System capacity evaluation and analysis platform

Abstract

The invention provides a system capacity evaluation and analysis platform, which comprises a master control unit, a service index acquisition unit, a service datum line calculation unit, an evaluation line formulation unit, a monitoring alarm unit, a middleware access unit and a dynamic telescopic unit, the general control unit is connected with the service index acquisition unit, the service datum line calculation unit, the evaluation line making unit, the monitoring alarm unit, the middleware access unit and the dynamic telescopic unit. By introducing an advanced data analysis method, the precision and reliability of the model are improved, real-time acquisition and analysis of data are realized, timely discovery and early warning of system performance problems are realized, integration of functional modules is optimized, seamless sharing and cooperative work of data are realized, a simple and easy-to-use operation interface is considered, and the use difficulty of a user is reduced.

Description

Technical Field

[0001] The present invention relates to the field of system capacity evaluation, and in particular to a system capacity evaluation and analysis platform. Background Art

[0002] System capacity refers to the maximum processing ability of the system to handle requests when the system is at maximum load or when a certain indicator reaches the maximum acceptable threshold.

[0003] At present, there are some system capacity assessment and analysis platforms on the market, which provide certain functions and services at different levels. The most common ones are real-time monitoring and analysis tools. These tools collect system operation data in real time, perform online analysis and monitoring, and promptly discover and solve problems. Common tools include Nagios, Zabbix, etc.

[0004] Such tools can reflect the current status of the system in real time and promptly warn of potential problems. However, such tools mainly focus on the current status and have limited ability to predict future performance. They also have high requirements for the real-time nature of data collection and processing.

[0005] That is to say, the existing system capacity assessment and analysis platform has solved the problem of system performance assessment to a certain extent, but the existing model assessment tools are often difficult to ensure the accuracy of the model when dealing with complex systems, especially in a dynamically changing environment, resulting in insufficient accuracy; and there are limitations in predicting future performance, resulting in poor real-time performance. Furthermore, although the existing technology is comprehensive in functions, the integration between modules is not high, and the data sharing and collaborative working capabilities are weak, resulting in low integration; at the same time, the operating interfaces of many existing tools are complex, and users need high professional skills to use them effectively, resulting in a poor user experience. Summary of the invention

[0006] The technical problem to be solved by the present invention is to overcome the defects of the prior art, such as insufficient accuracy, poor real-time performance, low integration and poor user experience, and to provide a system capacity evaluation and analysis platform.

[0007] The present invention solves the above technical problems through the following technical solutions:

[0008] The present invention provides a system capacity evaluation and analysis platform, comprising a master control unit, a service indicator acquisition unit, a service baseline calculation unit, an evaluation line formulation unit, a monitoring alarm unit, a middleware access unit and a dynamic scaling unit, wherein the master control unit is respectively connected to the service indicator acquisition unit, the service baseline calculation unit, the evaluation line formulation unit, the monitoring alarm unit, the middleware access unit and the dynamic scaling unit;

[0009] The master control unit is connected to the pulling unit, and the pulling unit is respectively connected to the service indicator acquisition unit, the service baseline calculation unit, the evaluation line formulation unit, the monitoring alarm unit, the middleware access unit and the dynamic scaling unit.

[0010] In this technical solution, by introducing advanced data analysis methods, the accuracy and reliability of the model are improved, real-time data collection and analysis are realized, system performance problems are discovered and warned in time, the integration of various functional modules is optimized, seamless data sharing and collaborative work are achieved, and a simple and easy-to-use operating interface is designed to reduce the difficulty of user use.

[0011] Preferably, the service baseline in the service baseline calculation unit includes a CPU baseline, a disk baseline, a QPS baseline, and a JVM baseline.

[0012] Preferably, the evaluation lines in the evaluation line formulation unit include a CPU evaluation line, a disk evaluation line, a QPS evaluation line, and a JVM evaluation line.

[0013] Preferably, it also includes a service details module 1, a service details module 2, a resource overview module and a display module, and the service details module 1, the service details module 2, the stress test management module and the resource overview module are respectively connected to the main control unit.

[0014] Preferably, the service details module 1 helps administrators and operators to fully understand the status and performance of the service by centrally displaying key information and performance indicators of the service.

[0015] Preferably, the service details module 2 helps administrators and operators to fully understand the status and performance of services by centrally displaying key information and performance indicators of multiple services.

[0016] Preferably, the stress testing management module helps administrators and operators understand the performance of the service under high load by providing analysis of stress test results in a specified time period.

[0017] Preferably, the resource overview module helps users understand the usage of Tencent Cloud resources by providing statistics and analysis of resource usage.

[0018] Preferably, it further comprises a display module, wherein the display module is connected to the main control unit.

[0019] Preferably, the display module is used to provide a simple and easy-to-use operating interface and rich visual charts.

[0020] On the basis of being in accordance with the common sense in the art, the above-mentioned preferred conditions can be arbitrarily combined to obtain the preferred embodiments of the present invention.

[0021] The positive and progressive effects of the present invention are:

[0022] The present invention improves the accuracy and reliability of the model by introducing advanced data analysis methods, realizes real-time data collection and analysis, timely discovers and warns system performance problems, optimizes the integration of various functional modules, realizes seamless data sharing and collaborative work, and designs a simple and easy-to-use operation interface to reduce the difficulty of use for users;

[0023] Through intuitive resource usage statistics and analysis, it helps users quickly understand resource usage, avoid resource waste, ensure reasonable allocation and use of resources, and improve resource management efficiency;

[0024] Provides detailed resource usage indicators and trend analysis, allowing users to make more scientific and reasonable decisions, improve business stability and reliability, and enhance decision support;

[0025] Realize real-time monitoring of resource usage and automatically detect abnormal situations, timely discover and handle potential problems, reduce the risk of system failures and business interruptions, and have the functions of real-time monitoring and abnormality detection;

[0026] Supports statistics and analysis of various resource types, such as APISIX gateway, CVM, ES management, etc., to fully understand all aspects of the system and formulate more comprehensive optimization strategies, with the function of multi-dimensional resource analysis;

[0027] Users can select different time periods for resource usage statistics, such as weekly and monthly, and view resource usage trends according to actual needs, which is convenient for long-term planning and short-term adjustments, with flexible time range selection;

[0028] Provides a simple and easy-to-use operation interface and rich visual charts, which can be easily used by non-professionals, improving the popularity and efficiency of the system, and has a user-friendly interface design;

[0029] Based on resource usage and trend analysis, optimization suggestions are automatically generated to reduce manual intervention, improve optimization efficiency and accuracy, and have the function of automated optimization suggestions. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 The figure is a schematic diagram of the principle of the system capacity evaluation and analysis platform according to an embodiment of the present invention.

[0031] Figure 2 for Figure 1 The overall structural diagram of the system capacity assessment and analysis platform is shown.

[0032] Description of Reference Numerals

[0033] 1. Master control unit;

[0034] 2. Service indicator acquisition unit;

[0035] 3. Service baseline calculation unit;

[0036] 4. Assessment line formulation unit;

[0037] 5. Monitoring and alarm unit;

[0038] 6. Middleware access unit;

[0039] 7. Dynamic telescopic unit;

[0040] 8. Pulling unit;

[0041] 9. Service details module 1;

[0042] 10. Service details module 2;

[0043] 11. Stress testing management module;

[0044] 12. Resource overview module;

[0045] 13. Display module. DETAILED DESCRIPTION

[0046] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples.

[0047] Figure 1 to Figure 2 The structure diagram of the embodiment of the system capacity evaluation and analysis platform of the present invention is shown. The system capacity evaluation and analysis platform comprises a master control unit 1, a service indicator acquisition unit 2, a service baseline calculation unit 3, an evaluation line formulation unit 4, a monitoring alarm unit 5, a middleware access unit 6 and a dynamic scaling unit 7, wherein the master control unit 1 is respectively connected to the service indicator acquisition unit 2, the service baseline calculation unit 3, the evaluation line formulation unit 4, the monitoring alarm unit 5, the middleware access unit 6 and the dynamic scaling unit 7;

[0048] The master control unit 1 is connected to the pulling unit 8, and the pulling unit 8 is respectively connected to the service indicator acquisition unit 2, the service baseline calculation unit 3, the evaluation line formulation unit 4, the monitoring alarm unit 5, the middleware access unit 6 and the dynamic scaling unit 7.

[0049] In this technical solution, by introducing advanced data analysis methods, the accuracy and reliability of the model are improved, real-time data collection and analysis are realized, system performance problems are discovered and warned in time, the integration of various functional modules is optimized, seamless data sharing and collaborative work are achieved, and a simple and easy-to-use operating interface is designed to reduce the difficulty of use for users.

[0050] When used, there are seven stages;

[0051] Phase 1 is to obtain various service indicators;

[0052] Phase 2 is to calculate the service baseline and show the current status of the server;

[0053] Phase 3 is to set different standards and different assessment lines, and provide development reference and expansion suggestions;

[0054] Stage 4 is to make an alarm based on the baseline and assessment line;

[0055] Stage five is the access middleware indicator;

[0056] Stage 6: The baseline and assessment lines are mature and dynamic expansion can be done;

[0057] Phase seven is the dynamic scaling of middleware.

[0058] That is, understand the current status of your own project, assist in anomaly identification, assist in scaling recommendations, understand the middleware used by the service, and automatically scale.

[0059] When the present invention is used, three indicators are mainly involved in the calculation, namely, the proportion of traffic and QPS, the 99line time consumption dimension, and the total project traffic.

[0060] The main ideas when using it are:

[0061] 1. Sort the project traffic from high to low, and extract the traffic proportion and traffic volume of the top 95% of the projects;

[0062] 2. The time consumption interval of each interface in the 95% traffic is subdivided. The distinction is based on the definition of the 99line time consumption interval table, as shown in Table 1.

[0063] Time interval ms Interface time complexity 1-20 1 20-50 2 50-100 3 100-200 4 >200 5

[0064] Table 1

[0065] 3. The interface time complexity coefficient is obtained by multiplying the proportion of each interface by the interface time complexity;

[0066] 4. Add the interface time-consuming complexity coefficients to get the overall time-consuming complexity coefficient of the project;

[0067] 5. The overall time complexity coefficient of the project multiplied by the project traffic level is equal to the number of server nodes. The definition of the project traffic level can be found in the traffic range definition table, as shown in Table 2.

[0068] Flow range Flow level 0-100 1 100-500 2 500-1000 3 1000-3000 4 3000-5000 5 5000-8000 6 8000-5000 7 >15000 8

[0069] Table 2

[0070] The service baseline in the service baseline calculation unit 3 includes a CPU baseline, a disk baseline, a QPS baseline, and a JVM baseline.

[0071] QPS stands for Queries Per Second, the number of queries per second, the number of queries that can be responded to per second, and is a measure of the search traffic received by the information retrieval system in one second;

[0072] QPS is the number of queries a server can respond to per second, that is, the number of requests completed in 1 second. It is a measure of the amount of traffic a specific query server handles within a specified time.

[0073] QPS is a measure of the amount of traffic a specific query server handles within a specified time. On the Internet, the performance of a machine that serves as a domain name system server is often measured by the query rate per second. The number of response requests per second is also the maximum throughput capacity.

[0074] JVM is the abbreviation of Java Virtual Machine, which is a fictional computer, a specification, which is realized by simulating various computer functions on an actual computer.

[0075] It is a specification for computing devices. After the introduction of the Java virtual machine, the Java language does not need to be recompiled when running on different platforms. The Java language compiler only needs to generate target code (bytecode) that runs on the Java virtual machine, and can run on multiple platforms without modification. As long as any platform is equipped with a Java virtual machine for that platform, the bytecode file (.class) can run on that platform.

[0076] The evaluation lines in the evaluation line formulation unit 4 include a CPU evaluation line, a disk evaluation line, a QPS evaluation line, and a JVM evaluation line.

[0077] It also includes a service details module 1 9 , a service details module 2 10 , a resource overview module 12 and a display module 13 . The service details module 1 9 , the service details module 2 10 , the stress test management module 11 and the resource overview module 12 are respectively connected to the main control unit 1 .

[0078] The service details module 9 helps administrators and operators to fully understand the status and performance of the service by centrally displaying the key information and performance indicators of the service.

[0079] The specific functions of the service details module 9 include:

[0080] Real-time monitoring, providing real-time data updates to ensure that users can obtain the latest status of the service in a timely manner;

[0081] Deep insights: Through basic monitoring and instance lists, users can gain in-depth insights into the operation details of the service.

[0082] Resource optimization, through CPU monitoring charts, helps users to reasonably allocate and utilize computing resources;

[0083] Decision support provides detailed service information to support users in making scientific decisions.

[0084] The service details module 10 helps administrators and operators to fully understand the status and performance of services by centrally displaying key information and performance indicators of multiple services.

[0085] The specific functions of the service details module 2 10 include:

[0086] Efficient management, providing a one-stop service management platform, allowing users to centrally monitor and manage multiple services;

[0087] Real-time monitoring, real-time update of service performance data, timely detection and resolution of potential problems;

[0088] Resource optimization, through evaluation suggestions and performance data, helps users to reasonably allocate resources and improve service efficiency;

[0089] Decision support provides detailed service information and evaluation suggestions to support users in making scientific decisions.

[0090] The stress test management module 11 helps administrators and operators understand the performance of services under high load by providing analysis of stress test results in a specified time period.

[0091] The specific functions of the stress testing management module 11 include:

[0092] Performance evaluation, through detailed performance indicators, evaluates the load capacity and stability of the service under stress conditions;

[0093] Problem location: quickly locate performance bottlenecks through abnormal marking, improving troubleshooting efficiency;

[0094] Decision support, providing detailed performance data to support users in making scientific decisions;

[0095] Continuous improvement: by comparing the test results of different batches, we can promote the continuous optimization of service performance.

[0096] The resource overview module 12 helps users understand the usage of Tencent Cloud resources by providing statistics and analysis of resource usage.

[0097] The specific functions of the resource overview module 12 include:

[0098] Resource management: through clear resource classification and quantity statistics, users can effectively manage different types of resources;

[0099] Trend analysis: by selecting a time range and displaying resource usage trends, users can understand the changing patterns of resource usage;

[0100] Problem discovery: Through anomaly detection, users can quickly identify possible problems and improve the efficiency and security of resource utilization.

[0101] It also includes a display module 13 , which is connected to the main control unit 1 .

[0102] The display module 13 is used to provide a simple and easy-to-use operation interface and rich visual charts.

[0103] Figure 1 middle:

[0104] Prometheus is an open source system monitoring and alerting toolkit. Its main features are a multidimensional data model in which time series data are identified by indicator names and key-value pairs; PromQL, a flexible query language, is used to exploit this multidimensionality; it does not rely on distributed storage, and single server nodes are autonomous; time series collection is performed through a pull model over HTTP; push time series are supported through an intermediate gateway; targets are discovered through service discovery or static configuration; and multiple drawing and dashboard support modes.

[0105] Nacos in nacos-server is a cloud-native application supporting tool open sourced by Alibaba. It is mainly used in scenarios such as service discovery, configuration management, and service management. It aims to simplify service governance in microservice architecture. Nacos is particularly suitable for building and managing microservice architecture for modern cloud-native applications.

[0106] Although the specific embodiments of the present invention are described above, it should be understood by those skilled in the art that this is only for illustration and the protection scope of the present invention is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. System capacity assessment and analysis platform, characterized by: The system comprises a master control unit (1), a service indicator acquisition unit (2), a service baseline calculation unit (3), an evaluation line formulation unit (4), a monitoring alarm unit (5), a middleware access unit (6) and a dynamic expansion unit (7), wherein the master control unit (1) is respectively connected to the service indicator acquisition unit (2), the service baseline calculation unit (3), the evaluation line formulation unit (4), the monitoring alarm unit (5), the middleware access unit (6) and the dynamic expansion unit (7); The master control unit (1) is connected to a pulling unit (8), and the pulling unit (8) is respectively connected to a service indicator acquisition unit (2), a service baseline calculation unit (3), an evaluation line formulation unit (4), a monitoring alarm unit (5), a middleware access unit (6), and a dynamic expansion unit (7).

2. The system capacity evaluation and analysis platform according to claim 1, characterized in that: The service baseline in the service baseline calculation unit (3) includes a CPU baseline, a disk baseline, a QPS baseline, and a JVM baseline.

3. The system capacity evaluation and analysis platform according to claim 1, characterized in that: The evaluation lines in the evaluation line formulation unit (4) include a CPU evaluation line, a disk evaluation line, a QPS evaluation line, and a JVM evaluation line.

4. The system capacity evaluation and analysis platform according to claim 1, characterized in that: It also includes a service details module 1 (9), a service details module 2 (10), a resource overview module (12) and a display module (13), wherein the service details module 1 (9), the service details module 2 (10), the stress test management module (11) and the resource overview module (12) are respectively connected to the main control unit (1).

5. The system capacity evaluation and analysis platform according to claim 4, characterized in that: The service details module 1 (9) helps administrators and operators to fully understand the status and performance of the service by centrally displaying the key information and performance indicators of the service.

6. The system capacity evaluation and analysis platform according to claim 4, characterized in that: The service details module 2 (10) helps administrators and operators to fully understand the status and performance of services by centrally displaying key information and performance indicators of multiple services.

7. The system capacity evaluation and analysis platform according to claim 4, characterized in that: The stress test management module (11) helps administrators and operators understand the performance of services under high load by providing analysis of stress test results in a specified time period.

8. The system capacity evaluation and analysis platform according to claim 4, characterized in that: The resource overview module (12) helps users understand the usage of Tencent Cloud resources by providing statistics and analysis of resource usage.

9. The system capacity evaluation and analysis platform according to claim 1, characterized in that: It also includes a display module (13), wherein the display module (13) is connected to the main control unit (1).

10. The system capacity evaluation and analysis platform according to claim 9, characterized in that: The display module (13) is used to provide a simple and easy-to-use operation interface and rich visual charts.

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