Health degree assessment method and device based on load balancing equipment

Abstract

The invention provides a health degree assessment method and device based on load balancing equipment, and relates to the technical field of equipment management. When the method is executed, firstly, hardware layer data, network layer data and application layer data of the load balancing equipment are collected, then, the health degree of the load balancing equipment is calculated according to the hardware layer data, the network layer data and the application layer data, and finally, a health degree report of the load balancing equipment is generated according to the health degree of the load balancing equipment. Thus, data of a hardware layer, a network layer and an application layer of the load balancing equipment are comprehensively collected, information can be obtained from multiple key dimensions such as the physical operation state of the equipment, network communication performance and the operation condition of borne application services, and the health degree is calculated based on the multiple layers of data. The method can comprehensively consider the influence of various factors on the overall health of the equipment, gets rid of the limitation of single-level data evaluation, and improves the accuracy of the health degree evaluation of the load balancing equipment.

Description

Technical Field

[0001] The present application relates to the technical field of equipment management, and in particular to a method and apparatus for evaluating the health of a load balancing device. Background Art

[0002] In today's era of rapid digital business development, various network applications and services place extremely high demands on system stability and reliability. As a key component ensuring the efficient and stable operation of network services, load balancing devices are widely used in data centers, enterprise networks, and other scenarios. By rationally distributing network traffic to multiple servers, they effectively avoid single points of failure and improve overall system availability and processing capacity. However, with the continuous growth of network traffic and the increasing complexity of applications, load balancing devices face increasingly severe operational challenges. Their health directly affects the performance and service quality of the entire network system.

[0003] To ensure stable operation of load balancing devices, timely monitoring of their health is crucial. Currently, monitoring of load balancing devices primarily focuses on collecting and analyzing data at different layers. However, while existing technologies collect data from the hardware, network, and application layers, when calculating the health of load balancing devices, they often simply analyze each layer independently or perform a simple weighted summation, failing to fully consider the inherent connections and interactions between data at different layers. This results in an inability to accurately assess the health of load balancing devices.

[0004] In summary, how to improve the accuracy of load balancing device health assessment is a technical problem that those skilled in the art urgently need to solve. Summary of the Invention

[0005] In view of this, the present application provides a method and apparatus for evaluating the health of a load balancing device, aiming to improve the accuracy of the health evaluation of the load balancing device.

[0006] In a first aspect, the present application provides a method for evaluating the health of a load balancing device, comprising:

[0007] Collect hardware layer data, network layer data, and application layer data of the load balancing device;

[0008] Calculating the health of the load balancing device based on the hardware layer data, the network layer data, and the application layer data;

[0009] Generate a health report of the load balancing device based on the health of the load balancing device.

[0010] Optionally, collecting hardware layer data, network layer data, and application layer data of the load balancing device includes:

[0011] The hardware layer data, the network layer data and the application layer data are collected by configuring a monitoring script on a monitoring node and sending a Simple Network Management Protocol (SNMP) request to the load balancing device.

[0012] Optionally, calculating the health of the load balancing device according to the hardware layer data, the network layer data, and the application layer data includes:

[0013] Calculating a hardware score, a network score, and an application score based on the hardware layer data, the network layer data, and the application layer data;

[0014] The health of the load balancing device is calculated according to the hardware score, the network score, and the application score.

[0015] Optionally, generating a health report of the load balancing device according to the health of the load balancing device includes:

[0016] Continuously obtaining the health of the load balancing device for a period of time;

[0017] The health of the load balancing device for the period of time is arranged in chronological order to generate a health report of the load balancing device.

[0018] Optionally, the hardware layer data includes CPU usage and memory usage.

[0019] Optionally, the network layer data includes the number of concurrent connections and broadband usage.

[0020] Optionally, the application layer data includes packet loss rate and failure rate.

[0021] In a second aspect, the present application provides a health assessment device based on a load balancing device, comprising:

[0022] The collection module is used to collect hardware layer data, network layer data and application layer data of the load balancing device;

[0023] a calculation module, configured to calculate the health of the load balancing device based on the hardware layer data, the network layer data, and the application layer data;

[0024] A generating module is used to generate a health report of the load balancing device according to the health of the load balancing device.

[0025] Optionally, the acquisition module includes:

[0026] The collecting unit is used to collect the hardware layer data, the network layer data and the application layer data by configuring a monitoring script on a monitoring node and sending a Simple Network Management Protocol (SNMP) request to the load balancing device.

[0027] Optionally, the calculation module includes:

[0028] a first calculation unit, configured to calculate a hardware score, a network score, and an application score based on the hardware layer data, the network layer data, and the application layer data;

[0029] A second calculation unit is configured to calculate the health of the load balancing device according to the hardware score, the network score, and the application score.

[0030] Optionally, the generating module includes:

[0031] An acquiring unit, configured to continuously acquire the health of the load balancing device for a period of time;

[0032] The generating unit is configured to arrange the health of the load balancing device for the period of time in a time sequence to generate a health report of the load balancing device.

[0033] Optionally, the hardware layer data includes CPU usage and memory usage.

[0034] Optionally, the network layer data includes the number of concurrent connections and broadband usage.

[0035] Optionally, the application layer data includes packet loss rate and failure rate.

[0036] In a third aspect, an embodiment of the present application provides a computer device comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, it implements the health assessment method based on a load balancing device as described in any one of the implementation methods in the first aspect of the embodiment of the present application.

[0037] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a terminal device, the terminal device executes the health assessment method based on a load balancing device as described in any one of the implementation methods in the first aspect of the embodiment of the present application.

[0038] The present application provides a health assessment method based on a load balancing device. When executing the method, the hardware layer data, network layer data, and application layer data of the load balancing device are first collected. Then, based on the hardware layer data, network layer data, and application layer data, the health of the load balancing device is calculated. Finally, based on the health of the load balancing device, a health report for the load balancing device is generated. In this way, by comprehensively collecting the hardware layer, network layer, and application layer data of the load balancing device, information can be obtained from multiple key dimensions such as the physical operating status of the device, network communication performance, and the operating status of the application services it carries. By calculating the health based on these multi-level data, the impact of various factors on the overall health of the device can be comprehensively considered, breaking away from the limitations of single-level data evaluation, thereby improving the accuracy of the health assessment of the load balancing device. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0040] Figure 1 A flow chart of a load balancing device health assessment method provided in an embodiment of the present application;

[0041] Figure 2 A schematic diagram of the structure of a health assessment device based on a load balancing device provided in an embodiment of the present application;

[0042] Figure 3 A schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The following, in conjunction with the accompanying drawings, provides a clear and complete description of the technical solutions in the embodiments of this application. This application provides a method and apparatus for assessing the health of a load balancing device, which is used in the field of device management technology. The above description is merely illustrative and does not limit the application areas of the method and apparatus provided herein.

[0044] In today's era of rapid digital business development, various network applications and services place extremely high demands on system stability and reliability. As a key component ensuring the efficient and stable operation of network services, load balancing devices are widely used in data centers, enterprise networks, and other scenarios. By rationally distributing network traffic to multiple servers, they effectively avoid single points of failure and improve overall system availability and processing capacity. However, with the continuous growth of network traffic and the increasing complexity of applications, load balancing devices face increasingly severe operational challenges. Their health directly affects the performance and service quality of the entire network system.

[0045] To ensure stable operation of load balancing devices, timely monitoring of their health is crucial. Currently, monitoring of load balancing devices primarily focuses on collecting and analyzing data at different layers. However, while existing technologies collect data from the hardware, network, and application layers, when calculating the health of load balancing devices, they often simply analyze each layer independently or perform a simple weighted summation, failing to fully consider the inherent connections and interactions between data at different layers. This results in an inability to accurately assess the health of load balancing devices.

[0046] After research, the inventors proposed the technical solution of this application. First, the hardware layer data, network layer data, and application layer data of the load balancing device are collected. Then, based on the hardware layer data, network layer data, and application layer data, the health of the load balancing device is calculated. Finally, based on the health of the load balancing device, a health report for the load balancing device is generated. In this way, by comprehensively collecting the hardware layer, network layer, and application layer data of the load balancing device, information can be obtained from multiple key dimensions such as the physical operating status of the device, network communication performance, and the operating status of the application services it carries. Based on these multi-level data, the health can be calculated, and the impact of various factors on the overall health of the device can be comprehensively considered, breaking away from the limitations of single-level data evaluation, thereby improving the accuracy of the load balancing device health evaluation.

[0047] In order to enable those skilled in the art to better understand the present application, the present application is further described in detail below in conjunction with the accompanying drawings and specific embodiments. Obviously, the embodiments described are only a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative work are within the scope of protection of the present application. It should be noted that, for ease of description, only the parts related to the relevant invention are shown in the accompanying drawings. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0048] See also Figure 1 , Figure 1A flow chart of a load balancing device health assessment method provided in an embodiment of the present application includes:

[0049] S101: Collecting hardware layer data, network layer data, and application layer data of a load balancing device.

[0050] First, you can configure a monitoring script on the monitoring node and send an SNMP request with corresponding parameters to the device to obtain the hardware layer data, network layer data, and application layer data of the load balancing device, and store it in the monitoring platform so that real-time data can be read on the monitoring platform.

[0051] Among them, SNMP (Simple Network Management Protocol) is a simple network management protocol.

[0052] In the embodiments of the present application, hardware layer data includes, but is not limited to, CPU usage and memory usage. Network layer data includes, but is not limited to, concurrent connections and bandwidth usage. Application layer data includes, but is not limited to, packet loss rate and failure rate.

[0053] After collecting the hardware layer data, network layer data and application layer data of the load balancing device, all monitoring data of the previous day can be read from the monitoring platform through a scheduled task every day, and the data can be sorted and stored in the file server for backup.

[0054] S102: Calculate the health of the load balancing device based on the hardware layer data, the network layer data, and the application layer data.

[0055] The health of the load balancing device is calculated as follows:

[0056] ;

[0057] Among them, the weights are determined by those skilled in the art based on current production needs.

[0058] The hardware score is calculated based on the CPU and memory usage. The specific calculation method is as follows:

[0059] ;

[0060] The CPU used is the current CPU usage, CPU safe The CPU usage safety threshold is set to 80%. used is the current memory usage, Memory safe The memory usage safety threshold is fixed at 80%. The steepness is controlled by k, which is fixed at 5.

[0061] The CPU and memory scores are calculated using a sigmoid function model because CPU and memory usage have a nonlinear impact on the system. When CPU and memory usage are below the threshold, they have little impact on system performance. When usage exceeds the threshold, system performance degrades rapidly.

[0062] The network score is calculated based on throughput usage, as follows:

[0063] ;

[0064] Throughput used is the current throughput utilization rate, Throughput safe The CPU throughput usage safety threshold is set to 80%.

[0065] The throughput utilization is calculated by comparing the throughput utilization rate to the safety threshold.

[0066] The application score is calculated based on the number of concurrent connections. The specific calculation method is as follows:

[0067] A fixed-length data window is continuously maintained, and only the data within the window is calculated as the current evaluation benchmark. The currently used window length is 30 minutes, the step length is 1 minute, and each window has 30 data points. The window mean μ and window standard deviation σ are calculated as follows:

[0068] ;

[0069] ;

[0070] Connection point The number of concurrent connections for 1 data point, n is 30. Connection safety threshold Connection safe is calculated as follows:

[0071] ;

[0072] Among them, k is 3, corresponding to a confidence level of 99.7%, and the application score is as follows:

[0073] ;

[0074] Connection now is the current number of concurrent connections, μ is the moving average of the current window; the final application score is the lowest score calculated from the two connection number safety thresholds.

[0075] S103: Generate a health report of the load balancing device according to the health of the load balancing device.

[0076] Reports can be generated based on time, with the highest and average values ​​of all load balancing monitoring data in the corresponding time interval written into a table for horizontal comparison. Monitoring data indicators within a period of time can also be retrieved based on the name of the load balancing device for vertical comparison. Data with abnormal performance and capacity can also be filtered out, marked in the table, and emailed to the administrator for review.

[0077] In the embodiment provided by the present application, the hardware layer data, network layer data and application layer data of the load balancing device are first collected, and then the health of the load balancing device is calculated based on the hardware layer data, network layer data and application layer data. Finally, a health report of the load balancing device is generated based on the health of the load balancing device. In this way, by comprehensively collecting the hardware layer, network layer and application layer data of the load balancing device, information can be obtained from multiple key dimensions such as the physical operating status of the device, network communication performance and the operating status of the application services it carries. The health is calculated based on these multi-level data, which can comprehensively consider the impact of various factors on the overall health of the device, get rid of the limitations of single-level data evaluation, and thus improve the accuracy of the load balancing device health evaluation.

[0078] The above are some specific implementations of the load balancing device health assessment method provided in the embodiments of the present application. Based on this, the present application also provides a corresponding device. The device provided in the embodiments of the present application will be introduced from the perspective of functional modularization.

[0079] See also Figure 2 , Figure 2 This is a schematic diagram of the structure of a load balancing device-based health assessment device provided in an embodiment of the present application. The load balancing device-based health assessment device 200 includes:

[0080] The collection module 210 is used to collect hardware layer data, network layer data and application layer data of the load balancing device;

[0081] A calculation module 220, configured to calculate the health of the load balancing device based on the hardware layer data, the network layer data, and the application layer data;

[0082] The generating module 230 is configured to generate a health report of the load balancing device according to the health of the load balancing device.

[0083] Optionally, the acquisition module 210 includes:

[0084] The collecting unit is used to collect the hardware layer data, the network layer data and the application layer data by configuring a monitoring script on a monitoring node and sending a Simple Network Management Protocol (SNMP) request to the load balancing device.

[0085] Optionally, the calculation module 220 includes:

[0086] a first calculation unit, configured to calculate a hardware score, a network score, and an application score based on the hardware layer data, the network layer data, and the application layer data;

[0087] A second calculation unit is configured to calculate the health of the load balancing device according to the hardware score, the network score, and the application score.

[0088] Optionally, the generating module 230 includes:

[0089] An acquiring unit, configured to continuously acquire the health of the load balancing device for a period of time;

[0090] The generating unit is configured to arrange the health of the load balancing device for the period of time in a time sequence to generate a health report of the load balancing device.

[0091] Optionally, the hardware layer data includes CPU usage and memory usage.

[0092] Optionally, the network layer data includes the number of concurrent connections and broadband usage.

[0093] Optionally, the application layer data includes packet loss rate and failure rate.

[0094] The embodiments of the present application also provide corresponding devices and computer storage media for implementing the solutions provided by the embodiments of the present application.

[0095] like Figure 3 As shown, computer device 01 is a general-purpose computing device. Components of computer device 01 may include, but are not limited to, one or more processors or processor units 03, system memory 08, and bus 04 connecting various system components (including system memory 08 and processor unit 03).

[0096] Bus 04 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures. Examples of these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0097] The computer device 01 typically includes a variety of computer system readable media, which can be any available media that can be accessed by the computer device 01, including volatile and non-volatile media, removable and non-removable media.

[0098] System memory 08 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 09 and / or cache memory 10. Computer device 01 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 11 may be used to read and write non-removable, non-volatile magnetic media ( Figure 3 Not shown, often called a "hard drive"). Although Figure 3 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk"), and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to the bus 04 via one or more data medium interfaces. The system memory 08 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of various embodiments of the present invention.

[0099] A program / utility 12 having a set (at least one) of program modules 13 may be stored, for example, in system memory 08. Such program modules 13 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may include an implementation of a network environment. Program modules 13 generally perform the functions and / or methods of the embodiments described herein.

[0100] The computer device 01 may also communicate with one or more external devices 02 (e.g., a keyboard, a pointing device, a display 07, etc.), one or more devices that enable a user to interact with the computer device 01, and / or any device that enables the computer device 01 to communicate with one or more other computing devices (e.g., a network card, a modem, etc.). Such communication may be performed via an input / output (I / O) interface 06. Furthermore, the computer device 01 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 05. Figure 3 As shown, the network adapter 05 communicates with other modules of the computer device 01 via the bus 04. Figure 3 Not shown, other hardware and / or software modules may be used in conjunction with the computer device 01, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0101] The processor unit 03 executes various functional applications and data processing by running programs stored in the system memory 08, such as implementing a health assessment method based on a load balancing device provided in an embodiment of the present application.

[0102] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

[0103] Through the description of the above embodiments, it can be seen that those skilled in the art can clearly understand that all or part of the steps in the above-mentioned embodiment methods can be implemented by means of software plus a general hardware platform. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product. The computer software product can be stored in a storage medium, such as a read-only memory (ROM) / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network communication device such as a router) to execute the methods described in various embodiments or certain parts of the embodiments of the present application.

[0104] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiment. Some or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment. Those of ordinary skill in the art can understand and implement it without paying any creative work.

[0105] The above description is merely an exemplary embodiment of the present application and is not intended to limit the scope of protection of the present application.

Claims

1. A health assessment method based on a load balancing device, characterized in that: include: Collect hardware layer data, network layer data, and application layer data of the load balancing device; Calculating the health of the load balancing device based on the hardware layer data, the network layer data, and the application layer data; Generate a health report of the load balancing device based on the health of the load balancing device.

2. The method according to claim 1, characterized in that The collection of hardware layer data, network layer data, and application layer data of the load balancing device includes: The hardware layer data, the network layer data and the application layer data are collected by configuring a monitoring script on a monitoring node and sending a Simple Network Management Protocol (SNMP) request to the load balancing device.

3. The method according to claim 1, characterized in that The calculating the health of the load balancing device according to the hardware layer data, the network layer data, and the application layer data includes: Calculating a hardware score, a network score, and an application score based on the hardware layer data, the network layer data, and the application layer data; The health of the load balancing device is calculated according to the hardware score, the network score, and the application score.

4. The method according to claim 1, wherein Generating a health report of the load balancing device according to the health of the load balancing device includes: Continuously obtaining the health of the load balancing device for a period of time; The health of the load balancing device for the period of time is arranged in chronological order to generate a health report of the load balancing device.

5. The method according to claim 1, wherein The hardware layer data includes CPU usage and memory usage.

6. The method according to claim 1, characterized in that The network layer data includes the number of concurrent connections and the bandwidth usage rate.

7. The method according to claim 1, characterized in that The application layer data includes packet loss rate and failure rate.

8. A health assessment device based on a load balancing device, characterized in that: include: The collection module is used to collect hardware layer data, network layer data and application layer data of the load balancing device; a calculation module, configured to calculate the health of the load balancing device based on the hardware layer data, the network layer data, and the application layer data; A generating module is used to generate a health report of the load balancing device according to the health of the load balancing device.

9. A computer device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the health assessment method based on a load balancing device as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed on the terminal device, the terminal device executes the health assessment method based on the load balancing device according to any one of claims 1 to 7.

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