Health state determination method and device and storage medium

Abstract

The invention provides a health state determination method and device and a storage medium, relates to the technical field of computers, and can determine the health state of a data center. The method comprises the following steps: acquiring performance indexes of a plurality of devices in a data center in a preset period; determining an equipment state of each piece of equipment according to the performance index of each piece of equipment in the plurality of pieces of equipment; the equipment state comprises normal or abnormal; determining the health state of the data center according to the proportion of the equipment with the normal equipment state in the data center; the health state comprises normal or abnormal. The method is used for determining the health state of the data center.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a health status determination method, device and storage medium. Background Art

[0002] Data centers are generally equipped with a large number of network resources, which can carry a large number of network services and manage massive amounts of business data. Therefore, data centers need to have high reliability to improve network stability.

[0003] Currently, the health status of a data center is mainly determined by staff performing health checks on each device in the data center. However, this method is inefficient and prone to misjudgment. Summary of the invention

[0004] The present application provides a health status determination method, device and storage medium, which can efficiently and accurately determine the health status of a data center.

[0005] In order to achieve the above objectives, this application adopts the following technical solutions:

[0006] In a first aspect, the present application provides a method for determining a health status, the method comprising: obtaining performance indicators of multiple devices in a data center within a preset period; determining a device status of each device based on the performance indicators of each of the multiple devices; the device status includes normal or abnormal; determining a health status of the data center based on the proportion of devices with normal device status in the data center; the health status includes normal or abnormal.

[0007] In one possible manner, the performance indicators include multiple types of performance indicators; the device status of each device is determined based on the performance indicators of each device in the multiple devices, including: performing the following target operation on each device to determine the device status of each device; the target operation includes: classifying the values ​​of the performance indicators of the target device according to the type, and determining multiple indicator sets of the target device; wherein the target device is any device in the multiple devices, and an indicator set includes the value of one type of performance indicator; performing anomaly detection processing on the values ​​in each indicator set to obtain the normal performance indicator probability of each indicator set; multiplying the normal performance indicator probability of each indicator set of the target device to obtain the health value of the target device; comparing the health value of the target device with a first threshold to obtain the device status of the target device.

[0008] In one possible method, before classifying the values ​​of the performance indicators of the target device according to the type and determining the multiple indicator sets of the target device, it also includes: normalizing the values ​​of the multiple types of performance indicators of the target device to obtain the values ​​of the processed performance indicators; classifying the values ​​of the performance indicators of the target device according to the type and determining the multiple indicator sets of the target device, including: classifying the values ​​of the processed performance indicators of the target device according to the type and determining the multiple indicator sets of the target device.

[0009] In one possible approach, the health status of the data center is determined based on the proportion of devices in normal equipment status in the data center, including: obtaining the proportion of devices in normal equipment status in the data center based on the equipment status of each device; and comparing the proportion of devices in normal equipment status in the data center with a second threshold to obtain the health status of the data center.

[0010] In one possible approach, anomaly detection processing is performed on the values ​​in each indicator set to obtain the normal probability of each performance indicator in the indicator set, including: calculating the mean and variance of each indicator set; processing the indicator set, mean and variance according to the normal distribution method to obtain the normal performance indicator probability of each performance indicator in the indicator set.

[0011] In one possible manner, the performance indicator includes one or more of the following: device port disconnection rate, device port packet loss rate, device port error packet rate, device central processing unit CPU utilization rate, device port throughput rate, and device port utilization rate.

[0012] In a second aspect, the present application provides a health status determination device, which includes: an acquisition unit and a determination unit; the acquisition unit is used to acquire performance indicators of multiple devices in a data center within a preset period; the determination unit is used to determine the device status of each device based on the performance indicators of each device in the multiple devices; the determination unit is also used to determine the health status of the data center based on the proportion of devices with normal device status in the data center.

[0013] In one possible manner, the determination unit is specifically used to: perform the following target operations on each device to determine the device status of each device; the target operations include: classifying the values ​​of the performance indicators of the target device according to the type, and determining multiple indicator sets of the target device; wherein the target device is any one of the multiple devices, and an indicator set includes the value of a type of performance indicator; performing anomaly detection processing on the values ​​in each indicator set to obtain the normal performance indicator probability of each indicator set; multiplying the normal performance indicator probability of each indicator set of the target device to obtain the health value of the target device; comparing the health value of the target device with a first threshold to obtain the device status of the target device.

[0014] In one possible manner, a determination unit is specifically used to: normalize the values ​​of multiple types of performance indicators of a target device to obtain values ​​of processed performance indicators; classify the values ​​of the performance indicators of the target device according to the types of performance indicators to determine multiple indicator sets for the target device, including: classify the values ​​of the processed performance indicators of the target device according to the types to determine multiple indicator sets for the target device.

[0015] In one possible manner, the determination unit is specifically used to: obtain the proportion of devices with normal device status in the data center according to the device status of each device; compare the proportion of devices with normal device status in the data center with a second threshold to obtain the health status of the data center.

[0016] In one possible embodiment, the device also includes: a processing unit; the processing unit is used to: calculate the mean and variance of each indicator set; process the indicator set, mean and variance according to the normal distribution method to obtain the normal performance indicator probability of each performance indicator in the indicator set.

[0017] In a third aspect, the present application provides a health status determination device, which includes: a processor and a communication interface; the communication interface and the processor are coupled, and the processor is used to run a computer program or instructions to implement the health status determination method described in the first aspect and any possible implementation method of the first aspect.

[0018] In a fourth aspect, the present application provides a computer-readable storage medium, which stores instructions. When the instructions are executed on a terminal, the terminal executes the health status determination method described in the first aspect and any possible implementation of the first aspect.

[0019] In a fifth aspect, an embodiment of the present application provides a computer program product comprising instructions. When the computer program product is run on a health status determination device, the health status determination device executes the health status determination method as described in the first aspect and any possible implementation of the first aspect.

[0020] In a sixth aspect, an embodiment of the present application provides a chip, the chip including a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run a computer program or instructions to implement a health status determination method as described in the first aspect and any possible implementation method of the first aspect.

[0021] Specifically, the chip provided in the embodiment of the present application also includes a memory for storing computer programs or instructions.

[0022] In this application, the name of the above-mentioned health status determination device does not limit the device or functional module itself. In actual implementation, these devices or functional modules may appear with other names. As long as the functions of each device or functional module are similar to those of this application, they belong to the scope of the claims of this application and their equivalent technologies.

[0023] These and other aspects of the present application will become more apparent from the following description.

[0024] Based on any of the above aspects, the technical solution provided by the present application brings at least the following beneficial effects: the performance indicators of multiple devices in the data center within a preset period can be obtained, and based on the performance indicators of each of the multiple devices, it is determined whether the device status of each device in the data center is normal or abnormal, so as to further determine the health status of the data center based on the proportion of devices with normal device status in the data center.

[0025] Compared with the method of determining the health status of the data center by having staff conduct health checks on each device in the data center, the health status determination device in this application can obtain and process the performance indicators of multiple devices within a preset period to determine the health status of the data center, which can avoid the low efficiency and easy misjudgment caused by manual inspection. Therefore, the application can efficiently and accurately determine the health status of the data center. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A structural diagram of a health status determination system provided in an embodiment of the present application;

[0027] Figure 2 A structural diagram of another health status determination system provided in an embodiment of the present application;

[0028] Figure 3 A schematic diagram of the hardware structure of a health status determination device provided in an embodiment of the present application;

[0029] Figure 4 A flowchart of a health status determination method provided in an embodiment of the present application;

[0030] Figure 5 A flowchart of another health status determination method provided in an embodiment of the present application;

[0031] Figure 6 A schematic diagram of the structure of another health status determination device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0032] The health status determination method and device provided in the embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0033] The term "and / or" in this article is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone.

[0034] The terms "first" and "second" and the like in the specification and drawings of this application are used to distinguish different objects, or to distinguish different processing of the same object, rather than to describe a specific order of objects.

[0035] In addition, the terms "including" and "having" and any variations thereof mentioned in the description of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but may optionally include other steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices.

[0036] It should be noted that, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0037] In order to facilitate understanding of the technical solution of this application, the technical terms involved in this application are introduced below:

[0038] 1. Device port disconnection rate.

[0039] The device port disconnection rate refers to the frequency of abnormal disconnection of the network port on the device within a certain period of time. The device port disconnection rate can reflect the stability and reliability of the device.

[0040] 2. Packet loss rate of device ports.

[0041] The device port packet loss rate refers to the proportion of network ports on a device that cannot normally receive or forward data packets during data transmission. The device port packet loss rate can reflect the performance and reliability of the device.

[0042] 3. Device port error packet rate.

[0043] The device port error packet rate refers to the ratio of the number of data packets with errors in the device's network port transmission process to the total transmitted data within a certain period of time. The device port error packet rate can reflect the stability and transmission quality of the device.

[0044] 4. Central Processing Unit (CPU) utilization of the device.

[0045] The CPU utilization of a device refers to the ratio of the working time of the device's CPU to the total working time within a certain period of time. The CPU utilization of a device can reflect the CPU load and utilization efficiency.

[0046] 5. Device port throughput.

[0047] Device port throughput refers to the amount of data transmitted through the network port on the device within a certain period of time. The device port throughput can reflect the data processing capability and network transmission capability of the device.

[0048] 6. Device port utilization.

[0049] Device port utilization refers to the ratio of the working time of the network port on the device to the total working time within a certain period of time. The device port throughput can reflect the load and utilization efficiency of the device port.

[0050] 7. Normal distribution method.

[0051] The normal distribution method is a statistical method used to fit and predict data given a set of data.

[0052] The above is an introduction to the technical terms involved in this application.

[0053] With the rapid development of network technology, the amount of data processed by the Internet is increasing day by day. As the supporting foundation of the Internet, data centers are generally equipped with a large number of network resources, which can carry a large number of network services and manage massive business data. As the number of network devices in data centers continues to increase, their complexity and scale also increase. Therefore, data centers need to have high reliability to improve the stability of the network.

[0054] Currently, the health of a data center is mainly determined by staff performing health checks on each device in the data center. However, this method is inefficient and prone to misjudgment.

[0055] In response to the defects of the above-mentioned prior art, the method for determining the health status of a data center provided in the present application can obtain the performance indicators of multiple devices in the data center within a preset period, and determine whether the device status of each device in the data center is normal or abnormal based on the performance indicators of each of the multiple devices, so as to further determine the health status of the data center based on the proportion of devices with normal device status in the data center.

[0056] Compared with the method of determining the health status of the data center by having staff conduct health checks on each device in the data center, the health status determination device in this application can obtain and process the performance indicators of multiple devices within a preset period to determine the health status of the data center, which can avoid the low efficiency and easy misjudgment caused by manual inspection. Therefore, the application can efficiently and accurately determine the health status of the data center.

[0057] For example, Figure 1 , which is a schematic diagram of a health status determination system 100 provided in an embodiment of the present application. The health status determination system 100 may include a health status determination device 101 and a performance indicator collection device 102. A communication connection may be established between the health status determination device 101 and the performance indicator collection device 102.

[0058] In practical applications, the health status determination device 101 may be communicatively connected with one or more performance indicator collection devices 102 .

[0059] For ease of understanding, this application is described by taking a health status determination device 101 and a performance indicator collection device 102 as an example.

[0060] Optional, Figure 1 The health status determination device 101 and the performance index collection device 102 may be functional modules integrated into the same device, or may be two devices independently provided. This application does not impose any limitation on this.

[0061] It is easy to understand that when the health status determination device 101 and the performance indicator collection device 102 are functional modules integrated in the same device, the communication method between the health status determination device 101 and the performance indicator collection device 102 is the communication between the internal modules of the device. In this case, the communication process between the two is the same as "the communication process between the health status determination device 101 and the performance indicator collection device 102 when they are independently set".

[0062] For ease of understanding, the present application is mainly explained by taking the example that the health status determination device 101 and the performance indicator collection device 102 are independently configured.

[0063] Figure 1 The health status determination device 101 in the data center may be configured with an anomaly detection algorithm, a first threshold, and a second threshold. The health status determination device 101 may receive the performance indicators of the equipment in the data center sent by the performance indicator collection device 102, and determine the health status of the data center based on the configured anomaly detection algorithm, the first threshold, and the second threshold.

[0064] Figure 1The performance indicator collection device 102 can be used to collect performance indicators of devices in the data center, and send the collected performance indicators of the devices in the data center to the health status determination device 101.

[0065] Optionally, Figure 1 The health status determination device 101 and the performance indicator collection device 102 may be a terminal, a server, or other types of electronic devices. Figure 1 What is shown in the figure is only an example of the equipment form of the health status determination device 101 and the performance indicator collection device 102, and does not constitute a limitation thereto.

[0066] When the health status determination device 101 and the performance indicator collection device 102 are terminals, the terminal can be a device that provides voice and / or data connectivity to a user, a handheld device with a wireless connection function, or other processing devices connected to a wireless modem. The terminal can communicate with one or more core networks via a radio access network (RAN). The terminal can be a mobile terminal, such as a computer with a mobile terminal, or a portable, pocket-sized, handheld, or computer-built-in mobile device that exchanges language and / or data with a radio access network, such as a mobile phone, a tablet computer, a laptop computer, a netbook, or a personal digital assistant (PDA). The embodiments of the present application do not impose any restrictions on this.

[0067] When the health status determination device 101 and the performance index collection device 102 are servers, the server may be a single server, or a server cluster composed of multiple servers. In some implementations, the server cluster may also be a distributed cluster. This application embodiment does not impose any restrictions on this.

[0068] In one possible embodiment, combining Figure 1 ,like Figure 2 As shown, it is a schematic diagram of the architecture of another health status determination system provided by the present application. The health status determination system 200 may include a control center 201, a health status determination device 202, and a node sensor 203. A communication connection may be established between the control center 201 and the health status determination device 202, and the health status determination device 202 may establish communication connections with multiple node sensors 203 respectively.

[0069] In practical applications, there may be multiple health status determination devices 202. The control center 201 may also be connected to communicate with multiple health status determination devices 202 respectively.

[0070] For ease of understanding, the present application takes the communication connection between a control center 201 and a health status determination device 202 as an example for explanation.

[0071] Figure 2 The node sensor 203 in the data center can collect performance indicators such as the device port offline rate, device port packet loss rate, device port error packet rate, device CPU utilization, device port throughput and device port utilization of the devices in the data center, and upload the collected performance indicators to the health status determination device 202. The health status determination device 202 can periodically send acquisition instructions to the node sensor 203. The node sensor 203 can receive the acquisition instruction sent by the control center 201, and in response to the acquisition instruction, send the collected performance indicators to the health status determination device 202. The health status determination device 202 can process the acquired performance indicators to obtain the health status of the data center, and upload the health status of the data center to the control center 201.

[0072] like Figure 3 , which is a hardware structure diagram of a health status determination device provided in an embodiment of the present application. The health status determination device includes a processor 31, a memory 32, a communication interface 33, and a bus 34. The processor 31, the memory 32, and the communication interface 33 can be connected via a bus 34.

[0073] The processor 31 is the control center of the health status determination device, which can be a processor or a general term for multiple processing elements. For example, the processor 31 can be a general-purpose central processing unit (CPU) or other general-purpose processors. Among them, the general-purpose processor can be a microprocessor or any conventional processor.

[0074] As an embodiment, the processor 31 may include one or more CPUs, such as Figure 3 CPU 0 and CPU 1 are shown in .

[0075] The memory 32 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0076] In a possible implementation, the memory 32 may exist independently of the processor 31, and the memory 32 may be connected to the processor 31 via a bus 34 for storing instructions or program codes. When the processor 31 calls and executes the instructions or program codes stored in the memory 32, the health status determination method provided in the following embodiments of the present application can be implemented.

[0077] In another possible implementation, the memory 32 may also be integrated with the processor 31 .

[0078] The communication interface 33 is used to connect the health status determination device to other devices through a communication network, and the communication network may be Ethernet, wireless access network, wireless local area network (WLAN), etc. The communication interface 33 may include a receiving unit for receiving data and a sending unit for sending data.

[0079] The bus 34 may be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 2 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0080] It should be pointed out that Figure 3 The structure shown in the figure does not constitute a limitation on the health status determination device. Figure 3In addition to the components shown, the health status determination device may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0081] like Figure 4 FIG. 1 is a flow chart of a method for determining a health status provided in an embodiment of the present application. The method for determining a health status can be applied to Figure 1 The health status determination system 100 is shown. The health status determination method includes: S401-S403.

[0082] S401. A health status determination device obtains performance indicators of multiple devices in a data center within a preset period.

[0083] In one possible manner, the performance indicator may include one or more of the following: device port offline rate, device port packet loss rate, device port error packet rate, device CPU utilization rate, device port throughput rate, and device port utilization rate.

[0084] Optionally, the preset period can be determined according to actual needs. For example, the preset period can be set to 1 hour or 15 minutes. This application does not make specific restrictions on this.

[0085] In one possible approach, a data center may include multiple devices. Each device may be used to provide computing resources and storage resources, etc. Figure 1 The health status determination system may include multiple performance indicator collection devices. A performance indicator collection device may collect performance indicators of some equipment in the data center in real time or periodically. The health status determination device may periodically obtain performance indicators collected by multiple performance indicator collection devices.

[0086] S402: The health status determining device determines the device status of each device according to the performance index of each device among the multiple devices.

[0087] The device status includes normal or abnormal.

[0088] In one possible manner, after obtaining performance indicators of multiple devices in the data center within a preset period, the health status determination device can process the performance indicators of multiple devices in the data center within the preset period to determine the device status of each device in the data center.

[0089] Optionally, the health status determination device processes performance indicators of multiple devices in the data center within a preset period to determine the device status of each device in the data center, including but not limited to the following two methods.

[0090] (1) The health status determination device can classify the values ​​of the performance indicators of the target device according to the type of performance indicators, divide the values ​​of the performance indicators of the same type into the same indicator set, and determine multiple indicator sets of the target device. The health status determination device can perform abnormality detection processing on the values ​​in each indicator set to obtain the normal performance indicator probability of each indicator set. The health status determination device can multiply the normal performance indicator probability of each indicator set of the target device to obtain the health value of the target device, and further compare the health value of the target device with the first threshold to obtain the device status of the target device. In addition, the specific implementation method of this method can refer to S501-S504 below.

[0091] (2) The health status determination device can classify the values ​​of the performance indicators of the target device according to the type of performance indicators, divide the values ​​of the performance indicators of the same type into the same indicator set, and determine multiple indicator sets of the target device. The health status determination device can perform anomaly detection processing on the values ​​in each indicator set to obtain the normal performance indicator probability of each indicator set. The health status determination device can calculate the average value of the normal performance indicator probabilities of multiple performance indicators of the target device to obtain the health value of the target device, and further compare the health value of the target device with the first threshold to obtain the device state of the target device.

[0092] Optionally, the first threshold value may be set according to actual needs. For example, when the health value of the target device is determined by multiplication, the first threshold value may be set to 0.7. When the health value of the target device is determined by averaging the probabilities of normal performance indicators of multiple performance indicators, the first threshold value may be set to 0.6. This application does not impose specific restrictions on this.

[0093] S403: The health status determining device determines the health status of the data center according to the proportion of devices in normal status in the data center.

[0094] The health status of a data center includes normal or abnormal.

[0095] Optionally, the health status determining device determines the health status of the data center according to the proportion of devices in normal device status in the data center, including but not limited to the following two methods.

[0096] (1) The health status determination device can count the number of devices in the data center with normal status and the total number of devices in the data center, and determine the ratio of the number of normal devices to the total number of devices as the proportion of devices in the data center with normal status.

[0097] (2) The health status determination device can count the number of devices in the data center with abnormal equipment status and the total number of devices in the data center, and determine the ratio of the number of abnormal devices to the total number of devices as the proportion of devices with abnormal equipment status in the data center, so as to further calculate and determine the proportion of devices in the data center with normal equipment status.

[0098] Based on this, the health status determination device may compare the proportion of devices in the data center with normal device status with the second threshold value to obtain the health status of the data center.

[0099] In one possible manner, if the proportion of devices in the data center that are in normal state is greater than or equal to the second threshold, it can indicate that the data center has high reliability and high stability when carrying network services. In this case, the health status determination device can determine the health status of the data center as normal.

[0100] Alternatively, if the proportion of devices in normal status in the data center is less than the second threshold, it may indicate that the data center has low reliability and stability when carrying network services, and the health status determination device may determine the health status of the data center as abnormal.

[0101] Optionally, the second threshold value may be set according to actual needs. For example, the first threshold value may be set to 0.8 or 0.9. This application does not impose any specific restrictions on this.

[0102] For example, assume that there are five devices in the data center, namely, device 1, device 2, device 3, device 4, and device 5, and the second threshold is 0.8. Among them, the device status of device 1, device 2, device 3, and device 4 is normal, and the device status of device 5 is abnormal. At this time, the proportion of devices in the data center with normal device status is 0.8, which is equal to the second threshold, and the health status of the data center can be determined to be normal.

[0103] In one possible manner, after determining the health status of the data center according to the proportion of devices in normal status in the data center, the health status determination device may also send the health status of the data center to a preset terminal or a preset data upload address.

[0104] Based on the above technical solution, the method for determining the health status of a data center provided in the present application can obtain the performance indicators of multiple devices in the data center within a preset period, and determine whether the device status of each device in the data center is normal or abnormal based on the performance indicators of each of the multiple devices, so as to further determine the health status of the data center based on the proportion of devices with normal device status in the data center.

[0105] Compared with the method of determining the health status of the data center by having staff conduct health checks on each device in the data center, the health status determination device in this application can obtain and process the performance indicators of multiple devices within a preset period to determine the health status of the data center, which can avoid the low efficiency and easy misjudgment caused by manual inspection. Therefore, the application can efficiently and accurately determine the health status of the data center.

[0106] In one embodiment, the following target operations are performed on each device to determine the device status of each device, for example: Figure 5 As shown, the target operation includes: S501-S504.

[0107] S501. The health status determining device classifies the values ​​of performance indicators of the target device according to the type, and determines a plurality of indicator sets of the target device.

[0108] The target device may be any device among the multiple devices. An indicator set may include the value of a type of performance indicator.

[0109] Exemplarily, it is assumed that the target device includes three types of performance indicators, namely, device port drop rate, device port packet loss rate, and device port error packet rate. The health status determination device classifies the values ​​of the three types of performance indicators of the target device, divides the device port drop rate of the target device into an indicator set corresponding to the device port drop rate, divides the device port packet loss rate of the target device into an indicator set corresponding to the device port packet loss rate, divides the device port error packet rate of the target device into an indicator set corresponding to the device port error packet rate, and determines the three indicator sets corresponding to the performance indicators of the target device.

[0110] In one possible approach, before classifying the values ​​of performance indicators of the target device according to type and determining multiple indicator sets of the target device, the health status determination device may normalize the values ​​of multiple types of performance indicators of the target device to obtain processed performance indicator values.

[0111] Based on this, the health status determination device can classify the values ​​of the performance indicators of the target device after processing according to the type, and determine multiple indicator sets of the target device.

[0112] S502: The health status determination device performs anomaly detection processing on the values ​​in each indicator set to obtain the normal performance indicator probability of each indicator set.

[0113] In one possible manner, the health status determination device may calculate the mean and variance of each indicator set. The health status determination device may process the indicator set, mean and variance according to the normal distribution method to obtain the normal performance indicator probability of each performance indicator in the indicator set.

[0114] Exemplarily, in combination with the example in S501, the health status determination device can perform abnormality detection processing on the values ​​in each of the three indicator sets, calculate the mean and variance of each indicator set respectively, and then process the three indicator sets, the mean and the variance of the indicator set according to the normal distribution method, and obtain the normal performance indicator probabilities of each of the three indicator sets as 0.9, 0.8 and 0.7 respectively.

[0115] Optionally, the anomaly detection algorithm for performing anomaly detection processing on the values ​​in each indicator set is not limited to the normal distribution method provided in the present application, and can also be set according to actual needs. The present application does not make any specific restrictions on this.

[0116] S503: The health status determination device multiplies the normal performance indicator probability of each indicator set of the target device to obtain the health value of the target device.

[0117] In a possible manner, after obtaining the normal performance indicator probability of each indicator set, the health status determination device may multiply the normal performance indicator probability of each indicator set to obtain the health value of the target device.

[0118] In one possible approach, the formula for accumulating the probability of normal performance indicators for each indicator set is as follows:

[0119]

[0120] Among them, the health value of the target device is P i , the probability of normal performance index of the index set is P j , the performance indicator type of the target device is n.

[0121] Exemplarily, in combination with the examples in S501 and S502, after obtaining the normal performance indicator probabilities of each of the three indicator sets as 0.9, 0.8 and 1 respectively, the health status determination device multiplies the normal performance indicator probabilities of each indicator set to obtain a health value of the target device of 0.72.

[0122] S504: The health status determining device compares the health value of the target device with a first threshold value to obtain the device status of the target device.

[0123] In one possible manner, after obtaining the health value of the target device, the health status determination device may compare the health value of the target device with a first threshold to obtain the device status of the target device. The health status determination device may determine the device status of the target device as normal when the health value of the target device is greater than or equal to the first threshold.

[0124] Alternatively, the health status determining device may determine the device status of the target device as abnormal when the health value of the target device is less than a first threshold.

[0125] Exemplarily, in combination with the examples in S501-S503, the first threshold is set to 0.8. After obtaining that the health value of the target device is 0.72, the health status determination device can compare the health value of the target device with the first threshold, and obtain that the health value of the target device is less than the first threshold, and determine the device state of the target device as abnormal.

[0126] Based on the above technical solution, the health status determination method provided by the present application can classify the values ​​of the performance indicators of the target device according to the type and determine multiple indicator sets of the target device. Then, the values ​​in each indicator set are subjected to abnormal detection processing to obtain the normal performance indicator probability of each indicator set. Based on this, the normal performance indicator probability of each indicator set of the target device can be multiplied to obtain the health value of the target device. In this way, the health value of the target device can be compared with the first threshold to obtain the device status of the target device.

[0127] Compared with the method of determining the equipment status of the data center by having the staff conduct a health check on each device in the data center, the health status determination device in this application can obtain and process the performance indicators of multiple devices within a preset period to determine the health status of the data center, which can avoid the low efficiency and easy misjudgment caused by the manual check method. Therefore, the present application can efficiently and accurately determine the health status of the data center.

[0128] For example, Figure 6 FIG. 1 is a schematic diagram of a health status determination device provided in an embodiment of the present application. The health status determination device is used to execute the data processing method provided in the present application. For example, the above Figure 4 and Figure 5 The health status determination method in the health status determination device may include: an acquisition unit 601, a determination unit 602, and a processing unit 603.

[0129] The acquisition unit 601 is used to acquire performance indicators of multiple devices in the data center within a preset period.

[0130] The determining unit 602 is configured to determine the device status of each device according to the performance indicator of each device among the multiple devices.

[0131] The determination unit 602 is further configured to determine the health status of the data center according to the proportion of devices in the data center that are in normal status.

[0132] Optionally, the determination unit 602 is specifically configured to perform the following target operation on each device to determine the device state of each device. The target operation includes: classifying the values ​​of the performance indicators of the target device according to the type to determine multiple indicator sets of the target device. Performing anomaly detection processing on the values ​​in each indicator set to obtain the normal performance indicator probability of each indicator set. Multiplying the normal performance indicator probability of each indicator set of the target device to obtain the health value of the target device. Comparing the health value of the target device with the first threshold to obtain the device state of the target device.

[0133] Optionally, the determining unit 602 is specifically configured to normalize the values ​​of multiple types of performance indicators of the target device to obtain the values ​​of the processed performance indicators. The values ​​of the performance indicators of the target device are classified according to the types of the performance indicators to determine multiple indicator sets of the target device, including: classifying the values ​​of the processed performance indicators of the target device according to the types to determine the multiple indicator sets of the target device.

[0134] Optionally, the determination unit 602 is specifically configured to obtain the proportion of devices in the data center with normal device status according to the device status of each device, and compare the proportion of devices in the data center with normal device status with a second threshold to obtain the health status of the data center.

[0135] Optionally, the processing unit 603 is configured to calculate the mean and variance of each indicator set, and process the indicator set, the mean and the variance according to the normal distribution method to obtain the normal performance indicator probability of each performance indicator in the indicator set.

[0136] also, Figure 6 The technical effects of the health status determination device can refer to the technical effects of the data processing method in the above embodiment, which will not be repeated here.

[0137] Through the description of the above implementation methods, technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0138] An embodiment of the present application provides a computer program product including instructions. When the computer program product is run on a computer, the computer is enabled to execute the data processing method in the above method embodiment.

[0139] An embodiment of the present application also provides a computer-readable storage medium, in which instructions are stored. When the instructions are executed on a computer, the computer executes the data processing method in the method flow shown in the above method embodiment.

[0140] Among them, the computer readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer readable storage media (a non-exhaustive list) include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a register, a hard disk, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above, or any other form of computer readable storage medium known in the art. An exemplary storage medium is coupled to a processor so that the processor can read information from the storage medium and write information to the storage medium. Of course, the storage medium can also be a component of the processor. The processor and the storage medium can be located in an application-specific integrated circuit (ASIC). In the embodiments of the present application, a computer-readable storage medium may be any tangible medium that contains or stores a program, which may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0141] Since the data processing device, computer-readable storage medium, and computer program product in the embodiments of the present application can be applied to the above method, the technical effects that can be obtained can also refer to the above method embodiments, and the embodiments of the present application will not be repeated here.

[0142] The above is only a specific real-time method of the present application, but the protection scope of the present application is not limited thereto, and any changes or replacements within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for determining health status, characterized in that: The method comprises: Obtain performance indicators of multiple devices in a data center within a preset period; Determine the device status of each device according to the performance indicator of each device in the plurality of devices; the device status includes normal or abnormal; The health status of the data center is determined according to the proportion of devices in normal device status in the data center; the health status includes normal or abnormal.

2. The method for determining health status according to claim 1, characterized in that: The performance indicators include multiple types of performance indicators; and determining the device status of each device according to the performance indicator of each device in the multiple devices includes: Performing the following target operation on each of the devices to determine the device status of each of the devices; the target operation includes: Classifying the values ​​of the performance indicators of the target devices according to the types, and determining a plurality of indicator sets of the target devices; wherein the target device is any one of the plurality of devices, and one indicator set includes the value of one type of performance indicator; Performing anomaly detection processing on the values ​​in each of the indicator sets to obtain the normal performance indicator probability of each of the indicator sets; Multiplying the normal performance indicator probability of each indicator set of the target device to obtain the health value of the target device; The target device health value is compared with a first threshold to obtain a device state of the target device.

3. The method for determining health status according to claim 1, characterized in that: Before classifying the values ​​of the performance indicators of the target devices according to the types and determining the multiple indicator sets of the target devices, the method further includes: Normalizing the values ​​of the multiple types of performance indicators of the target device to obtain processed values ​​of the performance indicators; The classifying the values ​​of the performance indicators of the target devices according to the types to determine a plurality of indicator sets of the target devices includes: The processed performance indicator values ​​of the target device are classified according to the type to determine a plurality of indicator sets of the target device.

4. The method for determining health status according to claim 3, characterized in that: Determining the health status of the data center according to the proportion of devices in the data center that are in normal status includes: According to the device status of each device, a proportion of devices in the data center with normal device status is obtained; The proportion of devices in the data center that are in normal state is compared with a second threshold value to obtain a health state of the data center.

5. The method for determining health status according to claim 4, characterized in that: The performing of anomaly detection processing on the values ​​in each of the indicator sets to obtain the normal probability of each performance indicator in the indicator set includes: Calculating the mean and variance of each of the indicator sets; The indicator set, mean and variance are processed according to the normal distribution method to obtain the normal performance indicator probability of each performance indicator in the indicator set.

6. The method for determining health status according to any one of claims 1 to 5, characterized in that: The performance indicators include one or more of the following: device port drop rate, device port packet loss rate, device port error packet rate, device central processing unit CPU utilization, device port throughput and device port utilization.

7. A health status determination device, characterized in that: The device comprises: an acquisition unit and a determination unit; An acquisition unit, used to acquire performance indicators of multiple devices in a data center within a preset period; a determining unit, configured to determine a device state of each device according to a performance indicator of each device among the plurality of devices; The determination unit is further configured to determine the health status of the data center according to the proportion of devices in the data center that are in normal status.

8. The health status determination device according to claim 7, characterized in that: The performance indicators include various types of performance indicators; the determining unit is specifically used to: Performing the following target operation on each of the devices to determine the device status of each of the devices; the target operation includes: Classifying the values ​​of the performance indicators of the target devices according to the types, and determining a plurality of indicator sets of the target devices; wherein the target device is any one of the plurality of devices, and one indicator set includes the value of one type of performance indicator; Performing anomaly detection processing on the values ​​in each of the indicator sets to obtain the normal performance indicator probability of each of the indicator sets; Multiplying the normal performance indicator probability of each indicator set of the target device to obtain the health value of the target device; The target device health value is compared with a first threshold to obtain a device state of the target device.

9. A health status determination device, characterized in that: include: A processor and a communication interface; the communication interface is coupled to the processor, and the processor is used to run a computer program or instruction to implement the health status determination method as described in any one of claims 1-6.

10. A computer-readable storage medium, wherein instructions are stored in the computer-readable storage medium, characterized in that: When a computer executes the instruction, the computer executes the health status determination method described in any one of claims 1-6 above.

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