CN116010201A - Monitoring method, management equipment and computing system - Google Patents

Abstract

The application discloses a monitoring method, management equipment and a computing system, relates to the technical field of cloud primary monitoring, and is used for improving index monitoring efficiency. The method is applied to the management equipment of the computing cluster for monitoring and deploying the cloud primary service; the method comprises the following steps: displaying a first interface; the first interface comprises a selection inlet of candidate objects corresponding to the monitoring objects with the granularity respectively; receiving a first operation on a first interface, and determining at least one target monitoring object in the candidate objects; wherein the target monitoring object comprises any one or more of the following: a target computing device in the computing cluster, a target program in the target computing device, and a target variable in the target program; sending a monitoring request comprising the identification of the target monitoring object and the monitored target parameter to the computing equipment corresponding to at least one target monitoring object; the target parameters are used for indicating parameters related to the cloud primary service of the target monitoring object; target parameter information is received in response to the monitoring request.

Description

A monitoring method, management equipment and computing system

technical field

The present application relates to the technical field of cloud computing, and in particular to a monitoring method, a management device and a computing system.

Background technique

The stable operation of the business system is an important prerequisite for providing business services to users. At present, the maintenance and management of the business system is realized by monitoring various indicators of the business system. In a cloud-native scenario, multiple computing devices usually form a cluster to provide users with business services. Among them, the resources of each computing device in the cluster are divided using container technology, so that the processes running in different containers are relatively independent. In this way, it is helpful for the flexible deployment of the business, but at the same time, it greatly increases the difficulty of monitoring various indicators in the system.

Contents of the invention

The embodiment of the present application provides a monitoring method, a management device and a computing system, which are used to monitor various indicators of computing devices in a cluster.

In order to achieve the above object, the embodiments of the present application adopt the following technical solutions:

In the first aspect, a monitoring method is provided, which is applied to a management device, wherein the management device is used to monitor a computing cluster for deploying cloud-native services, and the computing cluster includes multiple computing devices; the method includes: displaying a first interface; wherein, The first interface includes selection entries of candidate objects corresponding to monitoring objects of multiple granularities; receiving a first operation for the selection entry of candidate objects in the first interface; in response to the first operation, determining at least one target monitoring among the candidate objects object; wherein, the target monitoring object includes any one or more of the following: the target computing device in the computing cluster, the target program in the target computing device, and the target variable in the target program; the computing device corresponding to at least one target monitoring object Send a monitoring request; the monitoring request includes the identification of the target monitoring object and the monitored target parameters; wherein, the target parameter is used to indicate the parameters related to the target monitoring object and the cloud native business; receiving the computing device corresponding to the target monitoring object responds to the monitoring request Target parameter information.

Since the current cluster resources involve multiple computing devices, and based on container technology, the cluster resources are divided into finer-grained methods, which makes it difficult to monitor various indicators in the cluster resources. Currently, resources are usually monitored for a single computing device. It is impossible to flexibly change the monitored indicator items and monitor the overall resources based on different granularities for rapid positioning, which makes the current monitoring efficiency low. In this regard, using the above method provided by the embodiment of the present application, the management device can realize the monitoring of various indicators in the cluster. Among them, the user can use different monitoring granularities for the cluster resources to obtain corresponding data information, and improve the user's overall monitoring of the overall cluster. The monitoring effect of resources can improve the stability of cloud-native business operation.

In a possible implementation, the monitoring objects of multiple granularities include: computing device programs and variables; wherein, the programs include at least one of the following: pods, containers, and processes; Containers, processes and variables.

This possible implementation method provides a monitorable level of granularity of the management device, which helps users obtain indicator information of monitoring objects of different granularities through the management device, and improves the monitoring effect.

In a possible implementation manner, before displaying the first interface, the method further includes: storing associations between monitoring objects of multiple granularities; and in response to the first operation, determining at least one target monitoring object among candidate objects , including: in response to the first operation, determining at least one target monitoring object among the candidate objects according to the association relationship in descending granularity.

This possible implementation method provides an implementation method for selecting a target monitoring object based on multi-granularity monitoring objects, which helps the user quickly locate the target monitoring object and improves the efficiency of determining the monitoring object.

In a possible implementation manner, before sending the monitoring request to the computing device corresponding to the at least one target monitoring object, the method further includes: displaying a second interface, where the second interface includes operation options for operating parameters; A second operation of the operation option of the operating parameters in the interface; in response to the second operation, determining the target parameter among the operating parameters.

In this possible implementation manner, the implementability of the solution is improved through the user determining the target parameter for the operation on the second interface.

In a possible implementation, the second interface further includes modification operation options, and the method further includes: receiving a third operation of modifying operation options for operating parameters in the second interface; in response to the third operation, calculating the The device sends a modification request, and the modification request includes the modified operating parameters of the target monitoring object running cloud-native services.

This possible implementation method helps the user to modify the operating parameters, and then flexibly adjust the index items that the system monitors for the monitored objects, and improve the monitoring efficiency.

In a possible implementation, the method further includes: converting the target parameter information into information recognizable by a visualization program, wherein the visualization program is used to convert the information recognizable by the visualization program into a visualized image; displaying a third interface, The third interface includes visual images.

This possible implementation manner helps to provide users with more intuitive target parameter information, thereby improving user experience.

In a possible implementation manner, converting target parameter information into information identifiable by a visualization program includes: mapping target parameter information into readable labels and values; obtaining information identifiable by the visualization program according to the labels and values.

This possible implementation method provides a processing process when the target parameter information is converted into a visualized image, and improves the implementability of the scheme.

In a possible implementation manner, the method further includes: storing target parameter information.

This possible implementation method is helpful for statistics of historical operating parameters and facilitates further analysis and processing of data.

In a second aspect, a management device is provided, including a processor, a display, and a communication interface, the processor is connected to the communication interface and the display respectively; the display is used to display the first interface; wherein, the first interface includes multiple granularity monitoring The selection entries of the candidate objects corresponding to the objects respectively; the communication interface is used to receive the first operation for the selection entry of the candidate objects in the first interface; the processor is used to respond to the first operation and determine at least one target among the candidate objects A monitoring object; wherein, the target monitoring object includes any one or more of the following: a target computing device in the computing cluster, a target program in the target computing device, and a target variable in the target program; the communication interface is also used to send at least one target The computing device corresponding to the monitoring object sends a monitoring request; the monitoring request includes the identity of the target monitoring object and the monitored target parameters; wherein, the target parameter is used to indicate the parameters of the target monitoring object related to cloud native services; the communication interface is also used for The computing device corresponding to the target monitoring object responds to the target parameter information of the monitoring request.

In a third aspect, a management device is provided, including functional units for executing any one of the methods provided in the first aspect, and the actions performed by each functional unit are realized by hardware or by executing corresponding software by hardware. For example, the management device may include: a processing unit, a display unit, and a communication unit. The display unit is used to display the first interface; wherein, the first interface includes selection entries of candidate objects corresponding to monitoring objects of multiple granularities; the communication unit is used to receive the first selection entry for the candidate objects in the first interface. Operation; a processing unit configured to determine at least one target monitoring object among candidate objects in response to the first operation; wherein, the target monitoring object includes any one or more of the following: a target computing device in a computing cluster, a target computing device in The target program of the target program and the target variable in the target program; the communication unit is also used to send a monitoring request to the computing device corresponding to at least one target monitoring object; the monitoring request includes the identification of the target monitoring object and the monitored target parameters; wherein, the target The parameters are used to indicate the parameters of the target monitoring object related to the cloud native service; the communication unit is also used to receive the target parameter information of the computing device corresponding to the target monitoring object responding to the monitoring request.

In a fourth aspect, a management device is provided, including: a processor and a memory. The processor is electrically connected to the memory, the memory is used to store program instructions, and the processor is used to execute the program instructions, so that the management device executes any one of the methods provided in the first aspect.

In the fifth aspect, a computing system is provided, the computing system includes multiple computing devices and the management devices described in the second to fourth aspects above; wherein, the computing devices are used to run cloud-native services; the management devices are used to monitor Information related to cloud-native services running on computing devices, such as resource usage information of computing devices, pods, containers, processes, and variables.

According to a sixth aspect, a chip is provided, and the chip includes: a processor and an interface circuit; the interface circuit is used to receive code instructions and transmit them to the processor; a way.

In a seventh aspect, a computer-readable storage medium is provided, including computer-executable instructions, and when the computer-executable instructions are run on the computer, the computer is made to execute any one of the methods provided in the first aspect.

In an eighth aspect, a computer program product is provided, including computer-executable instructions, and when the computer-executable instructions are run on a computer, the computer is made to execute any one of the methods provided in the first aspect.

For the technical effects brought about by any one of the implementations from the second aspect to the eighth aspect, refer to the technical effects brought about by the corresponding implementations in the first aspect, which will not be repeated here.

Description of drawings

Fig. 1 is a schematic diagram of a system for realizing indicator monitoring based on a monitoring container;

FIG. 2 is a schematic diagram of a system for realizing indicator monitoring based on an indicator observation tool;

FIG. 3 is a schematic diagram of a monitoring scene provided by an embodiment of the present application;

FIG. 4 is a schematic diagram of the composition of a communication device provided by an embodiment of the present application;

FIG. 5 is a schematic flow diagram of a monitoring method provided in an embodiment of the present application;

FIG. 6 is a schematic diagram of a first interface for determining a target monitoring object provided by an embodiment of the present application;

FIG. 7 is a schematic diagram of a first interface for determining a target indicator provided by an embodiment of the present application;

FIG. 8 is a schematic diagram of a second interface for determining target indicators provided by an embodiment of the present application;

FIG. 9 is a schematic flowchart of a monitoring method provided in an embodiment of the present application;

FIG. 10 is a schematic diagram of a mapping relationship of raw data provided by an embodiment of the present application;

FIG. 11 is a schematic structural diagram of a management device provided by an embodiment of the present application.

Detailed ways

In the description of the present application, unless otherwise specified, "/" means "or", for example, A/B may mean A or B. The "and/or" in this article is just an association relationship describing associated objects, which means that there can be three relationships, for example, A and/or B, which can mean: A exists alone, A and B exist at the same time, and B exists alone These three situations. In addition, "at least one" means one or more, and "plurality" means two or more. Words such as "first" and "second" do not limit the number and order of execution, and words such as "first" and "second" do not necessarily limit the difference.

It should be noted that, in this application, words such as "exemplary" or "for example" are used as examples, illustrations or illustrations. Any embodiment or design described herein as "exemplary" or "for example" is not to be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "exemplary" or "such as" is intended to present related concepts in a concrete manner.

Currently, the cloud-native architecture is a mainstream architecture in cloud computing. It has the characteristics of micro-service, continuous integration, containerization, and developer operation and maintenance (development operations, DevOps). Enable flexible deployment. For example, in a cloud-native architecture, a cluster of multiple computing devices is usually used to carry business services. The resources of multiple computing devices are divided based on container technology to obtain multiple independent operating environments, which are used to carry one or more processes respectively. Specifically, the container technology realizes the isolation between processes by utilizing the control groups (control groups, cgroup for short) and namespace (namespace) mechanism of the Linux kernel. Among them, cgroup is used to represent the resources of a container (such as central processing unit (central processing unit, CPU) resources, memory, etc.). The command space mechanism is used to distinguish the same variable name in different operating environments. Based on the above method, each container has independent computing resources for the running of the process, and based on the namespace mechanism, conflicts caused by the existence of the same variable between containers are avoided.

It can be understood that the computing device involved in the embodiment of the present application includes but is not limited to an electronic device having a computing function such as a server and a computer.

Currently, in order to realize the management of cluster resources, the kubernetes open source platform (hereinafter referred to as k8s) is mainly used for container arrangement and scheduling. Among them, pod is the smallest deployable unit in k8s, and containers run in pods. A pod can include one or more containers, and pods can also be called container groups. Therefore, the cluster resources managed by k8s can be divided into different granularities based on computing device level, pod level, container level and process level.

Business service During the operation of the business system, the monitoring of various indicators in the business system is the key to maintaining the stability of the business system. Among them, the indicator items are used to reflect the operation of the business system from different dimensions. For example, the index items include operating parameters such as CPU usage, memory usage, and running time. In the Linux system, the indicator items described above can be monitored through the process management tool, and the status of the system process can be described. For example, the top tool can reflect the dynamic information of the system process, that is, update the status of the system process in time as the current system process runs. Another example is to use the ps tool to reflect static snapshots of processes executed by the system in the past, that is, to display the status of the process corresponding to the query time.

However, because the cluster resources that carry cloud-native services use container technology to divide each computing device resource in the cluster to form an independent operating environment, the process detection tools commonly used in the above-mentioned systems cannot obtain the running status of the container granularity. In this regard, a monitoring method is currently proposed. By adding parallel monitoring containers to the pod, the running status of each business container in the pod can be monitored. As shown in Figure 1, a pod with monitoring containers can monitor indicators for each business container in the pod. In this way, the monitoring container can be flexibly deployed according to the user's monitoring requirements based on the business container. For example, in Figure 1, in pod1, monitor container 1 is deployed for service container 1 and service container 2. In pod2, monitor container 2 is deployed for business container 3. In pod3, the monitoring container is not deployed to monitor the indicators of the service container 3, so it is not limited to the deployment form of the monitoring container in the pod. Among them, multiple monitoring containers can also be deployed in a pod to monitor different business containers in the pod.

The above monitoring method is a monitoring strategy adopted by a sensu monitoring tool provided in k8s. Specifically, sensu runs the monitoring container through the sidecar mode in k8s, and collects the required information by monitoring the communication between the container and each business container in the same pod. index item.

In the above monitoring method, because the monitoring container runs under the resources of the user mode, it cannot access kernel resources to obtain indicator monitoring based on process granularity. Therefore, the smallest monitoring unit of sensu is the container. In addition, using the above method, the user needs to add a monitoring container to the pod running on the monitoring object to realize monitoring, so that each pod occupies a certain amount of resources, which is used to deploy one or more monitoring containers according to user needs, and the monitoring efficiency is improved. lower.

Currently, another monitoring method is proposed, by calling the program in the indicator observation tool set (inspektor-gadget) to access kernel resources and obtain the running status of the internal process of the container. Specifically, the index observation tool set is based on the extended Berkeley packet filter (eBPF) framework of the Linux kernel to access kernel resources. The indicator observation tool set can realize the monitoring of more indicator items, such as obtaining information such as disk input and output (IO) traffic, network connection delay, and file open objects. As shown in Figure 2, the user calls the monitoring command for a certain indicator in the indicator observation tool set, and the command realizes access to kernel resources through the eBPF framework, obtains corresponding monitoring information, and feeds back to the user.

In this monitoring method, the indicator observation tool set is stored in each computing device, and indicator items are monitored based on user needs. However, in the cloud-native scenario, based on the cluster resources composed of multiple computing devices, it is impossible to quickly call instructions according to user needs.

In this regard, this application proposes a monitoring method, which is applied to a management device. The management device communicates with multiple computing devices deployed with cloud-native services, and is used to respond to user monitoring requests based on indicators of different granularities and locate corresponding computing devices. Devices, obtain the data information corresponding to the corresponding index items to feed back to the user, which helps to flexibly obtain the operation status of the computing devices in the cluster, and improve the efficiency of index monitoring through the unified management of multiple computing devices.

As shown in Figure 3, it is a schematic diagram of an indicator monitoring scenario provided by this application, including a management device used to manage multiple computing devices in the cluster (computing device 1, computing device 2, ..., computing device n, where n is greater than 1 integer). Each computing device includes one or more pods, each pod includes one or more containers, the processes in the containers run cloud-native services, and each computing device also includes a collection of observation programs for different indicators The item calls the corresponding observation program to obtain the corresponding data information. Exemplarily, the computing device reads data from the kernel by observing trace points or stub points such as kprobe and tracepoint in the kernel of the program. Based on the monitoring method provided by the embodiment of the present application, the management device sends an indicator monitoring request to a target computing device among multiple computing devices, and the target computing device invokes relevant monitoring instructions based on the target parameters requested by the indicator monitoring request to obtain target parameter information, And feed back to the management device, and the management device will feed back to the user after receiving it, so as to realize the indicator monitoring of different monitoring granularities of multiple computing devices in the cluster resource in the cloud native business scenario, and improve the monitoring efficiency of the overall resource of the cluster.

The management device to which the monitoring method provided in the embodiment of the present application is applied may execute the method provided in the present application as an independent communication device. The present application does not limit the specific form of the communication device, which may be a terminal or a server. Wherein, the terminal specifically may be a mobile phone, an augmented reality (augmented reality, AR) device, a virtual reality (virtual reality, VR) device, a tablet computer, a notebook computer, an ultra-mobile personal computer (ultra-mobile personal computer, UMPC), a netbook, a personal digital Assistant (personal digital assistant, PDA), etc. A server can be a physical or logical server.

In terms of hardware implementation, the aforementioned communication device may implement corresponding functions through the communication device shown in FIG. 4 . As shown in FIG. 4 , it is a schematic diagram of a hardware structure of a communication device 40 provided in the embodiment of the present application.

The communication device 40 shown in FIG. 4 may include: a processor 401 , a memory 402 , a communication interface 403 , a bus 404 and a display 405 . The processor 401 , the memory 402 , the communication interface 403 and the display 405 may be connected through a bus 404 .

The processor 401 is the control center of the communication device 40, and may be a general-purpose CPU or other general-purpose processors. Wherein, the general-purpose processor may be a microprocessor or any conventional processor.

As an example, the processor 401 may include one or more CPUs, such as CPU 0 and CPU1 shown in FIG. 4 .

The memory 402 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (random access memory, RAM) or other types that can store information and instructions The dynamic storage device can also be an electrically erasable programmable read-only memory (electrically erasable programmable read-only memory, EEPROM), a magnetic disk storage medium or other magnetic storage devices, or can be used to carry or store instructions or data structures. desired program code and any other medium that can be accessed by a computer, but not limited thereto.

In a possible implementation manner, the memory 402 may exist independently of the processor 401 . The memory 402 can be connected to the processor 401 through the bus 404, and is used for storing data, instructions or program codes. When the processor 401 invokes and executes instructions or program codes stored in the memory 402, the monitoring method provided by the embodiment of the present application can be realized.

In another possible implementation manner, the memory 402 may also be integrated with the processor 401 .

The communication interface 403 is used to connect the communication device 40 with other devices through a communication network, and the communication network may be Ethernet, radio access network (radio access network, RAN), wireless local area network (wireless local area networks, WLAN) and the like. The communication interface 403 may include a receiving unit for receiving data, and a sending unit for sending data.

The bus 404 may be an industry standard architecture (industry standard architecture, ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (extended industry standard architecture, EISA) bus, etc. The bus can be divided into address bus, data bus, control bus and so on. For ease of representation, only one thick line is used in FIG. 4 , but it does not mean that there is only one bus or one type of bus.

The display 405 is used for displaying images, videos and the like. The display includes a display screen, a display panel, and the like. The display panel can be a liquid crystal display (LCD), an organic light-emitting diode (OLED), an active matrix organic light emitting diode or an active matrix organic light emitting diode (active-matrix organic light emitting diode, AMOLED), flexible light-emitting diode (flex light-emitting diode, FLED), Miniled, MicroLed, Micro-oLed, quantum dot light emitting diodes (quantum dotlight emitting diodes, QLED), etc. In some embodiments, the communication device 40 may include 1 or N display screens, where N is a positive integer greater than 1. In the embodiment of the present application, the display can display the monitored target parameter information, and receive a user's selection operation or input operation on the monitored object and the monitored parameter.

It should be noted that the structure shown in FIG. 4 does not constitute a limitation on the communication device 40. In addition to the components shown in FIG. some components, or a different arrangement of components.

As shown in FIG. 5 , it is a schematic flowchart of a monitoring method provided in the embodiment of the present application. The method is applied to a management device monitoring multiple computing devices deploying cloud native services, including steps S501-S505.

S501. Displaying a first interface.

Wherein, the first interface includes selection entries of candidate objects corresponding to monitoring objects of multiple granularities.

Wherein, monitoring objects of multiple granularities include: computing devices, programs and variables. A program includes at least one of the following: pod, container, process. The granularity in descending order is computing device, pod, container, process, and variable.

It can be understood that the current business system includes multiple computing devices carrying cloud-native services. In the embodiments provided in this application, corresponding monitoring services are provided according to the division of computing resources in the business system. Specifically, the monitoring granularity includes computing device level, pod level, container level, process level and variable level. The target monitoring object can be determined as a specific monitoring object under a certain monitoring granularity based on each monitoring granularity.

Exemplarily, as shown in FIG. 6 , it is a schematic diagram of a first interface provided by the embodiment of the present application. Wherein, the first interface includes an entry for selecting candidate objects corresponding to monitoring objects based on different granularities. In the first interface shown in FIG. 6 , there are identifiers indicating each monitoring granularity, such as computing device, container group pod, container, and process. Correspondingly, each monitoring granularity includes one or more candidate objects.

S502. Receive a first operation for selecting an entry of a candidate object in the first interface.

Wherein, the first operation is used to determine the target monitoring object in the selection entry of the candidate object.

Exemplarily, in FIG. 6 , each monitoring granularity corresponds to a selection entry of a candidate object, and the selection entry is used for the user to select one or more candidate objects under the monitoring granularity. For example, by clicking this entry in FIG. 6 , a candidate object list corresponding to each monitoring granularity is displayed, and the candidate object list is composed of one or more identifiers of candidate objects. For example, the candidate object list corresponding to the computing device includes computing device a, computing device b, and computing device c. Similarly, the list of candidates for pods can include pod a, pod b, and pod c.

S503. In response to the first operation, determine a target monitoring object among candidate objects; wherein, the target monitoring object includes any one or more of the following: a target computing device in a computing cluster, a target program in a target computing device, and a target program in a target program target variable.

Exemplarily, when the target monitoring object is a target computing device in a computing cluster, the indicator monitoring request is used to perform indicator monitoring based on computing device-level granularity, and the target indicator obtained by the management device is that the target computing device is running a cloud-native business The running status of the process, such as the CPU usage rate of the overall resources of the target computing device, memory usage and other data information.

Exemplarily, when the target program is a pod, the target monitoring object is a pod in the target computing device among multiple computing devices, the indicator monitoring request is used for monitoring based on pod-level granularity, and the indicator monitoring request is used for requesting to obtain target indicators Data information such as the CPU usage and memory usage of the pod in the target computing device.

Exemplarily, when the target program is a container or a process, the indicator monitoring request is used for monitoring based on container-level or process-level granularity, wherein the requested target indicator is a certain container or a certain process in the target computing device in Operations on the target computing device.

Exemplarily, the monitoring granularity also includes a variable level. The target monitoring object is a certain variable in the target program. Among them, the process running on the computing device may contain multiple variables, and the indicator monitoring request can be detected based on variable-level granularity. Data information such as occupancy status.

In conjunction with the above step S501 and step S502, in a possible implementation manner, the management device stores identifiers of multiple computing devices in the business system, and associations between the multiple computing devices and programs. As shown in Table 1 below, it is an example of an association relationship between a computing device and a program.

Table 1. Examples of associations between computing devices and programs

In an example, the candidate object list corresponding to the computing device shown in Figure 6 includes computing device a, computing device b, and computing device c, and the candidate object list corresponding to pod includes pod a1, pod a2, pod b, and pod c, The candidate object list corresponding to the container includes container a1 , container a2 , container a3 , container b1 , container b2 and container c.

In another example, in combination with the example in Table 1 above, the candidate object list corresponding to the computing device shown in FIG. 6 includes computing device a, computing device b, and computing device c, and the candidate object list corresponding to pod is based on the Select the list of candidate objects in the computing device, and display it in conjunction with the relationship between the program and the computing device in Table 1. For example, when the user selects computing device a, based on the relationship between computing device a and the program, determine the candidate object corresponding to the pod The list includes pod a1 and pod a2. Similarly, when the user selects pod a1, the candidate object list corresponding to the container includes container a1 and container a2.

It can be understood that, based on the above example, the presentation manner of the candidate object identifiers in the first interface is helpful to improve the convenience of interacting with the user.

It should be noted that the above description of the first interface elements contained in the first interface is only an example, and can be further optimized in the actual application process. For example, in the above another example, different first interface elements According to the monitoring granularity selected by the user step by step, it is displayed on different interfaces. When the user selects the computing device a and jumps to the interface to pod and its corresponding candidate object list, the user then makes a selection based on the candidate object list in the interface. This is not limited.

It should be noted that, in the first interface shown in FIG. 6 , the identifiers of the candidate objects are displayed in the form of a pull-down menu. In practical applications, they can also be displayed in other forms, which is not limited in this application. In addition, more or fewer interface elements may be included in the first interface, for example, a process-level candidate object list is also included, so that the user can operate in the first interface and determine the monitoring object, which is not limited in this application .

In another example, the user selects candidate objects step by step according to the monitoring granularity, and takes the candidate object with the smallest monitoring granularity as the target monitoring object. As shown in (a) in Figure 7, based on Figure 6, after the user selects computing device a among the candidates of computing devices, he further selects pod a1 in pod; in (b) in Figure 7, based on Select container a1 from container a1 and container a2 corresponding to pod a1. At this time, container a1 is the identifier of the target monitoring object. If, in the example shown in FIG. 6 , the user selects the computing device a from among the computing devices and does not select a finer-grained pod, the target monitoring object is identified as the computing device a.

It should be noted that the first operation is related to the operable controls on the first interface, and can be flexibly adjusted according to the controls deployed on the first interface, which is not limited in this application.

Optionally, in response to the first operation, the management device determines at least one target monitoring object. Wherein, the at least one target monitoring object may be a monitoring object under different monitoring granularities. Exemplarily, in FIG. 6 or FIG. 7 , the user selects one or more computing devices, or one or more programs; or, the user selects one or more computing devices, and one or more programs. That is to say, the target monitoring object may be one or more monitoring objects of the same granularity, or multiple monitoring objects of different granularities.

S504. Send a monitoring request to a computing device corresponding to at least one target monitoring object.

Wherein, the monitoring request includes the identification of the target parameter information and the target parameter to be monitored, and the target parameter is used to indicate the parameters of the target monitoring object related to the cloud native service.

In an example, the target parameter is any one or more of the index items described above.

Optionally, before the above step S504, the management device determines the target parameters through the following steps S11-S13.

S11. Display a second interface; wherein, the second interface includes operation options for operating parameters.

Wherein, the operating parameter is used to indicate resource usage information in the business system. It can be understood as the index item mentioned above.

Exemplarily, as shown in FIG. 8 , it is a schematic diagram of a second interface provided by the embodiment of the present application. In the second interface shown in FIG. 8 , there are identifications of multiple running parameters, such as CPU usage rate, memory usage rate and running time. The second interface also includes operation options corresponding to various operating parameters, such as opening and closing. Specifically, when the user chooses to enable the operation option corresponding to a certain operating parameter, it indicates that information on the operating parameter needs to be acquired.

Among them, in Figure 8, the running time in the running parameters refers to the running time after the computing device or the program in the computing device is started (during which it is not closed), such as the running time after the computing device is turned on, the running time after the pod is created, etc. .

Optionally, the management device can also monitor the input and output of the disk, and the operating parameters also include the number of reads and writes per second (input/output operations per second, IOPS), which is used to monitor the performance of the disk. The management device can also perform network monitoring, and the operating parameters also include network packet loss rate, network delay, etc.

In a possible implementation manner, the one or more operating parameters have a corresponding relationship with target monitoring objects. Exemplarily, when the target monitoring object is a certain process, the running parameter may include not only one or more running parameters described in the above examples, but also the number of process handles. Among them, by monitoring the information of the number of process handles, it is avoided that a certain process occupies too many resources and affects the overall performance of the system. This implementation manner can also be understood as, the management device determines the target monitoring object based on the first interface and determines the second interface.

Further, when multiple target monitoring objects are determined in the above step S503, the second interface corresponding to each target monitoring object may be determined through the corresponding relationship between target monitoring objects and operating parameters. For example, in FIG. 6 , the user selects computing device a and computing device b, and in response to the user's selection, the second interface includes an interface corresponding to the operating parameters of computing device a and an interface corresponding to operating parameters of computing device b.

It can be understood that the number and form of the operating parameters included in the second interface described above are only examples, and in actual applications, more or fewer operating parameters and other corresponding operating parameters may also be included. option, which is not limited in this application.

S12. A second operation of receiving operation options for one or more operating parameters in the second interface.

Specifically, the second operation is performed based on a specific form of the operation option. For example, click, double-click, or type.

Exemplarily, in FIG. 8 , the operation options include on or off, which is used for the user to perform the second operation based on the requirement of the observed index.

S13. In response to the second operation, determine target parameter information in one or more pieces of parameter information.

Exemplarily, in FIG. 8 , when the user selects "on" based on the "CPU usage rate", the management device determines the "CPU usage rate" as the target parameter.

It can be understood that there may be one or more target parameters to meet the user's monitoring requirements.

Wherein, the above-mentioned process of determining the target parameter can also be understood as enabling or disabling the monitoring function of one or more index items.

Through the above steps S11-S13, the management device determines the target parameter by displaying the second interface for the user and receiving the user's operation on the second interface.

Wherein, when the target monitoring object is a target computing device, step S504 specifically includes: determining an address of the target computing device according to locally stored computing device information, and sending target parameters based on the address. When the target monitoring object is a target program or a target variable, step S502 specifically includes: according to the association relationship between the computing device and the program or variable, based on the target program indicated by the target monitoring object, determining the computing device corresponding to the target program; The computing device corresponding to the target program sends a monitoring request.

In a possible implementation manner, the address of the computing device is stored in the management device, and the address for sending the monitoring request is determined based on the identifier of the computing device corresponding to the target monitoring object.

Based on the above steps S11-S13, the management device determines for the target monitoring object and the monitored target parameter, and sends a monitoring request including the identification of the target parameter to the computing device corresponding to the target monitoring object.

S505. Receive target parameter information that the computing device corresponding to the target monitoring object responds to the monitoring request.

Wherein, the target parameter information is used to reflect the specific data information of the target parameter of the target monitoring object in its corresponding computing device.

After the monitoring request is sent through the above step S504, the computing device corresponding to the target monitoring object receives the monitoring request, and obtains target parameter information based on the monitoring request.

As shown in Figure 3, the management device sends the monitoring request to the computing device 1, and the computing device 1 invokes the corresponding program in the observation program set according to the identification of the target parameter included in the monitoring request, obtains the target parameter information, and feeds it back to the management equipment. Wherein, the observation program set includes observation programs corresponding to one or more operating parameters displayed on the second interface. The observation program is used to access the kernel based on the eBPF framework and obtain corresponding data information.

Since the current business system contains multiple computing devices, and the resources of the business system are divided into more fine-grained methods based on container technology, it is difficult to monitor various indicators in the resources of the business system. Resources are monitored, and the monitored indicators cannot be flexibly changed, and the monitoring of the overall resources based on different granularities cannot be quickly located, which makes the current monitoring efficiency low. In this regard, by adopting the above method provided by the embodiment of the present application, the management device provides an operation platform, so that the user can complete the monitoring of various indicators in the cluster through simple operations. Among them, users can use different monitoring granularities for cluster resources to obtain corresponding parameter information, improve the user's monitoring effect on business system resources, and then improve the stability of cloud-native business operations.

Optionally, after the above step S505, the method further includes: the management device stores the target parameter information.

Wherein, the management device stores the target parameter information locally, or stores the target parameter information in other devices or databases independent of the management device.

It is understandable that users may need to obtain data information for a certain target parameter information within a period of time, rather than real-time data information, so as to perform analysis based on the data information obtained within a period of time, such as obtaining Set the highest value reached within the time period, and determine whether to adjust the service carried by the computing device based on the highest value.

Optionally, after the above step S505, the method further includes: the management device displays monitoring data; wherein the monitoring data includes target parameter information of the target monitoring object responded by the target computing device, or the monitoring data includes target monitoring data responded by the target computing device The target parameter information of the object, and the identification of the computing device to which the target monitoring object belongs.

In one example, when the target monitoring object is a target computing device, and the target parameter information is identified as a CPU usage rate, the monitoring data includes the value of the current CPU usage rate of the target computing device, or further includes the target computing device ID . When the target monitoring object is a pod, and the identifier of the target parameter information is CPU usage, the monitoring data includes the value of the CPU usage of the pod in the computing device to which it belongs. Optionally also includes the identification of the computing device to which the pod belongs.

In another example, when the target monitoring object is a target program, such as a container, and the identification of the target parameter information is CPU usage, the monitoring data includes the value of the CPU usage of the container in the computing device to which it belongs; or, The monitoring data also includes the identity of the pod to which the container belongs and the identity of the computing device. Similarly, when the target monitoring object is a process, the monitoring data includes target parameter information, and may also include the identifier of the container, the identifier of the pod, and the identifier of the computing device to which the process belongs.

Through the above method, the user is provided with other monitoring granularity programs or computing device identifiers related to the target monitoring object, which facilitates the user to view relevant information and improves the intelligence of monitoring.

Optionally, the target parameter information received in the above step S505 is the original data obtained from the operating system kernel by the computing device described by the target monitoring object. After step S505, the method further includes: converting the target parameter information into a visualization program identifiable information, the visualization program is used to convert the information identifiable by the visualization program into a visualized image; displaying a third interface containing the visualized image.

It can be understood that when the target monitoring object is the target program, the corresponding observation program needs to access the kernel to obtain the required data. For example, when a container is created, the kernel records the running parameters of the container through cgroup information. When the target program is a pod, container, or process, the running parameters can be obtained through cgroup information.

Among them, the process of obtaining a visualized image by using a visualization program is called a visualization processing process, and visualization processing refers to converting data information into graphics or images based on image processing technology. Exemplarily, the user obtains the disk IOPS over a period of time, and obtains a line chart of the IOPS over time during the period through visualization processing, which helps the user to intuitively know the trend of IOPS over time based on the line chart, so as to determine whether it is the More or fewer resources are allocated for services carried by computing devices.

It can be understood that, through the above method, it is helpful for the user to obtain more intuitive data information through the visualized image, and improve the monitoring efficiency of the user.

Specifically, the management device obtains information identifiable by the visualization program through the steps shown in FIG. 9 , including steps S901-S904.

S901. Determine whether the target parameter information is formatted data.

If yes, execute step S904 to output the formatted data; if not, continue to execute step S902.

Wherein, the formatted data refers to the data that can be recognized by the above-mentioned visualization program.

It can be understood that the data obtained from the kernel is usually output in accordance with the data format specified by the observation program. Correspondingly, the data receiver needs to read it in accordance with the specified data format, so as to convert it into formatted data that can be recognized by the visualization program. When performing visualization processing, the visualization program has strict requirements on the data structure and the length of the string, and the data that meets the above requirements of the visualization program is formatted data.

S902. Map the target parameter information into readable labels and values.

Wherein, when the observation program obtains the target parameter information of the target program in the kernel of the computing device, it exports the information in the kernel according to preset rules. The preset rule may be a data storage format of labels and values. A set of labels and values corresponds to a set of data, and each set of data corresponds to a type of observation information. Correspondingly, the management device analyzes according to the preset rules to obtain readable labels and values; the readable labels and numbers are target parameter information that can be read by the management device. Exemplarily, as shown in FIG. 10 , the original data includes data group 1 , data group 2 and data group 3 . After mapping, the pod ID, container ID and PID are obtained. The three labels correspond to their respective values, so that the required data information can be obtained based on the original data.

In a possible implementation, the observation program needs to call other programs in the kernel to trace the data according to the data obtained in the kernel. For example, the PID can be obtained directly in the kernel, and based on the PID, the container ID can be traced back through its corresponding cgroup information, for example, in the following way:

cat /proc/$PID/cgroup|awk -F'/''{print $5}'

In addition, based on the PID, the pod ID can also be traced through moutinfo, such as the following method:

cat /proc/$PID/mountinfo|grep "etc-hosts"|awk -F/{'print $6'}

Through the above method, it is helpful to present more relevant data for reference based on tracing more relevant information, and improve the monitoring efficiency of cluster resources.

S903. Format the label and the value.

Specifically, the process of formatting the labels and data is to perform data processing according to the data structure and the length of the string specified by the visualization program to obtain formatted data.

S904. Output formatted data.

It can be understood that, in the above solution, the management device obtains the operating parameters of the corresponding computing device through the user's monitoring request, and further, can also process the obtained information to obtain a visualized image through a visualization program. The above step S904 is an example where the management device outputs the formatted data to the device for visualization processing. After this step, the method may further include receiving a visualization image and displaying it. For example, the management device acquires a change curve of disk I/O traffic over a period of time.

It should be noted that the visualization program can be directly deployed on the management device, and then step S904 can directly output and display the visualization image.

It can be understood that, through the above method, based on the original data obtained from the kernel, it is formatted and converted into formatted data that can be read by a visualization program, thereby providing an implementation basis for realizing data visualization processing.

Optionally, the management device stores the formatted data and/or visualized images locally, or in other devices or databases independent of the business system.

Optionally, after the above step S505, the method further includes: receiving a first modification request sent by the target computing device, where the first modification request is used to add or delete computing devices or programs in multiple computing devices; responding The first modification request is to update the information of the computing device in the business system and the association relationship between the computing device and the program.

It can be understood that the resource in the cluster may change, and the resource change needs to be updated in the management device, so that the target monitoring object of the indicator monitoring can be accurately located during the indicator monitoring.

In a possible implementation manner, the target computing device includes the identifier of the changed computing device or program in the first modification request and sends it to the management device. Exemplarily, if a new container is added to the target computing device, the identifier of the changed computing device or program includes at least the identifier of the container, the identifier of the pod to which the container belongs, and the identifier of the computing device to which the container belongs. If the existing container is deleted in the target computing device, only the identifier of the container may be included.

It can be understood that the management device maintains the relationship between the target computing device and the target program, that is, the relationship between the resources in the current cluster based on different granularities. to update the relationship. If deletion is performed, the management device may update the association relationship accordingly based on the identifier of the deletion program.

It should be noted that the modification of the program is taken as an example above, and the addition and deletion of computing devices are also included in the actual application. The method of updating the information of the computing devices in the business system by the management device is similar to the above implementation method, and will not be described again.

Optionally, the management device updates the first interface element on the first interface, including updating the candidate object list of the target computing device and/or the candidate object list of the target program.

Optionally, the second interface also includes modifying operation options. After the above step S505, the method further includes: receiving a third operation for modifying operating parameters in the second interface; in response to the third operation, calculating A modification request sent by the device, wherein the modification request includes the modified operating parameters of the target monitoring object running cloud-native services.

It can be understood that, in the example described above, the user can indicate the target index to be monitored by operating the operation option corresponding to the parameter in the second interface. Wherein, the second interface also includes modification operation options for modifying the operating parameters in the interface, and for adding or deleting observation instructions for currently existing target indicators.

In a possible implementation manner, the modification operation option is used to receive input information from a user, and the input information may be an instruction to add or delete any one or more of at least one instruction item of the target monitoring device. In response to the user's input information, the management device sends the modification request to the computing device to which the target monitoring device belongs, and the computing device that receives the modification request generates and runs a new observation program based on the eBPF framework, and obtains corresponding data information to feed back to the management device; or , the computing device deletes the observation program corresponding to the instruction item in the observation instruction set sum. After completing the above steps, the computing device feeds back response information to the management device, and the management device updates the operating parameters in the second interface based on the response information. Exemplarily, bpftrace, bcc or other bpf programs can add or delete trace points (kprobe, trace point, etc.) through classifiers to achieve the purpose of dynamically switching corresponding plug-ins to obtain desired information.

Optionally, the management device updates the identification of the operating parameters and corresponding operation options on the second interface.

It should be noted that the modification of the operating parameters above can be performed individually for the computing device to which the selected target monitoring object belongs, or for multiple computing devices in the business system, which is not limited in this application.

Through the above method, it is helpful to flexibly adjust the observation program of each command in each computing device according to user needs, and improve the overall monitoring efficiency of cluster resources.

It should be noted that, in the implementation process of the above scheme, there can be one or more target monitoring objects, and the number of target parameters can also be one or more, and the target parameters of different target monitoring objects can be the same or different. No limit.

The foregoing mainly introduces the solutions of the embodiments of the present application from the perspective of methods. It can be understood that, in order to realize the above functions, the management device includes at least one of corresponding hardware structures and software modules for performing various functions. Those skilled in the art should easily realize that the present application can be implemented in the form of hardware or a combination of hardware and computer software in combination with the units and algorithm steps of each example described in the embodiments disclosed herein. Whether a certain function is executed by hardware or computer software drives hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present application.

The embodiments of the present application may divide the management device into functional units according to the above method examples. For example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic, and is only a logical function division, and there may be another division manner in actual implementation.

In the case of dividing each functional module corresponding to each function, FIG. 11 shows a possible structural diagram of the management device involved in the above embodiment. As shown in FIG. 11 , the management device 110 includes a display unit 1101 , a communication unit 1102 and a processing unit 1103 .

The display unit 1101 is configured to display a first interface; wherein, the first interface includes selection entries of candidate objects corresponding to monitoring objects of multiple granularities.

The communication unit 1102 is configured to receive a first operation for selecting an entry of a candidate object in the first interface.

The processing unit 1103 is configured to determine at least one target monitoring object among the candidate objects in response to the first operation; wherein, the target monitoring object includes any one or more of the following: a target computing device in a computing cluster, a target computing device in a The object program and the object variable in the object program.

The communication unit 1102 is further configured to send a monitoring request to the computing device corresponding to at least one target monitoring object; the monitoring request includes the identification of the target monitoring object and the monitored target parameters; wherein, the target parameter is used to indicate that the target monitoring object is compatible with the cloud-native business-related parameters.

The communication unit 1102 is further configured to receive target parameter information of the computing device corresponding to the target monitoring object responding to the monitoring request.

In one example, monitoring objects of multiple granularities include: computing device programs and variables; wherein, the programs include at least one of the following: pods, containers, and processes; the order of granularity from large to small is computing devices, pods, containers, and processes and variables.

In an example, the management device 110 further includes a storage unit 1104, configured to store association relationships between monitoring objects of multiple granularities; Determine at least one target monitoring object among the candidate objects.

In an example, the display unit 1101 is further configured to display a second interface, and the second interface includes operation options of operating parameters; the communication unit 1102 is also configured to receive a second operation on the operation options of operating parameters in the second interface ; The processing unit 1103 is further configured to determine the target parameter among the running parameters in response to the second operation.

In one example, the second interface further includes modifying operation options, and the communication unit 1102 is further configured to receive a third operation for operating parameters in the second interface; the communication unit 1102 is further configured to respond to the third Operation, sending a modification request to the target computing device, the modification request includes the modified operating parameters of the target monitoring object running the cloud native business.

In one example, the processing unit 1103 is further configured to convert target parameter information into information recognizable by a visualization program, wherein the visualization program is used to convert information recognizable by the visualization program into a visualized image; the display unit 1101 is also used to For displaying the third interface, the third interface includes a visualized image.

In an example, the processing unit 1103 is specifically configured to map target parameter information into readable labels and values; and obtain information recognizable by the visualization program according to the labels and values.

In an example, the storage unit 1104 is further configured to store target parameter information.

In an example, the storage unit 1104 is also used to store computer-executable instructions, and other units in the management device may perform corresponding actions according to the computer-executable instructions stored in the storage unit 1104 .

For a specific description of the foregoing optional manners, reference may be made to the foregoing method embodiments, and details are not repeated here. In addition, for the explanations and descriptions of the beneficial effects of any management device 110 provided above, reference may be made to the corresponding method embodiments above, and details are not repeated here.

The embodiment of the present application also provides a management device. Referring to the schematic diagram of the hardware structure of the communication device shown in FIG. 4 above, the management device includes: a processor, a display, and a communication interface, and the processor is connected to the communication interface and the display respectively. The display is used to display the first interface; wherein, the first interface includes the selection entries of candidate objects corresponding to the monitored objects of multiple granularities; the communication interface is used to receive the first operation for the selection entries of the candidate objects in the first interface a processor, configured to determine at least one target monitoring object among candidate objects in response to the first operation; wherein, the target monitoring object includes any one or more of the following: a target computing device in a computing cluster, a target computing device in a The target program and the target variable in the target program; the communication interface is also used to send a monitoring request to the computing device corresponding to at least one target monitoring object; the monitoring request includes the identification of the target monitoring object and the monitored target parameter; wherein, the target parameter It is used to indicate the parameters related to the target monitoring object and the cloud native business; the communication interface is also used to receive the target parameter information of the computing device corresponding to the target monitoring object responding to the monitoring request.

The management device also includes a memory. Wherein, the memory may contain computer program codes. The processor is configured to execute the computer program code stored in the memory, so as to realize the method provided by the embodiment of the present application.

During implementation, each step in the method provided by this embodiment may be implemented by an integrated logic circuit of hardware in a processor of the management device or instructions in the form of software. The steps of the methods disclosed in connection with the embodiments of the present application may be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

The embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is run on a computer, the computer is made to execute any one of the management devices provided above The method executed.

Regarding the explanation of relevant content and the description of beneficial effects in any computer-readable storage medium provided above, reference may be made to the above-mentioned corresponding embodiments, and details are not repeated here.

The embodiment of the present application also provides a chip. The chip integrates a control circuit and one or more ports for realizing the above-mentioned functions of the management device. Optionally, the functions supported by the chip can refer to the above, and will not be repeated here. Those of ordinary skill in the art can understand that all or part of the steps for implementing the above-mentioned embodiments can be completed by instructing related hardware through a program. The program can be stored in a computer-readable storage medium. The storage medium mentioned above may be a read-only memory, a random access memory, and the like. The above-mentioned processing unit or processor can be a central processing unit, a general-purpose processor, a specific integrated circuit (application specific integrated circuit, ASIC), a microprocessor (digital signal processor, DSP), a field programmable gate array (field programmable gate array, FPGA) ) or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof.

The embodiments of the present application also provide a computer program product containing instructions, which, when the instructions are run on a computer, cause the computer to execute any one of the methods in the foregoing embodiments. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions according to the embodiments of the present application will be generated in whole or in part. A computer can be a general purpose computer, special purpose computer, computer network, or other programmable device. Computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, e.g. Coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (such as infrared, wireless, microwave, etc.) transmission to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that can be accessed by a computer, or may contain one or more data storage devices such as servers and data centers that can be integrated with the medium. The available media may be magnetic media (eg, floppy disk, hard disk, magnetic tape), optical media (eg, DVD), or semiconductor media (eg, SSD), etc.

It should be noted that the above-mentioned devices for storing computer instructions or computer programs provided in the embodiments of the present application, such as but not limited to, the above-mentioned memory, computer-readable storage medium, and communication chip, etc., all have non-transitory .

In the above embodiments, all or part of them may be implemented by software, hardware, firmware or any combination thereof. When implemented using a software program, it may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions according to the embodiments of the present application will be generated in whole or in part. A computer can be a general purpose computer, special purpose computer, computer network, or other programmable device. Computer instructions may be stored in or transmitted from one computer-readable storage medium to another computer-readable storage medium, e.g. Coaxial cable, optical fiber, digital subscriber line (digital subscriber line, DSL)) or wireless (such as infrared, wireless, microwave, etc.) transmission to another website site, computer, server or data center. The computer-readable storage medium may be any available medium that can be accessed by a computer, or may contain one or more data storage devices such as servers and data centers that can be integrated with the medium. The usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, or a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (solid state disk, SSD)), etc.

Although the present application has been described in conjunction with various embodiments herein, those skilled in the art can understand and realize the disclosure by viewing the drawings, the disclosure, and the appended claims during the implementation of the claimed application. Other Variations of Embodiments. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude a plurality. A single processor or other unit may fulfill the functions of several items recited in the claims. The mere fact that certain measures are recited in mutually different dependent claims does not indicate that these measures cannot be combined to advantage.

Although the application has been described in conjunction with specific features and embodiments thereof, it will be apparent that various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Accordingly, the specification and drawings are merely illustrative of the application as defined by the appended claims and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of this application. Obviously, those skilled in the art can make various changes and modifications to the application without departing from the spirit and scope of the application. In this way, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims (10)

1. A monitoring method, wherein the monitoring method is applied to a management device, wherein the management device is used to monitor a plurality of computing devices in a computing cluster deploying cloud-native services; The methods include: Displaying a first interface; wherein, the first interface includes selection entries of candidate objects corresponding to monitoring objects of multiple granularities; receiving a first operation of selecting an entry for the candidate object in the first interface; In response to the first operation, at least one target monitoring object is determined among the candidate objects; wherein, the target monitoring object includes any one or more of the following: a target computing device in the computing cluster, the target an object program in the computing device and an object variable in the object program; Send a monitoring request to the computing device corresponding to the at least one target monitoring object; the monitoring request includes the identification of the target monitoring object and the monitored target parameters; wherein the target parameters are used to indicate the target monitoring object Parameters related to the cloud-native business; receiving target parameter information in response to the monitoring request from the computing device corresponding to the target monitoring object. 2. The method according to claim 1, wherein the monitoring objects at multiple granularities include: computing device programs and variables; wherein the programs include at least one of the following: pods, containers, and processes; the The granularity in descending order is computing device, pod, container, process, and variable. 3. The method according to claim 2, characterized in that, before the display of the first interface, the method further comprises: storing the association relationship between the monitoring objects of the plurality of granularities; In response to the first operation, determining at least one target monitoring object among the candidate objects includes: In response to the first operation, the at least one target monitoring object is determined among the candidate objects in descending granularity according to the association relationship. 4. The method according to any one of claims 1 to 3, wherein before sending a monitoring request to the computing device corresponding to the at least one target monitoring object, the method further comprises: displaying a second interface, the second interface including operation options for operating parameters; receiving a second operation of operating options for the operating parameters in the second interface; The target parameter is determined among the operating parameters in response to the second operation. 5. The method according to claim 4, wherein the second interface also includes modification operation options, and the method further includes: A third operation of receiving an operation option for modifying the operating parameters in the second interface; In response to the third operation, a modification request is sent to the target computing device, where the modification request includes modified operating parameters for the target monitoring object to run the cloud native service. 6. The method according to any one of claims 1 to 5, characterized in that the method further comprises: converting the target parameter information into information recognizable by a visualization program, wherein the visualization program is used to convert the information recognizable by the visualization program into a visualized image; A third interface is displayed, the third interface includes the visualized image. 7. The method according to claim 5, wherein said converting said target parameter information into information recognizable by a visualization program comprises: Mapping the target parameter information into readable labels and values; Information recognizable by the visualization program is obtained according to the label and the value. 8. The method according to any one of claims 1 to 7, further comprising: storing the target parameter information. 9. A management device, characterized in that it includes a memory and a processor, the memory is electrically connected to the processor; wherein the memory is used to store program instructions, and the processor is used to execute the program instructions, so that the management device executes the monitoring method according to any one of claims 1-8. 10. A computing system, characterized in that the computing system comprises a plurality of computing devices and the management device according to claim 9; wherein the plurality of computing devices are used to run cloud-native services; the management device It is used for monitoring the running information of cloud native services on the multiple computing devices.

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