provided in the embodiment of the present application. The data processing device based on a service registration center provided in the embodiment of the present application is introduced below.

[0084] According to an embodiment of the present application, a device for implementing the above-mentioned data processing method based on a service registration center is also provided. Figure 3 As shown, the device includes: an acquisition unit 31, a collection unit 32, an analysis unit 33 and a generation unit 34.

[0085] The acquisition unit 31 is used to acquire monitoring parameters, wherein the monitoring parameters at least include: N preset thresholds, data collection frequency, and the monitoring parameters are adjusted based on a preset adjustment strategy, where N is a positive integer;

[0086] The collection unit 32 is used to collect the status data of the registration center cluster based on the data collection frequency to obtain the target status data, wherein the registration center cluster includes: a cluster constructed by the service registration and discovery component, and the target status data includes: instance data of the service instance, M types of resource occupancy data, and the M types of resource occupancy data include at least one of the following: the utilization rate of the central processing unit and the memory occupancy ratio;

[0087] The analysis unit 33 is used to analyze the operation status of the registration center cluster based on the target status data and N preset thresholds to obtain an analysis result;

[0088] The generating unit 34 is used to generate warning information when the analysis result indicates that there is an abnormality in the registration center cluster.

[0089] In the data processing device based on the service registration center provided in the embodiment of the present application, the monitoring parameters can be obtained by the acquisition unit, wherein the monitoring parameters at least include: N preset thresholds, data collection frequency, the monitoring parameters are adjusted based on the preset adjustment strategy, N is a positive integer, and the state data of the registration center cluster is collected by the acquisition unit 32 based on the data collection frequency to obtain the target state data, wherein the registration center cluster includes: a cluster constructed by the service registration and discovery component, the target state data includes: instance data of the service instance, M types of resource occupancy data, and the M types of resource occupancy data include at least one of the following: the utilization rate of the central processing unit, the memory occupancy ratio, and the analysis unit 33 analyzes the operation state of the registration center cluster based on the target state data and N preset thresholds to obtain the analysis result, and the generation unit 34 generates an early warning prompt information when the analysis result indicates that the registration center cluster is abnormal. Thus, the technical problem of low early warning efficiency in the related technology of manually checking the operation data of the service registration center cluster, analyzing whether the service registration center cluster is abnormal and performing manual early warning is solved.

[0090] In this embodiment, the instance data and resource usage data of the registration center cluster are automatically collected according to the monitoring parameters, and the operating status of the registration center cluster is analyzed to see whether there are any abnormalities. In the event of an abnormality, early warning information is generated, thereby achieving the purpose of automatic monitoring and early warning of the operating status of the registration center cluster, thereby achieving the technical effect of improving the early warning efficiency of the abnormal status of the registration center cluster.

[0091] Optionally, in the data processing device based on the service registration center provided in the embodiment of the present application, the N preset thresholds include: a preset instance threshold associated with the instance data, a preset resource threshold and a preset score threshold associated with each resource occupancy data, and the analysis unit includes: a comparison subunit, used to compare each resource occupancy data with the preset resource threshold associated with the resource occupancy data to obtain a comparison result; a scoring subunit, used to score the target status data based on preset scoring rules to obtain a target score value; and an analysis subunit, used to analyze the operating status of the registration center cluster based on the comparison result, the target score value, the preset instance threshold and the instance data to obtain an analysis result.

[0092] Optionally, in the data processing device based on the service registration center provided in the embodiment of the present application, the instance data includes: the number of service instances in the registration center cluster, and the instance status, wherein the instance status is used to indicate whether the service instance can work, and the analysis subunit includes: a first determination module, used to determine that the analysis result indicates that there is an abnormality in the running state of the registration center cluster when the comparison result indicates that any resource occupancy data exceeds a preset resource threshold associated with the resource occupancy data; a second determination module, used to determine that the analysis result indicates that there is an abnormality in the running state of the registration center cluster when the number of service instances in the registration center cluster is lower than the preset instance threshold; a third determination module, used to determine that the analysis result indicates that there is an abnormality in the running state of the registration center cluster when the instance status of any service instance indicates that the service instance cannot work; a fourth determination module, used to determine that the analysis result indicates that there is an abnormality in the running state of the registration center cluster when the target score value is lower than the preset score threshold.

[0093] Optionally, in the data processing device based on the service registration center provided in the embodiment of the present application, the scoring subunit includes: a fifth determination module, used to determine the score value of the instance data based on a preset scoring rule to obtain a first score value; a processing module, used to determine the score value of each resource occupancy data based on a preset scoring rule to obtain M second score values; a calculation module, used to perform weighted calculation on the first score value and the M second score values ​​based on preset weights to obtain a target score value.

[0094] Optionally, in the data processing device based on the service registration center provided in the embodiment of the present application, the monitoring parameters are adjusted through the following sub-units: a calculation sub-unit, used to calculate the change rate of the target state data to obtain a change rate set, wherein the change rate set includes: the change rate of the number of service instances in the registration center cluster, the change rate of M types of resource occupancy data; an adjustment sub-unit, used to adjust the monitoring parameters based on the change rate set.

[0095] Optionally, in the data processing device based on the service registration center provided in the embodiment of the present application, the adjustment sub-unit includes: an increase module, which is used to increase the data collection frequency in the monitoring parameters according to a preset proportion when the change rate of the instance number of service instances in the registration center cluster is greater than a preset change rate threshold; a decrease module, which is used to reduce the data collection frequency in the monitoring parameters according to a preset proportion when the change rate of the instance number of service instances in the registration center cluster is not greater than a preset change rate threshold.

[0096] Optionally, in the data processing device based on the service registration center provided in the embodiment of the present application, N preset thresholds are obtained through the following sub-units: a first acquisition sub-unit, used to obtain status data of the registration center cluster in an abnormal state during a historical time period, and obtain first status data; a second acquisition sub-unit, used to obtain status data of the registration center cluster in a normal state during a historical time period, and obtain second status data; a determination sub-unit, used to determine N preset thresholds based on the first status data and the second status data.

[0097] It should be noted that the acquisition unit 31, the acquisition unit 32, the analysis unit 33 and the generation unit 34 correspond to steps S201 to S204 in Example 1, and the two modules and the corresponding steps implement the same examples and application scenarios, but are not limited to the contents disclosed in the above-mentioned Example 1. It should be noted that the above-mentioned modules or units may be hardware components or software components stored in a memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n), and the above-mentioned modules may also be part of the device and may be run in the computer terminal 10 provided in Example 1.

[0098] Example 3

[0099] An embodiment of the present application may provide an electronic device, Figure 4 is a structural block diagram of an electronic device according to an embodiment of the present application. Figure 4 As shown, the electronic device may include: one or more ( Figure 4 (only one is shown) processor 402, memory 404, storage controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0100] Among them, the memory can be used to store software programs and modules, such as program instructions / modules corresponding to the methods and devices in the embodiments of the present application, and the processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the above-mentioned method. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0101] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: obtain monitoring parameters, wherein the monitoring parameters include at least: N preset thresholds, data collection frequency, the monitoring parameters are adjusted based on a preset adjustment strategy, and N is a positive integer; based on the data collection frequency, collect the status data of the registration center cluster to obtain target status data, wherein the registration center cluster includes: a cluster constructed by a service registration and discovery component, the target status data includes: instance data of the service instance, M types of resource occupancy data, the M types of resource occupancy data include at least one of the following: the utilization rate of the central processing unit, the memory occupancy ratio; based on the target status data and N preset thresholds, analyze the operating status of the registration center cluster to obtain an analysis result; when the analysis result indicates that there is an abnormality in the registration center cluster, generate an early warning prompt information.

[0102] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: N preset thresholds include: a preset instance threshold associated with the instance data, a preset resource threshold and a preset score threshold associated with each resource occupancy data, and based on the target state data and the N preset thresholds, analyzing the operating state of the registration center cluster to obtain an analysis result, and also including: comparing each resource occupancy data with the preset resource threshold associated with the resource occupancy data to obtain a comparison result; scoring the target state data based on a preset scoring rule to obtain a target score value; analyzing the operating state of the registration center cluster based on the comparison result, the target score value, the preset instance threshold and the instance data to obtain an analysis result.

[0103] The processor can also call the information and application stored in the memory through the transmission device to perform the following steps: the instance data includes: the number of service instances in the registration center cluster, the instance status, wherein the instance status is used to indicate whether the service instance can work, and based on the comparison result, the target score value, the preset instance threshold and the instance data, the running status of the registration center cluster is analyzed to obtain the analysis result, including: when the comparison result indicates that any resource occupancy data exceeds the preset resource threshold associated with the resource occupancy data, it is determined that the analyzed result indicates that there is an abnormality in the running status of the registration center cluster; when the number of service instances in the registration center cluster is lower than the preset instance threshold, it is determined that the analysis result indicates that there is an abnormality in the running status of the registration center cluster; when the instance status of any service instance indicates that the service instance cannot work, it is determined that the analysis result indicates that there is an abnormality in the running status of the registration center cluster; when the target score value is lower than the preset score threshold, it is determined that the analysis result indicates that there is an abnormality in the running status of the registration center cluster.

[0104] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: scoring the target state data based on the preset scoring rules to obtain the target score value, and also includes: determining the score value of the instance data based on the preset scoring rules to obtain the first score value; determining the score value of each resource occupancy data based on the preset scoring rules to obtain M second score values; based on the preset weights, weighted calculation of the first score value and the M second score values ​​to obtain the target score value.

[0105] The processor can also call the information and applications stored in the memory through the transmission device to perform the following steps: the monitoring parameters are adjusted in the following way: the change rate of the target state data is calculated to obtain a change rate set, wherein the change rate set includes: the change rate of the number of service instances in the registration center cluster, the change rate of M types of resource occupancy data; based on the change rate set, the monitoring parameters are adjusted.

[0106] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: adjust the monitoring parameters based on the change rate set, including: when the change rate of the number of service instances in the registration center cluster is greater than the preset change rate threshold, increase the data collection frequency in the monitoring parameters according to a preset ratio; when the change rate of the number of service instances in the registration center cluster is not greater than the preset change rate threshold, reduce the data collection frequency in the monitoring parameters according to a preset ratio.

[0107] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: N preset thresholds are obtained in the following manner: obtaining status data of the registration center cluster in an abnormal state during a historical time period to obtain first status data; obtaining status data of the registration center cluster in a normal state during a historical time period to obtain second status data; based on the first status data and the second status data, determining N preset thresholds.

[0108] By adopting the embodiment of the present application, a data processing solution based on the service registration center is provided. By automatically collecting the instance data and resource occupancy data of the registration center cluster according to the monitoring parameters, and analyzing whether there is an abnormality in the operation status of the registration center cluster, and generating early warning information in the case of an abnormality, the purpose of automatic monitoring and early warning of the operation status of the registration center cluster is achieved, thereby achieving the technical effect of improving the early warning efficiency of the abnormal state of the registration center cluster. This solves the technical problem of low early warning efficiency in the related technology of manually checking the operation data of the service registration center cluster, analyzing whether the service registration center cluster is abnormal and issuing manual early warnings.

[0109] It can be understood by those skilled in the art that Figure 4The structure shown is for illustration only, and the electronic device may also be a smart phone, a tablet computer, a PDA, a mobile Internet device (MID), a PAD or other terminal device. Figure 4 The structure of the electronic device is not limited. Figure 4 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Figure 4 Different configurations are shown.

[0110] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0111] Example 4

[0112] The embodiment of the present application further provides a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the data processing method based on the service registration center provided in the first embodiment.

[0113] Optionally, in this embodiment, the above storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0114] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing the program of the data processing method steps based on the service registration center.

[0115] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0116] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0117] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0118] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0119] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0120] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, in essence, or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0121] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A data processing method based on a service registration center, characterized in that: include: Acquire monitoring parameters, wherein the monitoring parameters at least include: N preset thresholds, data collection frequency, the monitoring parameters are adjusted based on a preset adjustment strategy, and N is a positive integer; Based on the data collection frequency, the status data of the registration center cluster is collected to obtain the target status data, wherein the registration center cluster includes: a cluster constructed by the service registration and discovery component, and the target status data includes: instance data of the service instance, M types of resource occupancy data, and the M types of resource occupancy data include at least one of the following: a usage rate of a central processing unit, and a memory occupancy ratio; Based on the target status data and the N preset thresholds, analyzing the operating status of the registration center cluster to obtain an analysis result; When the analysis result indicates that an abnormality exists in the registration center cluster, an early warning prompt message is generated.

2. The data processing method according to claim 1, characterized in that: The N preset thresholds include: a preset instance threshold associated with the instance data, a preset resource threshold associated with each resource occupancy data, and a preset score threshold. Based on the target state data and the N preset thresholds, the operation state of the registration center cluster is analyzed to obtain an analysis result, including: Compare each of the resource occupancy data with a preset resource threshold associated with the resource occupancy data to obtain a comparison result; Scoring the target state data based on a preset scoring rule to obtain a target score value; Based on the comparison result, the target score value, the preset instance threshold and the instance data, the operation status of the registration center cluster is analyzed to obtain the analysis result.

3. The data processing method according to claim 2, characterized in that: The instance data includes: the number of service instances in the registry center cluster and instance status, wherein the instance status is used to indicate whether the service instance can work. Based on the comparison result, the target score value, the preset instance threshold value and the instance data, the operation status of the registry center cluster is analyzed to obtain the analysis result, including: In a case where the comparison result indicates that any of the resource occupancy data exceeds a preset resource threshold associated with the resource occupancy data, determining that the analysis result indicates that an abnormality exists in the operation state of the registration center cluster; When the number of service instances in the registry center cluster is lower than the preset instance threshold, determining that the analysis result indicates that an abnormality exists in the operation state of the registry center cluster; In a case where the instance status of any service instance indicates that the service instance cannot work, determining that the analysis result indicates that there is an abnormality in the operation status of the registration center cluster; When the target score value is lower than the preset score threshold, it is determined that the analysis result indicates that an abnormality exists in the operation status of the registration center cluster.

4. The data processing method according to claim 2, characterized in that: Scoring the target state data based on a preset scoring rule to obtain a target score value includes: Determine a score value of the instance data based on the preset scoring rule to obtain a first score value; Determine a score value for each type of resource occupancy data based on the preset scoring rule to obtain M second score values; Based on a preset weight, weighted calculation is performed on the first score value and the M second score values ​​to obtain the target score value.

5. The data processing method according to claim 1, characterized in that: The monitoring parameters are adjusted in the following ways: Calculating the change rate of the target state data to obtain a change rate set, wherein the change rate set includes: a change rate of the number of service instances in the registration center cluster and a change rate of M types of resource occupancy data; Based on the set of rates of change, the monitoring parameters are adjusted.

6. The data processing method according to claim 5, characterized in that: Adjusting the monitoring parameter based on the set of change rates includes: When the rate of change of the number of instances of the service instances in the registration center cluster is greater than a preset rate of change threshold, increasing the data collection frequency in the monitoring parameter according to a preset ratio; When the change rate of the number of service instances in the registration center cluster is not greater than the preset change rate threshold, the data collection frequency in the monitoring parameter is reduced according to the preset ratio.

7. The data processing method according to claim 1, characterized in that: The N preset thresholds are obtained in the following manner: Acquire state data of the registration center cluster being in an abnormal state during a historical time period to obtain first state data; Acquire status data of the registration center cluster being in a normal state during a historical time period to obtain second status data; Based on the first state data and the second state data, N preset thresholds are determined.

8. A data processing device based on a service registration center, characterized in that: include: An acquisition unit, configured to acquire monitoring parameters, wherein the monitoring parameters at least include: N preset thresholds, a data acquisition frequency, the monitoring parameters are adjusted based on a preset adjustment strategy, and N is a positive integer; A collection unit is used to collect status data of a registration center cluster based on the data collection frequency to obtain target status data, wherein the registration center cluster includes: a cluster constructed by a service registration and discovery component, and the target status data includes: instance data of a service instance, M types of resource occupancy data, and the M types of resource occupancy data include at least one of the following: a utilization rate of a central processing unit and a memory occupancy ratio; An analysis unit, configured to analyze the operation status of the registration center cluster based on the target status data and the N preset thresholds to obtain an analysis result; A generating unit is used to generate early warning information when the analysis result indicates that the registration center cluster is abnormal.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the data processing method based on the service registration center according to any one of claims 1 to 7.

10. An electronic device, characterized in that: include: A memory storing an executable program; A processor is used to run the program, wherein the program, when running, executes the data processing method based on the service registration center as described in any one of claims 1 to 7.

11. A computer program product comprising computer instructions, characterized in that: When the computer instructions are executed by a processor, the steps of the data processing method based on the service registration center described in any one of claims 1 to 7 are implemented.

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