ICE monitoring method and system

Abstract

The present invention provides an ICE monitoring method and system, comprising: obtaining a first preset monitoring indicator according to a first monitoring requirement; constructing a first custom exporter template in the Grafana visualization tool based on the first preset monitoring indicator; integrating with Pinpoint monitoring to construct a first custom ICE plugin; configuring the first custom ICE plugin into a plugin directory according to a first configuration instruction; and introducing the first custom exporter template and the first custom ICE plugin, using a Java agent as a first preset method, to perform monitoring. This method solves the technical problems of inadequate monitoring and the high invasiveness of third-party plugins in the prior art.

Description

Technical Field

[0001] The present invention relates to the technical field related to system monitoring, and in particular to an ICE monitoring method and system. Background Art

[0002] Zeroc Ice provides a cross-language, multi-platform, and efficient RPC framework based on TCP, UDP, WebSockets, SSL, and Bluetooth, supporting both synchronous and asynchronous calls. It reuses connections, uses compression, and employs efficient binary protocols to minimize CPU and network overhead, and can encrypt, decrypt, and verify data. Monitoring Zeroc Ice parameters helps optimize the system and prevent anomalies.

[0003] There are two main existing methods for monitoring Zeroc ice metrics. The first relies on IceMx, Ice's built-in metrics package, which primarily provides metrics information for the ice process, such as the number of client-initiated calls distributed by the ice server, the number of threads currently in use, and the amount of data transmitted by ice connections. The second method uses the open-source third-party metrics toolkit, Dropwizard Metrics, primarily for custom metrics monitoring. Developers need to write monitoring code to collect monitoring items, and the monitoring data can be output to external storage such as InfluxDB, Elasticsearch, or Zabbix via a reporter. Dropwizard Metrics collects monitoring data through scheduled tasks and outputs it in the form of a reporter. It can aggregate historical and multi-application metrics into unified external storage, and then visualize them through tools like Grafana, significantly addressing the shortcomings of IceMx.

[0004] IceMx, the metric package that comes with Ice, has nearly 30 attributes, which places high demands on configuration personnel. The configuration process is complex and cannot monitor historical data or metrics for each RPC. DropWizardMetrics requires programmers to hard-code, which is too invasive. There is no single call tracking for the monitoring items, and detailed call tracking information is impossible.

[0005] However, in the process of implementing the technical solutions of the embodiments of the present application, the inventors of the present application discovered that the above technology has at least the following technical problems:

[0006] The existing technology has technical problems such as insufficient monitoring and high intrusiveness when using third-party plug-ins. Summary of the Invention

[0007] The embodiments of the present application provide an ICE monitoring method and system to solve the technical problems in the prior art, such as inadequate monitoring and high intrusiveness when using third-party plug-ins. A custom exporter template is constructed in the Grafana visualization tool through preset monitoring indicators to display the monitored data; then, combined with Pinpoint monitoring, a custom ICE plugin is constructed, and each working module is inserted into the plugin directory to implement monitoring of Zeroc Ice. The custom exporter template and the custom ICE plugin are then introduced into the Zeroc Ice system using the Javaagent method. Since the Javaagent introduction does not require the configuration of various parameters, it is less intrusive. The technical effects of comprehensive monitoring and less intrusive use of third-party plug-ins are achieved.

[0008] In view of the above problems, an embodiment of the present application provides an ICE monitoring method and system.

[0009] In a first aspect, an embodiment of the present application provides an ice monitoring method, which is applied to a custom open source monitoring system, wherein the method includes: obtaining a first preset monitoring indicator according to a first monitoring requirement; constructing a first custom exporter template in a grafana visualization tool based on the first preset monitoring indicator; constructing a first custom ice plugin by docking with pinpoint monitoring; configuring the first custom ice plugin to a plugin directory according to a first configuration instruction; introducing the first custom exporter template and the first custom ice plugin according to a first preset method, wherein the first preset method is a javaagent method; and monitoring according to the first custom exporter template and the first custom iceplugin.

[0010] On the other hand, an embodiment of the present application provides an ice monitoring system, wherein the system includes: a first obtaining unit, the first obtaining unit is used to obtain a first preset monitoring indicator according to a first monitoring requirement; a second obtaining unit, the second obtaining unit is used to build a first custom exporter template in the grafana visualization tool based on the first preset monitoring indicator; a first building unit, the first building unit is used to build a first custom ice plugin plug-in by docking with pinpoint monitoring; a first configuration unit, the first configuration unit is used to configure the first custom ice plugin plug-in into the plugin directory according to a first configuration instruction; a first introduction unit, the first introduction unit is used to introduce the first custom exporter template and the first custom ice plugin plug-in according to a first preset method, wherein the first preset method is a javaagent method; a first monitoring unit, the first monitoring unit is used to monitor according to the first custom exporter template and the first custom ice plugin plug-in.

[0011] In a third aspect, an embodiment of the present application provides an ice monitoring system, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods described in the first aspect when executing the program.

[0012] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0013] The system uses a first monitoring requirement to obtain a first preset monitoring indicator; based on the first preset monitoring indicator, a first custom exporter template is constructed in the Grafana visualization tool; a first custom ice plugin is constructed by integrating with Pinpoint monitoring; the first custom ice plugin is configured in the plugin directory according to a first configuration instruction; the first custom exporter template and the first custom ice plugin are introduced according to a first preset method, wherein the first preset method is a Java agent method; a technical solution for monitoring based on the first custom exporter template and the first custom ice plugin is constructed in the Grafana visualization tool to display the monitored data using the preset monitoring indicator; a custom ice plugin is constructed in conjunction with Pinpoint monitoring, and each working module is inserted into the plugin directory to implement monitoring of Zeroc Ice. The custom exporter template and the custom ice plugin are then introduced into the Zeroc Ice system using the Java agent method. Because Java agent introduction does not require configuration of various parameters and is less invasive, this achieves the technical effect of comprehensive monitoring and less invasive use of third-party plugins.

[0014] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a flow chart of an ICE monitoring method according to an embodiment of the present application;

[0016] Figure 2 This is a flowchart of a method for implementing an ICE monitoring visualization interface according to an embodiment of the present application;

[0017] Figure 3 This is a flowchart of an ICE monitoring data storage method according to an embodiment of the present application;

[0018] Figure 4 This is a schematic diagram of the structure of an ice monitoring system according to an embodiment of the present application;

[0019] Figure 5 This is a schematic diagram of the structure of an exemplary electronic device according to an embodiment of the present application.

[0020] Explanation of the reference numerals: first obtaining unit 11 , second obtaining unit 12 , first constructing unit 13 , first configuring unit 14 , first introducing unit 15 , first monitoring unit 16 , electronic device 300 , memory 301 , processor 302 , communication interface 303 , bus architecture 304 . DETAILED DESCRIPTION

[0021] The embodiments of the present application provide an ICE monitoring method and system to solve the technical problems in the prior art, such as inadequate monitoring and high intrusiveness when using third-party plug-ins. A custom exporter template is constructed in the Grafana visualization tool using preset monitoring indicators to display the monitored data. Combined with Pinpoint monitoring, a custom ICE plugin is constructed, and each work module is inserted into the plugin directory to monitor the Zeroc ICE industry. Javaagent is then used to introduce the custom exporter template and custom ICE plugin into the Zeroc ICE system. Because the Javaagent introduction does not require the configuration of various parameters, it is less intrusive. This achieves the technical effect of comprehensive monitoring and less intrusive use of third-party plug-ins.

[0022] Application Overview

[0023] Zeroc Ice provides a cross-language, multi-platform, and efficient RPC framework based on TCP, UDP, WebSockets, SSL, and Bluetooth, supporting both synchronous and asynchronous calls. It reuses connections, uses compression, and employs efficient binary protocols to minimize CPU and network overhead, and can encrypt, decrypt, and verify data. Monitoring Zeroc Ice parameters helps optimize the system and prevent anomalies.

[0024] There are two main existing methods for monitoring Zeroc ice metrics: the first relies on IceMx, Ice's built-in metrics package, which primarily provides metrics information for the ice process, such as the number of client-initiated calls distributed by the ice server, the number of threads currently in use, and the amount of data transmitted by the ice connection. The second method uses the open-source third-party metrics toolkit Dropwizard Metrics, which is primarily suitable for custom metrics monitoring. Developers need to write monitoring code to collect monitoring items, and the monitoring data can be output to external storage such as influxdb, elasticsearch, and zabbix via a reporter. Dropwizard Metrics collects monitoring data through scheduled tasks and outputs it in the form of a reporter. It can aggregate historical and multi-application metrics into unified external storage, and then visualize them through tools like Grafana, significantly addressing the shortcomings of IceMx. IceMx, the metric package included with Ice, has nearly 30 attributes, placing high demands on configuration personnel. The configuration process is complex and cannot monitor historical data or metrics for individual RPCs. DropWizard metrics require programmers to hard-code them, making them highly invasive. Furthermore, there's no single call tracking for monitored items, making detailed call tracking impossible. However, existing technologies suffer from inadequate monitoring and high invasiveness when using third-party plug-ins.

[0025] In response to the above technical problems, the overall idea of ​​the technical solution provided by this application is as follows:

[0026] An embodiment of the present application provides an ice monitoring method, which is applied to a custom open source monitoring system, wherein the method includes: obtaining a first preset monitoring indicator according to a first monitoring requirement; constructing a first custom exporter template in a grafana visualization tool based on the first preset monitoring indicator; constructing a first custom ice plugin by docking with pinpoint monitoring; configuring the first custom ice plugin to a plugin directory according to a first configuration instruction; introducing the first custom exporter template and the first custom ice plugin according to a first preset method, wherein the first preset method is a javaagent method; and monitoring according to the first custom exporter template and the first custom iceplugin.

[0027] After introducing the basic principles of the present application, various non-limiting implementation methods of the present application will be specifically introduced in conjunction with the drawings in the specification.

[0028] Example 1

[0029] like Figure 1 As shown, an embodiment of the present application provides an ICE monitoring method, which is applied to a custom open source monitoring system, wherein the method includes:

[0030] S100: Obtaining a first preset monitoring indicator according to a first monitoring requirement;

[0031] Specifically, the first monitoring requirement refers to the status indicator actually referenced by the zeroc ice framework, including but not limited to: how many times the ice server has distributed calls initiated by the client, the number of threads currently in use, the amount of data transmitted by the ice connection, how many times the ice client has received feedback information initiated by the server, and other data; the first preset monitoring indicator refers to the data obtained by classifying and storing the first monitoring requirement information. For example, there is no restriction: it is divided into port-type demand monitoring data, such as the data corresponding to the above-mentioned ice server and ice client; business call link demand monitoring data, that is, the corresponding data during the call process, such as the number of threads currently in use, the amount of data transmitted by the ice connection, the number of threads used in the past hour, the type of threads used at a fixed point, and other information. Through the classified storage of the first preset monitoring indicator, the corresponding module can be called for monitoring based on different types of demand monitoring data.

[0032] S200: Building a first custom exporter template in the Grafana visualization tool based on the first preset monitoring indicator;

[0033] Specifically, the first custom exporter template refers to calling the first preset monitoring indicator information stored, and constructing the parameter page to be displayed in the Grafana visualization tool based on the data to be monitored, which is used to expose the indicator data of Zeroc Ice. The Grafana visualization tool refers to a cross-platform open source measurement analysis and visualization tool that can query the collected data and then visualize it and provide timely notifications. In short, it is a multi-purpose monitoring tool that can also provide effective early warning notifications through methods such as email. Its rich and intuitive visualization interface and multiple data source configurations are its advantages. Preferably, the Prometheus system and the Grafana visualization tool are connected to a custom monitoring view, that is, the first custom exporter template, wherein the Prometheus system refers to an open source monitoring and alarm system based on a time series database designed and implemented in cloud native. Prometheus comes with a visualization view interface and AlertManager alarm component, and can flexibly connect to the Grafana custom monitoring view. Both the server and the client are out-of-the-box and do not require installation. The indicator data of Zeroc Ice is exposed through the first custom exporter template, and analysis can be performed based on the data and alarms can be issued when the indicators are abnormal.

[0034] S300: Build the first custom ice plugin by connecting to Pinpoint monitoring;

[0035] Specifically, the Pinpoint monitoring system is a full-link analysis tool that provides non-invasive call chain monitoring, method execution details viewing, and application status information monitoring. A few examples of available monitoring functions include service topology diagrams, real-time active thread diagrams, request-response scatter plots, request call stack viewing, application status, machine status checks, and other metrics. Because Pinpoint monitoring requires only selecting the appropriate call method and does not require parameter configuration, monitoring through the Pinpoint system is less invasive and has a minimal impact on the Zeroc Ice framework system. The first custom Ice plugin is a plugin designed to extend the Zeroc Ice framework architecture for integration with the Pinpoint monitoring system. By integrating with the Pinpoint monitoring system, comprehensive monitoring can be achieved. For example, if metrics are needed for each call, clicking on a service node in the service topology diagram displays detailed information about that node, such as the current node status and number of requests.

[0036] S400: According to the first configuration instruction, configure the first custom ice plugin into the plugin directory;

[0037] Specifically, the plugin directory refers to the various components of the PinPoint monitoring system within the first custom Ice plugin; the first configuration refers to the control signal issued by the ZeroCice framework system to initiate configuration of the various components of the PinPoint monitoring system within the extended architecture according to the plugin directory. For example, if the PinPoint monitoring system components in the first custom Ice plugin include: a Collector component (a data collection module that receives monitoring data and stores it in a database); and a Web UI component (a monitoring display module that displays system call relationships, call details, application status, etc., and supports functions such as alarms), then configuring these components to the plugin directory results in the PinPointCollector component and the PinPointWebUI component being implemented on the ZeroCice framework. By configuring the first custom Ice plugin to the plugin directory, the PinPoint monitoring system is fully extended on the ZeroCice framework system and is ready for invocation.

[0038] S500: Introducing the first custom exporter template and the first custom ice plugin according to a first preset method, wherein the first preset method is a javaagent method;

[0039] S600: Monitoring is performed according to the first customized exporter template and the first customized ice plugin.

[0040] Furthermore, based on monitoring according to the first customized exporter template and the first customized ice plugin, the method step S600 includes:

[0041] S610: The pinpoint monitoring can view the virtual machine monitoring indicators and service link call details of the client and server through the Web server;

[0042] S620: The virtual machine monitoring indicator is obtained through the first virtual machine, wherein the first virtual machine mainly deploys the main program of the pinpoint monitoring, including the Hbase database, the collector controller and the display end of the Web server.

[0043] Specifically, the first preset method involves introducing the first custom exporter template and the first custom ice plugin, and then waiting for invocations to perform monitoring. The Javaagent method involves adding monitoring code at the virtual machine level, enabling minimally invasive introduction of the monitoring module. After introduction, the Zerocice framework system can be fully monitored based on the first custom exporter template and the first custom ice plugin, achieving comprehensive and minimally invasive monitoring.

[0044] Furthermore, based on the first configuration instruction, the first custom ice plugin is configured into the plugin directory, and the method step S400 further includes:

[0045] S410: Obtain a first deployment instruction and a first configuration instruction;

[0046] S420: Deploy the HBase database, collector controller, and Web server application monitored by the pinpoint according to the first deployment instruction, wherein the HBase database is used to store monitoring information;

[0047] S430: According to the first configuration instruction, configure the first custom ice plugin plug-in to the plugin directory of the collector controller and the Web server.

[0048] Specifically, the first deployment instruction refers to deploying the loading locations of each module in the plugin directory extension architecture based on the Pinpoint monitoring component modules of the first custom ice plugin, such as the HBase database, the collector controller, and the Web server application, wherein the HBase database is used to store monitoring information; the collector controller is used to receive monitoring data sent by the javaagentgent and store it in the HBase database; the Web server is used to display system call relationships, call details, application status, etc., and supports functions such as alarms. Furthermore, according to the first configuration instruction, each component module in the first custom ice plugin is loaded into the corresponding location in the plugin directory extension architecture, awaiting call, which can implement the monitoring functions supported by Pinpoint monitoring.

[0049] Furthermore, based on monitoring according to the first customized exporter template and the first customized ice plugin, the method step S600 includes:

[0050] S610: The pinpoint monitoring can view the virtual machine monitoring indicators and service link call details of the client and server through the Web server;

[0051] S620: The virtual machine monitoring indicator is obtained through the first virtual machine, wherein the first virtual machine mainly deploys the main program of the pinpoint monitoring, including the Hbase database, the collector controller and the display end of the Web server.

[0052] Specifically, the virtual machine refers to a complete computer system with complete hardware system functions, running in a completely isolated environment, simulated by software. Through virtual machine software, one or more virtual computers can be simulated on a physical computer, and these virtual machines operate exactly like real computers. The Java agent method adds monitoring code at the virtual machine level, eliminating the need for hard coding and resulting in minimal invasiveness. The monitoring code, combined with the various functional modules monitored by Pinpoint, monitors the client and server based on the port monitoring requirements in the first preset monitoring indicators to obtain corresponding call and feedback information. The service call link requirement monitoring data in the first preset monitoring indicators is monitored to obtain service link call detail data, which constitutes the virtual machine monitoring indicators. The first virtual machine refers to the simulated computer on which the Pinpoint monitoring main program is deployed, including the HBase database, the collector controller, and the presentation end of the web server. Deploying each monitoring module based on the first virtual machine is minimally invasive to the original system.

[0053] Furthermore, based on the Pinpoint monitoring, the virtual machine monitoring indicators and service link call details including the client and server can be viewed through the Web server. Step S610 of the method includes:

[0054] S611: Obtain a first historical call link according to the pinpoint monitoring;

[0055] S612: Obtain a first marked instruction based on the first historical call link;

[0056] S613: Obtain a first marking call link according to the first marking instruction;

[0057] S614: Track and monitor the first tag call link according to the first tracking instruction.

[0058] Specifically, the first historical call link refers to the historical link call status from the start of the call command to a certain preset time in the past. Based on the monitoring data obtained by the Pinpoint monitoring, data information that matches the first historical call link is filtered out and matched with the first historical call link. Furthermore, the first marking instruction refers to marking the first historical call link so that the corresponding data can be located according to the mark when detailed node data needs to be called. The first marked call link is the first historical call link marked according to the first marking instruction. The first tracking instruction refers to a control signal issued after the historical data of the first historical call link matches the first historical call link, which continues to monitor the indicators of the first marked call link in real time. Furthermore, the indicator information of the first marked call link is tracked in real time according to the first tracking instruction. By marking the first historical call link, it can be quickly called when detailed node information needs to be called, and it can also facilitate the Pinpoint monitoring to identify and continue to track detailed data in real time. The historical data corresponding to the first historical call link can also be called according to the mark.

[0059] Further, such as Figure 2 As shown, the method includes step S700:

[0060] S710: Obtain a first visualization interface of the grafana visualization tool;

[0061] S720: Input a first query instruction into the first visualization interface;

[0062] S730: Obtain first query indicators according to the first query instruction, where the first query indicators include various indicators of the ice server and the ice client.

[0063] Specifically, the first visualization interface refers to an interface that displays various indicator data based on the display of the Grafana visualization tool; the first query instruction refers to setting a query instruction based on the required indicator information. For example, there is no restriction: querying various indicator data such as the number of call information distributed by the server in one hour; the first query indicator refers to the corresponding indicator information obtained by entering the first query instruction into the search bar of the first visualization interface; the ice server refers to the indicator information of the port class, including server indicator data and client indicator data; the ice client refers to the process indicator data of the business link class, and the ice server indicator and the ice client indicator are both included in the first query indicator. The indicator data obtained through monitoring is integrated through the first visualization interface, achieving the technical effect of obtaining a unified system view.

[0064] Furthermore, based on introducing the first customized exporter template and the first customized ice plugin according to the first preset manner, the method S500 includes:

[0065] S510: Obtaining a first calling method of the Javaagent mode according to the Pinpoint monitoring;

[0066] S520: Generate a first calling instruction according to the first calling method;

[0067] S530: Calling the first preset mode based on the first calling instruction.

[0068] Specifically, the first calling method refers to adding monitoring code methods matching the various functional options of the Pinpoint monitoring module at the first virtual machine level according to the Javaagent method. The first calling instruction refers to the control signal issued after the first calling method completes the matching process, invoking the first custom exporter template and the first custom ice plugin. Furthermore, invoking the first custom exporter template and the first custom ice plugin according to the first calling method to achieve the monitoring purpose is the process introduced according to the first preset method. By combining the Javaagent method with Pinpoint monitoring, the technical effect of less invasive and comprehensive monitoring of system indicators is achieved.

[0069] Further, based on the monitoring according to the first custom exporter template and the first custom iceplugin plug-in, as Figure 3As shown, the method further includes step S800:

[0070] S810: Perform monitoring based on the first customized exporter template and the first customized ice plugin to obtain first monitoring indicator data;

[0071] S820: Storing the first monitoring indicator data in the Hbase database;

[0072] S830: Periodically store the data in the Hbase database according to a first preset data storage period.

[0073] Specifically, the first monitoring indicator data refers to a series of system indicator data obtained after calling the first custom exporter template and the first custom ice plugin for monitoring according to the first calling method; the first monitoring indicator data is stored in the Hbase database; the first preset data storage period refers to the preset frequency of storing the first monitoring indicator data in the Hbase database, which can be freely defined according to actual needs; the first monitoring indicator data is stored according to the first preset data storage period. By periodically storing the first monitoring indicator data, the technical effect of calling historical indicator data can be achieved.

[0074] In summary, the ICE monitoring method and system provided by the embodiments of the present application have the following technical effects:

[0075] 1. Based on a first monitoring requirement, a first preset monitoring indicator is obtained; based on the first preset monitoring indicator, a first custom exporter template is constructed in the Grafana visualization tool; a first custom ice plugin is constructed by integrating with Pinpoint monitoring; the first custom ice plugin is configured in the plugin directory according to a first configuration instruction; the first custom exporter template and the first custom ice plugin are introduced according to a first preset method, wherein the first preset method is a Java agent method; a technical solution for monitoring based on the first custom exporter template and the first custom ice plugin is used. A custom exporter template is constructed in the Grafana visualization tool to display monitored data based on the preset monitoring indicator; a custom ice plugin is constructed in conjunction with Pinpoint monitoring, and each working module is inserted into the plugin directory to implement monitoring of Zeroc Ice. The custom exporter template and the custom ice plugin are then introduced into the Zeroc Ice system using the Java agent method. Because Java agent introduction does not require configuration of various parameters and is less invasive, this achieves the technical effect of comprehensive monitoring and less invasive use of third-party plugins.

[0076] 2. The indicator data obtained from monitoring is integrated through the first visual interface, achieving the technical effect of obtaining a unified system view.

[0077] 3. By periodically storing the first monitoring indicator data, the technical effect of calling historical indicator data can be achieved.

[0078] Example 2

[0079] Based on the same inventive concept as the ice monitoring method in the above embodiment, Figure 4 As shown, an embodiment of the present application provides an ICE monitoring system, wherein the system includes:

[0080] A first obtaining unit 11, wherein the first obtaining unit 11 is configured to obtain a first preset monitoring indicator according to a first monitoring requirement;

[0081] A second obtaining unit 12, wherein the second obtaining unit 12 is configured to construct a first custom exporter template in a Grafana visualization tool based on the first preset monitoring indicator;

[0082] A first construction unit 13 is used to build a first custom ice plugin by connecting to Pinpoint monitoring;

[0083] A first configuration unit 14, configured to configure the first custom ice plugin into a plugin directory according to a first configuration instruction;

[0084] A first introducing unit 15 is configured to introduce the first custom exporter template and the first custom ice plugin according to a first preset method, wherein the first preset method is a javaagent method;

[0085] The first monitoring unit 16 is configured to perform monitoring according to the first customized exporter template and the first customized ice plugin.

[0086] Furthermore, the system further comprises:

[0087] a third obtaining unit, configured to obtain a first deployment instruction and a first configuration instruction;

[0088] a first deployment unit, configured to deploy an HBase database, a collector controller, and a Web server application monitored by the pinpoint according to the first deployment instruction, wherein the HBase database is used to store monitoring information;

[0089] The first configuration unit is used to configure the first custom ice plugin plug-in to the plugin directory of the collector controller and the Web server according to the first configuration instruction.

[0090] Furthermore, the system further comprises:

[0091] A first viewing unit, wherein the first viewing unit is used for the Pinpoint monitoring to view the virtual machine monitoring indicators and service link call details including the client and server through the Web server;

[0092] The second deployment unit is used to obtain the virtual machine monitoring indicators through the first virtual machine, wherein the first virtual machine mainly deploys the main program monitored by the pinpoint, including the Hbase database, the collector controller and the display end of the Web server.

[0093] Furthermore, the system further comprises:

[0094] a fourth obtaining unit, configured to obtain a first historical call link according to the pinpoint monitoring;

[0095] a fifth obtaining unit, configured to obtain a first marking instruction based on the first historical call link;

[0096] a sixth obtaining unit, configured to obtain a first marking call link according to the first marking instruction;

[0097] A first calling unit is configured to track and monitor the first tag call link according to a first tracking instruction.

[0098] Furthermore, the system further comprises:

[0099] A seventh obtaining unit, wherein the seventh obtaining unit is used to obtain a first visualization interface of the grafana visualization tool;

[0100] a first input unit, the first input unit being used to input a first query instruction into the first visual interface;

[0101] An eighth obtaining unit is configured to obtain a first query indicator according to the first query instruction, wherein the first query indicator includes various indicators of the ice server and the ice client.

[0102] Furthermore, the system further comprises:

[0103] a ninth obtaining unit, configured to obtain, according to the pinpoint monitoring, a first calling method of the javaagent mode;

[0104] a first generating unit, configured to generate a first calling instruction according to the first calling method;

[0105] A second calling unit, wherein the second calling unit is configured to call the first preset mode based on the first calling instruction.

[0106] Furthermore, the system further comprises:

[0107] a tenth obtaining unit, configured to perform monitoring based on the first custom exporter template and the first custom ice plugin to obtain first monitoring indicator data;

[0108] A first storage unit, the first storage unit is used to store the first monitoring indicator data in the Hbase database;

[0109] The second storage unit is used to periodically store the data in the Hbase database through a first preset data storage period.

[0110] Exemplary electronic devices

[0111] Reference below Figure 5 To describe the electronic device of the embodiment of the present application,

[0112] Based on the same inventive concept as the ICE monitoring method in the aforementioned embodiment, the embodiment of the present application further provides an ICE monitoring system, comprising: a processor, the processor being coupled to a memory, the memory being used to store a program, and when the program is executed by the processor, the system executes the method described in any one of the first aspects.

[0113] The electronic device 300 includes: a processor 302, a communication interface 303, and a memory 301. Optionally, the electronic device 300 may further include a bus architecture 304. The communication interface 303, the processor 302, and the memory 301 may be interconnected via the bus architecture 304; the bus architecture 304 may be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 5 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0114] The processor 302 may be a CPU, a microprocessor, an ASIC, or one or more integrated circuits for controlling the execution of the program of the present application.

[0115] The communication interface 303 uses any transceiver-like device for communicating with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), wired access network, etc.

[0116] The memory 301 may be a ROM or other static storage device that can store static information and instructions, a RAM or other dynamic storage device that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc, or a read-only optical disk.

[0117] The computer may store, for example, a computer program code (program code) in a form of a read-only memory (CD-ROM) or other optical disk storage, optical disk storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but is not limited thereto. The memory may be independent and connected to the processor via the bus architecture 304. The memory may also be integrated with the processor.

[0118] The memory 301 is used to store computer-executable instructions for executing the solution of the present application, and the execution is controlled by the processor 302. The processor 302 is used to execute the computer-executable instructions stored in the memory 301, thereby implementing an ICE monitoring method provided by the above embodiment of the present application.

[0119] Optionally, the computer-executable instructions in the embodiments of the present application may also be referred to as application code, which is not specifically limited in the embodiments of the present application.

[0120] An embodiment of the present application provides an ICE monitoring method, which is applied to a custom open source monitoring system. The method includes: obtaining a first preset monitoring indicator based on a first monitoring requirement; constructing a first custom exporter template in the Grafana visualization tool based on the first preset monitoring indicator; constructing a first custom ICE plugin by integrating with Pinpoint monitoring; configuring the first custom ICE plugin into a plugin directory according to a first configuration instruction; introducing the first custom exporter template and the first custom ICE plugin according to a first preset method, wherein the first preset method is a Java agent method; and performing monitoring based on the first custom exporter template and the first custom ICE plugin. A custom exporter template is constructed in the Grafana visualization tool based on the preset monitoring indicator to display monitored data; a custom ICE plugin is then constructed in conjunction with Pinpoint monitoring, and each working module is inserted into the plugin directory to implement monitoring of the ZeroC ICE industry. The custom exporter template and the custom ICE plugin are then introduced into the ZeroC ICE system using a Java agent method. Because Java agent introduction does not require configuration of various parameters, it is less invasive. This achieves the technical effect of comprehensive monitoring and less invasive use of third-party plugins.

[0121] Those skilled in the art will understand that the various numerical numbers such as the first and second involved in this application are only for the convenience of description, and are not used to limit the scope of the embodiments of the present application, nor do they represent the order of precedence. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one" refers to one or more. At least two refers to two or more. "At least one", "any one" or similar expressions refer to any combination of these items, including any combination of single items (individuals) or plural items (individuals). For example, at least one item (individual, kind) of a, b, or c can represent: a, b, c, a-b, ac, bc, or abc, where a, b, c can be single or multiple.

[0122] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware, or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiments of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable system. The computer instructions

[0123] The instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a magnetic tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state drive (SSD)).

[0124] The various illustrative logic units and circuits described in the embodiments of the present application can be implemented or operated by the design of a general-purpose processor, a digital signal processor, an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic system, discrete gate or transistor logic, discrete hardware components, or any combination thereof. The general-purpose processor can be a microprocessor, alternatively, the general-purpose processor can also be any traditional processor, controller, microcontroller or state machine. The processor can also be implemented by a combination of computing devices, such as a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration to implement.

[0125] The steps of the method or algorithm described in the embodiments of the present application can be directly embedded in hardware, software units executed by a processor, or a combination of the two. The software unit can be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM or any other form of storage medium in the art. For example, the storage medium can be connected to the processor so that the processor can read information from the storage medium and write information to the storage medium. Optionally, the storage medium can also be integrated into the processor. The processor and the storage medium can be provided in an ASIC, and the ASIC can be provided in a terminal. Optionally, the processor and the storage medium can also be provided in different components in the terminal. These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are performed on the computer or other programmable device to produce computer-implemented processing, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0126] Although the present application has been described with reference to specific features and embodiments thereof, it will be apparent that various modifications and combinations may be made thereto without departing from the spirit and scope of the present application. Accordingly, this specification and the drawings are merely illustrative of the present application as defined by the appended claims and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, the present application intends to include such modifications and variations if they fall within the scope of the claims of the present application and their equivalents.

Claims

1. An ice monitoring method, the method being applied to a custom open source monitoring system, wherein: The method comprises: According to a first monitoring requirement, a first preset monitoring indicator is obtained; the first monitoring requirement is determined according to a zeroc ice framework; Based on the first preset monitoring indicator, a first custom exporter template is constructed in the Grafana visualization tool; the first preset monitoring indicator refers to data obtained by classifying and storing the first monitoring requirement information; By connecting to Pinpoint monitoring, we built the first custom ice plugin. According to the first configuration instruction, the first custom ice plugin is configured in the plugin directory; wherein the first custom exporter template is used to expose the indicator data of zeroc ice, and the plugin directory refers to the Pinpoint monitoring components in the first custom ice plugin; Introducing the first custom exporter template and the first custom ice plugin according to a first preset method, wherein the first preset method is a Javaagent method; the first preset method is invoked based on a first invocation instruction, the first invocation instruction is generated based on a first invocation method, and the first invocation method is used to add monitoring code matching each function option monitored by Pinpoint at the virtual machine level according to the Javaagent method; Monitoring is performed according to the first customized exporter template and the first customized ice plugin.

2. The method according to claim 1, wherein Configuring the first custom iceplugin plug-in into the plugin directory according to the first configuration instruction includes: Obtaining a first deployment instruction and a first configuration instruction; Deploy the HBase database, collector controller, and Web server application monitored by the pinpoint according to the first deployment instruction, wherein the HBase database is used to store monitoring information; According to the first configuration instruction, the first custom ice plugin is configured in the plugin directory of the collector controller and the Web server.

3. The method according to claim 2, wherein: Monitoring is performed according to the first customized exporter template and the first customized ice plugin, including: The pinpoint monitoring uses the web server to view the virtual machine monitoring indicators and business link call details including the client and server; The virtual machine monitoring indicator is obtained through the first virtual machine, wherein the first virtual machine deploys the main program monitored by Pinpoint, including the Hbase database, the collector controller and the display end of the Web server.

4. The method according to claim 3, wherein: The Pinpoint monitoring uses the Web server to view the virtual machine monitoring indicators and business link call details of the client and server, including: Obtaining a first historical call link according to the pinpoint monitoring; Based on the first historical call link, obtain a first marking instruction; Obtaining a first marking call link according to the first marking instruction; The first tag call link is traced and monitored according to the first tracing instruction.

5. The method of claim 1 , further comprising: Obtain a first visualization interface of the grafana visualization tool; Inputting a first query instruction into the first visual interface; According to the first query instruction, a first query indicator is obtained, wherein the first query indicator includes various indicators of the ice server and the ice client.

6. The method of claim 1, wherein: The introducing the first custom exporter template and the first custom ice plugin according to the first preset method includes: According to the pinpoint monitoring, obtaining the first calling method of the javaagent mode; Generate a first calling instruction according to the first calling method; The first preset mode is called based on the first calling instruction.

7. The method according to claim 1, wherein the monitoring according to the first customized exporter template and the first customized ice plugin further comprises: Performing monitoring based on the first custom exporter template and the first custom ice plugin to obtain first monitoring indicator data; Storing the first monitoring indicator data in an Hbase database; The data in the Hbase database is periodically stored based on a first preset data storage period.

8. An ice monitoring system, wherein: The system comprises: a first obtaining unit, configured to obtain a first preset monitoring indicator according to a first monitoring requirement; wherein the first monitoring requirement is determined according to a zeroc ice framework; a second obtaining unit, configured to construct a first custom exporter template in a Grafana visualization tool based on the first preset monitoring indicator; wherein the first preset monitoring indicator refers to data obtained by classifying and storing the first monitoring requirement information; A first building unit, wherein the first building unit is used to build a first custom iceplugin plug-in by connecting to pinpoint monitoring; a first configuration unit, configured to configure the first custom iceplugin plug-in into a plugin directory according to a first configuration instruction; wherein the first custom exporter template is used to expose indicator data of Zeroc Ice, and the plugin directory refers to the Pinpoint monitoring components in the first custom ice plugin plug-in; a first importing unit, configured to import the first custom exporter template and the first custom ice plugin according to a first preset method, wherein the first preset method is a javaagent method; the first preset method is invoked based on a first invocation instruction, the first invocation instruction is generated based on a first invocation method, and the first invocation method is configured to add monitoring code matching each function option of the pinpoint monitoring at a virtual machine level according to the javaagent method; A first monitoring unit is configured to perform monitoring according to the first custom exporter template and the first custom ice plugin.

9. An ice monitoring system comprising: A processor is coupled to a memory, wherein the memory is used to store a program, and when the program is executed by the processor, the monitoring system executes the method according to any one of claims 1 to 7.

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