A method for global monitoring of a full-link large screen based on a monitoring platform observation system

Abstract

The application discloses a full-link large-screen global monitoring board method based on a monitoring platform observation system, relates to the technical field of computers, and solves the technical problem that the prior art does not consider observing the operation of a business system from a global perspective, which may cause the loss of enterprise business due to business system operation failure; the application acquires business request data, determines the life cycle of a business request; divides the business system into a plurality of business nodes, and defines corresponding monitoring indexes; constructs a full-link monitoring board platform of a large screen, displays the defined monitoring indexes on the full-link monitoring board in a visual manner; collects operation data of the business system, processes the operation data to obtain monitoring index data; judges whether there is a fault node in the plurality of business nodes according to the monitoring index data; if yes, an early warning notice is generated; if no, the monitoring index data is continuously detected; the fault node is processed according to the early warning notice, and the normal operation of the business system is ensured.

Description

Technical Field

[0001] This invention belongs to the field of computer technology and relates to business system monitoring and data analysis technology, specifically a full-link large-screen global monitoring dashboard method based on a monitoring platform observation system. Background Technology

[0002] The end-to-end dashboard can display the IT operational status in real time, ensuring the immediacy of monitoring. Through the dashboard interface, information such as asset quantity, link relationships, and anomalies can be presented in intuitive and vivid visual graphics, helping operations and maintenance personnel quickly understand the system status. The end-to-end dashboard integrates all IT assets into a unified monitoring platform, realizing integrated monitoring of the data center. The unified monitoring interface enables operations and maintenance personnel to have a comprehensive grasp of the system status, avoiding the problem of information silos and improving monitoring efficiency.

[0003] The prior art (patent application CN115878425A) discloses an automated monitoring method for enterprise big data business reports. This method includes the following steps: S1, acquiring different types of core indicator data from different reports; S2, configuring the core indicator data; S3, under different pre-configured scheduling frequencies, obtaining the interface address based on the primary key, concatenating the interface parameters and interface address to obtain the required core indicator data from the report, and parsing the response message for the required core indicator data; S4, storing the encrypted data in a MySQL database; S5, configuring monitoring conditions, performing early warning monitoring, and obtaining monitoring results. However, the prior art achieves global automated monitoring by quickly configuring the report interface address and interface parameters, automatically generating a complete interface access address after configuration, and then parsing and marking the result data returned by the interface using regular expressions and basic tagging methods. It does not consider observing the operation of the business system from a global perspective, which may lead to business losses due to business system malfunctions.

[0004] This invention provides a full-link large-screen global monitoring dashboard method based on a monitoring platform observation system to solve the above-mentioned technical problems. Summary of the Invention

[0005] This invention aims to at least solve one of the technical problems existing in the prior art; to this end, this invention proposes a full-link large-screen global monitoring dashboard method based on a monitoring platform observation system, which is used to solve the technical problem that the prior art does not consider observing the operation of the business system from a global perspective, and may cause business losses due to the failure of the business system.

[0006] To achieve the above objectives, the first aspect of the present invention provides a method for a full-link large-screen global monitoring dashboard based on a monitoring platform observation system, comprising:

[0007] Step S1: Obtain business request data and determine the lifecycle of the business request based on the business request data; wherein, the business request data includes initiation data, processing data, and response data;

[0008] Step S2: Divide the business system into several business nodes according to the lifecycle of business requests; define corresponding monitoring metrics for each business node.

[0009] Step S3: Build a large-screen end-to-end monitoring dashboard platform to display the defined monitoring metrics in a visual way on the end-to-end monitoring dashboard;

[0010] Step S4: Collect operational data of the business system in real time through the end-to-end monitoring dashboard platform, process and analyze the operational data to obtain real-time monitoring indicator data;

[0011] Step S5: Detect the monitoring indicator data of several business nodes to determine whether there are any faulty nodes among them; if yes, generate an early warning notification; if no, continue to detect the monitoring indicator data; and handle the faulty nodes according to the early warning notification.

[0012] Preferably, determining the lifecycle of a business request based on the business request data includes:

[0013] The user enters a URL in the client to initiate a service request; the client requests the DNS server to resolve the domain name in the URL to obtain the IP address of the target server; based on the IP address of the target server, the client sends the request to the IDC data center;

[0014] In an IDC (Internet Data Center) server room, the firewall determines whether a request complies with the security policy; if yes, the request is allowed to pass and sent to the core switch; otherwise, the request is not allowed to pass.

[0015] The core switch forwards requests to the corresponding web application server based on the routing table, and the gateway processes different requests and then sends the requests to several corresponding servers.

[0016] After processing the request using middleware, the processing results are stored in a database or file system; the processing results are then encapsulated into an HTTP response and returned to the client through gateways, switches, firewalls, and the Internet.

[0017] It should be noted that the request lifecycle refers to the entire process from when the client initiates a request until the client receives the server's response and ends the request.

[0018] This invention acquires business request data throughout the entire process of a business system, determines the lifecycle of the request based on the entire process, and can monitor each stage of the entire lifecycle, ensuring the smooth operation of the business, facilitating full-link monitoring, and enhancing the correlation between each stage.

[0019] Preferably, the step of dividing the business system into several business nodes according to the lifecycle of the business request includes:

[0020] Retrieve the lifecycle of the business request and extract the data type of the business request data; allocate the business data of each data type to the corresponding server; design a portal page on each server as the business entry point; the portal page displays the core functions and information of the business type.

[0021] Extract core business data from business request data of several data types as primary business entry points; analyze the requests under several primary business entry points to obtain all requests generated by the user during operation; identify business data that meets the set criteria from several requests as secondary business data.

[0022] Determine the data sources and data types required for several secondary business operations; select the storage nodes of requests that meet the requirements of the secondary business operations from the database as the end nodes of the requests.

[0023] This invention determines the primary business entry point based on the data type of the business request data; extracts secondary business from the requests under the primary business entry point, and selects storage nodes that meet the business requirements as the end nodes; it can flexibly divide business nodes, and when business requirements change, only the corresponding business nodes need to be adjusted; this is beneficial to improving the flexibility of the business system.

[0024] Preferably, the monitoring metrics include: IDC network equipment, infrastructure, basic monitoring, service monitoring, application services, middleware, log monitoring, and business metrics such as processing time, response rate, and success rate.

[0025] Preferably, the process of processing and analyzing the operational data to obtain real-time monitoring indicator data includes:

[0026] Retrieve operational data from the business system and determine if the data is complete. If yes, retain the corresponding operational data; otherwise, manually supplement the operational data. The operational data includes log data, performance metrics, and transaction trace data.

[0027] Based on the logical structure of the business system, the running data is divided into corresponding business nodes, and the performance indicators of several business nodes are calculated and marked as monitoring indicator data; among them, the monitoring indicator data includes processing time, response rate and success rate.

[0028] This invention uses a monitoring platform to collect and process operational data in real time, and generates monitoring index data based on the performance indicators of the operational data. This allows for understanding the usage of system resources, which is beneficial for optimizing resource allocation, ensuring that critical tasks receive sufficient resource support, and avoiding resource waste.

[0029] Preferably, determining whether there is a faulty node among the plurality of service nodes includes:

[0030] Retrieve monitoring indicator data from several business nodes and fit the monitoring indicator data into a curve F(t); solve for the first derivative f(t) of the curve F(t);

[0031] Determine whether there exists a part in the first derivative |f(t)| that is greater than y = n; if yes, mark the abnormal part and generate an early warning notification; otherwise, continue to analyze the monitoring indicator data.

[0032] This invention analyzes the abnormal growth and decline of monitoring indicator curves, and generates early warning notifications in a timely manner when an anomaly is detected; it can immediately initiate fault investigation and repair processes, reduce the downtime of business systems, and help ensure the continuity and stability of business.

[0033] Preferably, the step of processing the faulty node according to the early warning notification includes:

[0034] Retrieve early warning notifications, identify abnormal monitoring indicator data based on the early warning notifications, and mark the abnormal monitoring indicator data as abnormal data.

[0035] Historical abnormal data is retrieved from the database, and the abnormal data is matched with the historical abnormal data to obtain the similarity between the historical abnormal data and the abnormal data; several historical abnormal data with similarity greater than the similarity threshold are selected as reference data.

[0036] Several parameter data were analyzed to identify several causes of anomalies; based on these causes, log files were investigated and those corresponding to the causes of anomalies were selected.

[0037] The selected log files are analyzed to obtain the corresponding processing methods. The abnormal data is processed according to the processing methods, and the results are verified. The processing process and results are stored in the corresponding database.

[0038] This invention enables timely investigation and handling of faulty nodes through early warning notifications, allowing for intervention measures to be taken before the fault spreads, which helps to avoid chain reactions and reduce business losses caused by the fault.

[0039] Compared with the prior art, the beneficial effects of the present invention are:

[0040] 1. This invention acquires the entire process of business request data within a business system, determines the request lifecycle based on the entire process, monitors each stage of the entire lifecycle, ensures smooth business operation and resolves problems, facilitates full-link monitoring, and enhances the correlation between each stage; determines the primary business entry point based on the data type of the business request data; extracts secondary business from requests under the primary business entry point, and selects storage nodes that meet business requirements as end nodes; it allows for flexible division of business nodes, and when business requirements change, only the corresponding business nodes need to be adjusted; thus, it improves the flexibility of the business system.

[0041] 2. This invention monitors and processes operational data in real time through a monitoring platform system, generating monitoring indicator data based on the performance metrics of the operational data. This allows for understanding of system resource usage, facilitating optimized resource allocation, ensuring sufficient resource support for critical tasks, and preventing resource waste. It analyzes abnormal increases and decreases in monitoring indicator curves, generating timely early warning notifications when anomalies are detected. It enables immediate initiation of fault investigation and repair processes, reducing business system downtime and ensuring business continuity and stability. Timely investigation and handling of faulty nodes through early warning notifications allows for intervention before the fault spreads, preventing chain reactions and reducing business losses caused by faults. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a schematic diagram illustrating the specific steps of the present invention;

[0044] Figure 2 This is a schematic diagram illustrating the connection configuration of the present invention;

[0045] Figure 3 This is a schematic diagram illustrating the steps of dividing business nodes in this invention;

[0046] Figure 4 This is a schematic diagram of the abnormal monitoring indicator data detection steps of the present invention;

[0047] Figure 5 This is a schematic diagram illustrating the representation of abnormal points in this invention. Detailed Implementation

[0048] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0049] Please see Figure 1 The first aspect of this invention provides a method for a full-link large-screen global monitoring dashboard based on a monitoring platform observation system, comprising:

[0050] Step S1: Obtain business request data and determine the lifecycle of the business request based on the business request data; wherein, the business request data includes initiation data, processing data, and response data;

[0051] Step S2: Divide the business system into several business nodes according to the lifecycle of business requests; define corresponding monitoring metrics for each business node.

[0052] Step S3: Build a large-screen end-to-end monitoring dashboard platform to display the defined monitoring metrics in a visual way on the end-to-end monitoring dashboard;

[0053] Step S4: Collect operational data of the business system in real time through the end-to-end monitoring dashboard platform, process and analyze the operational data to obtain real-time monitoring indicator data;

[0054] Step S5: Detect the monitoring indicator data of several business nodes to determine whether there are any faulty nodes among them; if yes, generate an early warning notification; if no, continue to detect the monitoring indicator data; and handle the faulty nodes according to the early warning notification.

[0055] It is worth noting that the monitoring metrics include: IDC network equipment, infrastructure, basic monitoring, service monitoring, application services, middleware, log monitoring, and business metrics such as processing time, response rate, and success rate.

[0056] It should be noted that monitoring indicators are generally represented as a range or a certain threshold, which serves as a standard and lays the foundation for subsequent analysis.

[0057] Please see Figures 2-3 Determine the lifecycle of a business request, including the following steps:

[0058] The user enters a URL in the client to initiate a service request; the client requests the DNS server to resolve the domain name in the URL to obtain the IP address of the target server; based on the IP address of the target server, the client sends the request to the IDC data center;

[0059] In an IDC (Internet Data Center) server room, the firewall determines whether a request complies with the security policy; if yes, the request is allowed to pass and sent to the core switch; otherwise, the request is not allowed to pass.

[0060] The core switch forwards requests to the corresponding web application server based on the routing table, and the gateway processes different requests and then sends the requests to several corresponding servers.

[0061] After processing the request using middleware, the processing results are stored in a database or file system; the processing results are then encapsulated into an HTTP response and returned to the client through gateways, switches, firewalls, and the Internet.

[0062] For example: Suppose that a client initiates business requests A, B, and C; the client requests the DNS server to resolve the domain name in the URL to obtain the IP addresses A and B of the target server; based on the IP addresses A, B, and C of the target server, the client sends the request to the IDC data center;

[0063] In the IDC data center, the firewall checks whether service requests A, B, and C comply with the security policy. If request A does not comply with the security policy, while requests B and C do comply, then request A is not allowed to pass, and requests B and C are sent to the central switch.

[0064] After processing by the web application server, request B is sent to server 3 and request C is sent to server 1. After backend processing of requests B and C using middleware, requests B and C are returned to the client.

[0065] The business system is divided into several business nodes, including the following steps:

[0066] Retrieve the lifecycle of the business request and extract the data type of the business request data; allocate the business data of each data type to the corresponding server; design a portal page on each server as the business entry point; the portal page displays the core functions and information of the business type.

[0067] Extract core business data from business request data of several data types as primary business entry points; analyze the requests under several primary business entry points to obtain all requests generated by the user during operation; identify business data that meets the set criteria from several requests as secondary business data.

[0068] Determine the data sources and data types required for several secondary business operations; select the storage nodes of requests that meet the requirements of the secondary business operations from the database as the end nodes of the requests.

[0069] Please see Figures 4-5The system retrieves operational data from the business system and determines whether the data is complete. If it is, the corresponding operational data is retained; otherwise, the operational data is manually supplemented. The operational data includes log data, performance metrics, and transaction tracking data.

[0070] Based on the logical structure of the business system, the running data is divided into corresponding business nodes, and the performance indicators of several business nodes are calculated and marked as monitoring indicator data; among them, the monitoring indicator data includes processing time, response rate and success rate.

[0071] Retrieve monitoring indicator data from several business nodes and fit the monitoring indicator data into a curve F(t); solve for the first derivative f(t) of the curve F(t);

[0072] Determine whether there exists a part in the first derivative |f(t)| that is greater than y = n; if yes, mark the abnormal part and generate an early warning notification; otherwise, continue to analyze the monitoring indicator data.

[0073] It is worth noting that analyzing anomalies in monitoring indicator data can also involve comparing the monitoring indicator data with the defined monitoring indicators to determine whether the monitoring indicator data is within the defined monitoring indicator range. If it is, the monitoring indicator data is determined to be normal; otherwise, it is determined that the monitoring indicator data is abnormal. An early warning notification can then be generated, and the anomaly can be investigated and handled.

[0074] Retrieve early warning notifications, identify abnormal monitoring indicator data based on the early warning notifications, and mark the abnormal monitoring indicator data as abnormal data.

[0075] Historical abnormal data is retrieved from the database, and the abnormal data is matched with the historical abnormal data to obtain the similarity between the historical abnormal data and the abnormal data; several historical abnormal data with similarity greater than the similarity threshold are selected as reference data.

[0076] Several parameter data were analyzed to identify several causes of anomalies; based on these causes, log files were investigated and those corresponding to the causes of anomalies were selected.

[0077] The selected log files are analyzed to obtain the corresponding processing methods. The abnormal data is processed according to the processing methods, and the results are verified. The processing process and results are stored in the corresponding database.

[0078] For example, when an anomaly occurs, such as a callback line anomaly, it will first be reflected in the abnormal response of the monitoring platform to requests, such as a significant increase in single-unit throughput and connection waiting number; checking the line traffic graph will reveal a sharp drop in overall traffic.

[0079] The monitoring platform revealed normal requests to the line interface, but investigation based on the called party information provided by the user showed that the requests did not reach the data platform. Checking the data platform logs revealed that the callback 20 had a circuit breaker issue. Alarms triggered by abnormal page access on the monitoring platform revealed that the gateway service was abnormal.

[0080] An anomaly was found in the gateway service logs; the gateway service was restarted; and finally, the business metrics were verified to have returned to normal.

[0081] The working principle of this invention is as follows: This invention acquires business request data and determines the lifecycle of the business request based on the data. The business request data includes initiation data, processing data, and response data. Based on the lifecycle of the business request, the business system is divided into several business nodes. Corresponding monitoring indicators are defined for each business node. A large-screen end-to-end monitoring dashboard platform is constructed to visually display the defined monitoring indicators. The end-to-end monitoring dashboard platform collects real-time operational data from the business system, processes and analyzes the data to obtain real-time monitoring indicator data. The monitoring indicator data of several business nodes is monitored to determine if any faulty nodes exist. If so, an early warning notification is generated; otherwise, the monitoring indicator data is continuously monitored. Faulty nodes are addressed based on the early warning notification.

[0082] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for full-link large-screen global monitoring dashboard based on a monitoring platform observation system, characterized in that, include: Step S1: Obtain business request data and determine the lifecycle of the business request based on the business request data; wherein, the business request data includes initiation data, processing data, and response data; Step S2: Divide the business system into several business nodes according to the lifecycle of business requests; define corresponding monitoring metrics for each business node. Step S3: Build a large-screen end-to-end monitoring dashboard platform to display the defined monitoring metrics in a visual way on the end-to-end monitoring dashboard platform; Step S4: Collect operational data of the business system in real time through the end-to-end monitoring dashboard platform, process and analyze the operational data to obtain real-time monitoring indicator data; Step S5: Detect the monitoring indicator data of several business nodes to determine whether there are any faulty nodes among them; if yes, generate an early warning notification; if no, continue to detect the monitoring indicator data; and handle the faulty nodes according to the early warning notification. The process of processing and analyzing operational data to obtain real-time monitoring indicator data includes: Retrieve operational data from the business system and determine if the data is complete. If it is, retain the corresponding operational data; otherwise, manually supplement the operational data. The operational data includes log data, performance metrics, and transaction trace data. Based on the logical structure of the business system, the running data is divided into corresponding business nodes, and the performance indicators of several business nodes are calculated and marked as monitoring indicator data; among them, the monitoring indicator data includes processing time, response rate and success rate. The determination of whether there is a faulty node among several service nodes includes: Retrieve monitoring indicator data from several business nodes and fit the monitoring indicator data into a curve F(t); solve for the first derivative f(t) of the curve F(t); Determine if there exists a part of the absolute value of the first derivative |f(t)| that is greater than y=n; if yes, mark the abnormal part and generate an early warning notification; otherwise, continue to analyze the monitoring indicator data.

2. The method for full-link large-screen global monitoring dashboard based on a monitoring platform observation system according to claim 1, characterized in that, Determining the lifecycle of a business request based on business request data includes: The user enters a URL in the client to initiate a service request; the client requests the DNS server to resolve the domain name in the URL to obtain the IP address of the target server; based on the IP address of the target server, the client sends the request to the IDC data center. In an IDC (Internet Data Center) server room, the firewall determines whether a request complies with the security policy; if yes, the request is allowed to pass and sent to the core switch; otherwise, the request is not allowed to pass. The core switch forwards requests to the corresponding web application server based on the routing table, and the gateway processes different requests and then sends the requests to several corresponding servers. After processing the request using middleware, the processing results are stored in a database or file system; the processing results are then encapsulated into an HTTP response and returned to the client through gateways, switches, firewalls, and the Internet.

3. The method for full-link large-screen global monitoring dashboard based on a monitoring platform observation system according to claim 2, characterized in that, The process of dividing the business system into several business nodes based on the lifecycle of business requests includes: Retrieve the lifecycle of the business request and extract the data type of the business request data; allocate the business request data of each data type to the corresponding server; design a portal page on each server as the business entry point; the portal page displays the core functions and information of the business type. Extract core business data from business request data of several data types as primary business entry points; analyze the requests under several primary business entry points to obtain all requests generated by the user during operation; identify business data that meets the set criteria from several requests as secondary business data. Determine the data sources and data types required for several secondary business operations; select the storage nodes of requests that meet the requirements of the secondary business operations from the database as the end nodes of the requests.

4. The method for full-link large-screen global monitoring dashboard based on a monitoring platform observation system according to claim 1, characterized in that, The monitoring metrics include: IDC network equipment, infrastructure, basic monitoring, service monitoring, application services, middleware, log monitoring, and business metrics such as processing time, response rate, and success rate.

5. The method for full-link large-screen global monitoring dashboard based on a monitoring platform observation system according to claim 1, characterized in that, The process of handling faulty nodes based on early warning notifications includes: Retrieve early warning notifications, identify abnormal monitoring indicator data based on the early warning notifications, and mark the abnormal monitoring indicator data as abnormal data. Historical abnormal data is retrieved from the database, and the abnormal data is matched with the historical abnormal data to obtain the similarity between the historical abnormal data and the abnormal data; several historical abnormal data with similarity greater than the similarity threshold are selected as reference data. Several parameter data were analyzed to identify several causes of anomalies; based on these causes, log files were investigated and those corresponding to the causes of anomalies were selected. The selected log files are analyzed to obtain the corresponding processing methods. The abnormal data is processed according to the processing methods, and the results are verified. The processing process and results are stored in the corresponding database.

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