阅读说明：本技术 分布式计算系统的监控方法、装置、电子设备及存储介质 (Monitoring method and device for distributed computing system, electronic equipment and storage medium ) 是由 耿雨飞 古新才 于 2021-09-10 设计创作，主要内容包括：本公开提供了一种分布式计算系统的监控方法、装置、电子设备、可读存储介质、计算机程序产品以及分布式计算系统,涉及分布式计算、高精地图和自动驾驶领域。具体实现方案为：获取执行指定任务的分布式计算系统对应的监控指标,所述监控指标用于表示所述分布式计算系统在执行所述指定任务时的运行情况；将所述监控指标按照获取时间生成时间序列数据；基于所述时间序列数据,对所述监控指标进行可视化处理。该方案能够为可能出现的运行异常的处理和预防,以及分布式计算系统的任务或资源调整提供决策依据。而通过为相关人员提供用于管理分布式计算系统运行的决策依据,能够提高分布式计算系统任务执行的成功率。(The disclosure provides a monitoring method and device of a distributed computing system, an electronic device, a readable storage medium, a computer program product and the distributed computing system, and relates to the field of distributed computing, high-precision maps and automatic driving. The specific implementation scheme is as follows: acquiring a monitoring index corresponding to a distributed computing system executing a specified task, wherein the monitoring index is used for representing the running condition of the distributed computing system when the specified task is executed; generating time sequence data according to the monitoring index and the acquisition time; and performing visualization processing on the monitoring index based on the time sequence data. The scheme can provide decision basis for processing and preventing possible operation abnormity and task or resource adjustment of the distributed computing system. And the success rate of task execution of the distributed computing system can be improved by providing decision basis for managing the operation of the distributed computing system for related personnel.)

1. A method of monitoring a distributed computing system, comprising:

acquiring a monitoring index corresponding to a distributed computing system executing a specified task, wherein the monitoring index is used for representing the running condition of the distributed computing system when the specified task is executed;

generating time sequence data according to the monitoring index and the acquisition time;

and performing visualization processing on the monitoring index based on the time sequence data.

2. The method of claim 1, wherein the obtaining of the corresponding monitoring index of the distributed computing system comprises:

determining a monitoring index receiver corresponding to each node;

and pulling the corresponding monitoring indexes of the nodes from each monitoring index collector, wherein each node is a node in the distributed computing system for executing different subtasks in the specified task, and the monitoring index collector is a data collector in each node for collecting the respective monitoring indexes.

3. The method of claim 1, wherein the generating time series data of the monitoring index according to the acquisition time comprises:

and writing the monitoring index into a time sequence database to generate the time sequence data.

4. The method of claim 1 or 3, wherein the generating the time series data comprises:

determining monitoring index names corresponding to different types of monitoring indexes in the monitoring indexes and monitoring index labels corresponding to the different types of monitoring indexes, wherein the monitoring index labels are labels used for representing characteristics of the different types of monitoring indexes;

and generating time sequence data corresponding to the different types of monitoring indexes based on the monitoring index name and the monitoring index label.

5. The method of claim 4, wherein the visualizing the monitoring indicator based on the time-series data comprises:

and carrying out visualization processing on the different types of monitoring indexes based on the time sequence data corresponding to the different types of monitoring indexes.

6. The method of claim 1 or 5, wherein the visualizing the monitoring indicator based on the time-series data comprises:

and carrying out graph and report processing on the time sequence data to generate a visual chart corresponding to the monitoring index.

7. A monitoring apparatus of a distributed computing system, comprising:

the system comprises a monitoring index acquisition module, a task execution module and a task execution module, wherein the monitoring index acquisition module is used for acquiring a monitoring index corresponding to a distributed computing system executing a specified task, and the monitoring index is used for representing the running condition of the distributed computing system when the specified task is executed;

the time sequence data generating module is used for generating time sequence data according to the monitoring index and the acquisition time;

and the visualization processing module is used for performing visualization processing on the monitoring index based on the time sequence data.

8. The apparatus of claim 7, wherein the monitoring indicator obtaining module comprises:

the receiver determining submodule is used for determining the monitoring index receivers corresponding to the nodes;

and the monitoring index pulling submodule is used for pulling the corresponding monitoring indexes of the nodes from each monitoring index collector, each node is a node which is used for executing different subtasks in the specified task in the distributed computing system, and the monitoring index collector is a data collector which is used for collecting each monitoring index in each node.

9. The apparatus of claim 7, wherein the time series data generating module is specifically configured to write the monitoring indicator into a time series database to generate the time series data.

10. The apparatus of claim 7 or 9, wherein the time series data generating module comprises:

the index name and label determining submodule is used for determining monitoring index names corresponding to different types of monitoring indexes in the monitoring indexes and monitoring index labels corresponding to the different types of monitoring indexes, and the monitoring index labels are labels used for representing characteristics of the different types of monitoring indexes;

and the time sequence data generation submodule is used for generating time sequence data corresponding to the different types of monitoring indexes on the basis of the monitoring index names and the monitoring index labels.

11. The apparatus according to claim 10, wherein the visualization processing module is specifically configured to perform visualization processing on the different types of monitoring indicators based on the time-series data corresponding to the different types of monitoring indicators.

12. The apparatus according to claim 7 or 11, wherein the visualization processing module is specifically configured to perform graphic and report processing on the time-series data to generate a visualization chart corresponding to the monitoring index.

13. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 6.

14. A non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method of any one of claims 1 to 6.

15. A computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the steps of the method of claims 1 to 6.

16. A distributed computing system comprising the electronic device of claim 13.

Technical Field

The present disclosure relates to the field of distributed computing, high-precision maps and autopilot, and is particularly applicable to scenarios such as big data, distributed computing, high-precision mapping in autopilot, and the like.

Background

Tasks involving large-scale data processing, such as high-precision mapping for automated driving, often need to be accomplished using distributed computing systems. When a large-scale data processing task is completed by using a distributed computing system, the task execution is often failed due to various abnormal operation problems of the distributed computing system because the data computation amount is very large and complicated. In order to improve the success rate of task execution of the distributed computing system, the operation condition of the distributed computing system when executing a specified task needs to be monitored, so as to monitor the possible operation abnormality of the distributed computing system in real time.

However, the existing monitoring method for the distributed computing system often cannot provide decision basis for managing the operation of the distributed computing system for related personnel.

Disclosure of Invention

The present disclosure provides a monitoring method and apparatus for a distributed computing system, an electronic device, a readable storage medium, a computer program product, and a distributed computing system, so as to provide a decision basis for managing the operation of the distributed computing system for related personnel, and improve the success rate of task execution of the distributed computing system.

According to an aspect of the present disclosure, there is provided a monitoring method of a distributed computing system, which may include the steps of:

acquiring a monitoring index corresponding to a distributed computing system executing a specified task, wherein the monitoring index is used for representing the running condition of the distributed computing system when the specified task is executed;

generating time sequence data according to the monitoring index and the acquisition time;

and performing visualization processing on the monitoring index based on the time sequence data.

According to a second aspect of the present disclosure, there is provided a monitoring apparatus of a distributed computing system, the apparatus may include:

the system comprises a monitoring index acquisition module, a task execution module and a task execution module, wherein the monitoring index acquisition module is used for acquiring a monitoring index corresponding to a distributed computing system executing a specified task, and the monitoring index is used for representing the running condition of the distributed computing system when the specified task is executed;

the time sequence data generating module is used for generating time sequence data according to the monitoring index and the acquisition time;

and the visualization processing module is used for performing visualization processing on the monitoring index based on the time sequence data.

According to another aspect of the present disclosure, there is provided an electronic device including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method according to any one of the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform a method in any of the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a computer program product comprising computer programs/instructions, characterized in that the computer programs/instructions, when executed by a processor, implement the method in any of the embodiments of the present disclosure.

According to another aspect of the present disclosure, there is provided a distributed computing system including the electronic device provided in the embodiments of the present disclosure.

According to the technology disclosed by the invention, after the monitoring indexes corresponding to the distributed computing system executing the specified task are obtained, the monitoring indexes are firstly generated into time sequence data according to the obtaining time, and then the monitoring indexes are visualized based on the time sequence data, so that the visualization of the monitoring indexes corresponding to the distributed computing system executing the specified task can be realized.

Related personnel can analyze and predict possible operation abnormity of the distributed computing system based on the visualized monitoring index, so that decision basis is provided for processing and preventing the possible operation abnormity. Related personnel can also perform tasks or resources on the distributed computing system based on the visualized monitoring indexes, so that decision basis is provided for task or resource adjustment of the distributed computing system. And the success rate of task execution of the distributed computing system can be improved by providing decision basis for managing the operation of the distributed computing system for related personnel.

It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.

Drawings

The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:

FIG. 1 is a flow chart of a method of monitoring a distributed computing system provided in an embodiment of the present disclosure;

fig. 2 is a flowchart of a monitoring index obtaining method provided in an embodiment of the present disclosure;

fig. 3 is a schematic illustration of a visualization of a monitoring indicator provided in an embodiment of the present disclosure;

FIG. 4 is a flow chart of a method of time series data provided in an embodiment of the present disclosure;

FIG. 5 is a schematic illustration of a visual icon of a monitoring indicator provided in an embodiment of the present disclosure;

FIG. 6 is a schematic diagram of a monitoring device of a distributed computing system provided in an embodiment of the present disclosure;

fig. 7 is a schematic view of an electronic device provided in an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

The present disclosure provides a monitoring method for a distributed computing system, and in particular, refer to fig. 1, which is a flowchart of a monitoring method for a distributed computing system provided in an embodiment of the present disclosure. The method may comprise the steps of:

step S101: and acquiring a monitoring index corresponding to the distributed computing system executing the specified task, wherein the monitoring index is used for representing the running condition of the distributed computing system when executing the specified task.

Step S102: and generating time sequence data according to the monitoring index and the acquisition time.

Step S103: and performing visualization processing on the monitoring index based on the time sequence data.

By distributed computing system performing a specified task, we mean a system comprising a plurality of nodes connected via the internet, which cooperate to perform and accomplish a specified task. Specifically, the nodes may include a master node and a child node, and the master node may be a management node, and is responsible for management and configuration of the system, management and allocation of tasks, and may also be used to execute child tasks. The child nodes may also be referred to as slave nodes, and their purpose includes, but is not limited to, executing the respective assigned different subtasks in parallel.

The subtask may be a task that is executed by the main node after the main node divides the designated task and allocates the divided task to a different node. In the process of executing the sub-tasks distributed by each node, the real-time execution results of the sub-tasks in the corresponding time intervals can be provided for the main node for unified combination of the results according to the preset time intervals; or after each node completes the respective assigned subtasks, the execution results corresponding to the subtasks are provided to the master node for unified combination of the results, so as to obtain the final task execution result of the specified task.

The real-time execution results of the subtasks in the corresponding time intervals are provided for the main node to carry out unified combination of the results, the unified combination of the results can be dispersed to different time periods, and therefore the pressure of the main node can be reduced.

Common implementations of so-called nodes include, but are not limited to, computers, servers. The server cluster may specifically include different servers of a unified server cluster, may also be a computer, a server, and the like deployed in different places of the same region, and may also be a computer, a server, and the like deployed in different regions.

Taking an appointed task as an example of making a high-precision map of a certain urban area, the task may be divided into a plurality of sub-tasks according to different regions included in the urban area, and each sub-task is a task of making a high-precision map of the region. After the subtasks are divided, the subtasks for making the high-precision map of the region are correspondingly distributed to the computers, servers and the like deployed in the region to which the subtasks belong.

In the monitoring method of the distributed computing system provided in the embodiment of the present disclosure, the execution main body is mainly a target program, application, or software running on the master node. A target program, application, or software is a program, application, or software having a function of monitoring a distributed computing system.

In the monitoring method for the distributed computing system provided in the embodiment of the disclosure, after the monitoring index corresponding to the distributed computing system executing the specified task is acquired, the monitoring index generates time series data according to the acquisition time. And then, based on the time sequence data, performing visualization processing on the monitoring index. Therefore, the visualization of the monitoring indexes corresponding to the distributed computing system executing the specified tasks can be realized.

Related personnel can analyze and predict possible operation abnormity of the distributed computing system based on the visualized monitoring index, so that decision basis is provided for processing and preventing the possible operation abnormity. Related personnel can also perform tasks or resources on the distributed computing system based on the visualized monitoring indexes, so that decision basis is provided for task or resource adjustment of the distributed computing system. By providing decision basis for managing the operation of the distributed computing system for related personnel, the success rate of task execution of the distributed computing system can be improved.

Specifically, related personnel can analyze and predict possible operation abnormity of the distributed computing system based on the visualized monitoring index. The process enables related personnel to quickly process and prevent possible operation abnormity of the distributed computing system. And finally, the success rate of task execution can be improved.

The analysis and prediction of possible operation anomalies of the distributed computing system includes but is not limited to: analyzing and predicting the time that the operating memory occupation of the distributed computing system possibly exceeds the corresponding threshold value; and analyzing and predicting the corresponding workload when the CPU utilization rate exceeds an alarm threshold value, and the like.

In addition, based on the visualized monitoring indexes, the distributed computing system is adjusted in tasks or resources, including but not limited to: based on the visualized monitoring indexes, analyzing and predicting which node is overloaded and adjusting tasks or resources of the node to be overloaded, such as: reducing the workload, adjusting the resources for supporting the execution of the subtasks in the nodes, and the like; or, based on the visualized monitoring indexes, analyzing and predicting the type of the job executed by each node in different time periods of each day and the current work amount, and allocating the resources required by each node in different time periods according to the type of the job and the current work amount. The resources and the like required by each node in different time periods are adjusted according to the running conditions, so that the success rate of task execution can be improved.

In the embodiment of the present disclosure, the monitoring index includes at least one of a read data amount, a write record number, a read record number, a current work amount, a Central Processing Unit (CPU) usage rate, a memory usage rate, a network access flow rate, a thread number, a Transaction Per Second (TPS) and a disk read/write throughput, etc., of a program, an application, etc. for specifying a task during execution of the task.

In the embodiment of the present disclosure, the monitoring index may be configured according to data such as task type and task amount. For example, for a task requiring occupation of a large CPU resource, the usage rate of the CPU is generally required to be used as a monitoring index; for a task with frequent data reading and writing, the read data volume, the write record number, and the read record number are generally required to be used as monitoring indexes.

The method is used for acquiring the state or degree of the change of the running condition along with time so as to reflect the running condition in real time, so that related personnel can know the real-time running condition of the distributed computing system when the distributed computing system executes a specified task. In the embodiment of the disclosure, after the monitoring index is acquired, the monitoring index is generated into time series data according to the acquisition time.

Specifically, the step of generating the time series data by the monitoring index according to the acquisition time refers to the step of generating the time series data by the monitoring index acquired at different times according to the sequence of the acquisition time, and generating the time series data at specified time intervals. The time-series data is used to reflect the state or degree of change of the operating condition with time. The implementation mode can be as follows: the monitoring index is written into a Time Series Database (TSDB) to generate Time Series data.

In order to facilitate obtaining the monitoring indexes corresponding to different nodes in the distributed computing system, so as to better distinguish the monitoring indexes corresponding to the different nodes, so that relevant personnel can obtain a decision basis for each node in a targeted manner, the step of obtaining the monitoring indexes corresponding to the distributed computing system may be as shown in fig. 2, which is a flowchart of a monitoring index obtaining method provided in an embodiment of the present disclosure.

Step S201: and determining monitoring index receivers corresponding to the nodes.

Step S202: and pulling the monitoring indexes of the corresponding nodes from each monitoring index collector, wherein each node is a node which is used for executing different subtasks in the specified task in the distributed computing system, and each monitoring index collector is a data collector which is used for collecting each monitoring index in each node.

Fig. 3 is a schematic diagram of a visualization of a monitoring indicator provided in an embodiment of the disclosure. The monitoring index receiver is a data collector which is pre-deployed at each node 301. The specific implementation manner includes a graph-export, where a monitoring index receiver corresponding to each monitoring index collector in a monitoring index service (monitoring-server) is configured to pull the monitoring index of the corresponding node from each monitoring index collector, and write the monitoring index into a time series database to generate time series data. Finally, the time series data can be visualized into a corresponding visualization chart through a graphic editor. Wherein the graphic editor may be Grafana.

It should be noted that the exporter is a component that collects monitoring indexes and provides data to the outside through a Prometheus monitoring specification; prometheus is an open source service monitoring system and a time sequence database, and runs on a main node; grafana is an open-source instrument panel and a graph editor, a promQL is built in Grafana and provides a rich graph tool, the graph tool is connected with a Prometous time sequence database through an http (Hypertext Transfer Prtcl) protocol, and a monitoring index required by the promQL (Prometous Query Language, a data Query domain specific Language corresponding to Prometous) is used for querying so as to realize visualization processing on the required monitoring index.

That is, in the embodiment of the present disclosure, only the required monitoring index may be visualized. For example, only the running memory occupation amount or the CPU usage rate and the like are visualized. Only the required monitoring indexes are visualized, so that the obtained visualized data are more targeted, and resources required by visualization can be reduced.

In addition, after the required monitoring indexes are subjected to visualization processing, the required monitoring indexes can be further visually displayed, so that relevant personnel can make relevant decisions on the distributed computing system based on the visualized monitoring indexes. The specific implementation mode is as follows: and carrying out visualization processing on the different types of monitoring indexes based on the time sequence data corresponding to the different types of monitoring indexes.

In addition, the implementation manners of the monitoring index collector, the monitoring index receiver and the service monitoring system are not limited to the above implementation manners, as long as the visualization processing of the monitoring index can be realized.

In order to conveniently aggregate, filter and crop the monitoring index for visualization processing of the monitoring index, the steps shown in fig. 4 may be adopted to generate the time series data, and fig. 4 is a flowchart of a method for generating the time series data provided in the embodiment of the present disclosure.

Step S401: and determining monitoring index names corresponding to different types of monitoring indexes in the monitoring indexes and monitoring index labels corresponding to the different types of monitoring indexes, wherein the monitoring index labels are labels used for representing the characteristics of the different types of monitoring indexes.

Step S402: and generating time sequence data corresponding to different types of monitoring indexes based on the monitoring index name and the monitoring index label.

The monitoring index name may be a special name for identifying a certain monitoring index. For example: when the monitoring index is the CPU utilization rate, the name is the CPU utilization rate. The following steps are repeated: and when the monitoring index is the operating memory occupation amount, the name is the operating memory occupation amount.

In order to improve the visualization efficiency, reduce the visualization cost, and ensure that the time series data can be visually displayed, in the embodiment of the disclosure, the visualization processing of the monitoring index is realized by adopting a method of performing graph and report processing on the time series data and generating a visualization chart corresponding to the monitoring index. Fig. 5 is a schematic diagram illustrating a visual icon of a monitoring indicator provided in an embodiment of the present disclosure. The monitoring index in the graph is the number of read records, the abscissa of the coordinate system represents time, and the ordinate represents the current number of read records.

The monitoring method of the distributed computing system provided in the embodiment of the present disclosure may further compare the time-series data with the alarm rule. When the monitoring index reaches the alarm rule, alarming; or when the monitoring index does not reach the alarm rule, continuing monitoring.

As shown in fig. 6, a monitoring apparatus of a distributed computing system provided in an embodiment of the present disclosure includes:

the monitoring index acquiring module 601 is configured to acquire a monitoring index corresponding to a distributed computing system that executes a specified task, where the monitoring index is used to indicate an operation condition of the distributed computing system when executing the specified task;

a time series data generating module 602, configured to generate time series data from the monitoring index according to the acquisition time;

and a visualization processing module 603, configured to perform visualization processing on the monitoring index based on the time-series data.

In an embodiment, the monitoring index obtaining module 601 may further include:

the receiver determining submodule is used for determining the monitoring index receivers corresponding to the nodes;

and the monitoring index pulling submodule is used for pulling the monitoring indexes of the corresponding nodes from each monitoring index collector, each node is a node which is used for executing different subtasks in the specified task in the distributed computing system, and the monitoring index collector is a data collector which is used for collecting each monitoring index in each node.

In one embodiment, the time-series data generating module 602 is specifically configured to write the monitoring index into a time-series database to generate the time-series data.

In one embodiment, the time-series data generating module 602 may further include:

the index name and label determining submodule is used for determining monitoring index names corresponding to different types of monitoring indexes in the monitoring indexes and monitoring index labels corresponding to the different types of monitoring indexes, and the monitoring index labels are labels used for representing characteristics of the different types of monitoring indexes;

and the time sequence data generation submodule is used for generating time sequence data corresponding to different types of monitoring indexes based on the monitoring index name and the monitoring index label.

In an embodiment, the visualization processing module 603 is specifically configured to perform visualization processing on different types of monitoring indexes based on time-series data corresponding to the different types of monitoring indexes.

In an embodiment, the visualization processing module 603 is specifically configured to perform graph and report processing on the time series data to generate a visualization chart corresponding to the monitoring index.

In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.

According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.

In addition, the present disclosure also provides a distributed computing system including the electronic device provided by the embodiment of the present disclosure.

FIG. 7 illustrates a schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 7, the device 700 comprises a computing unit 701, which may perform various suitable actions and processes according to a computer program stored in a Read Only Memory (ROM)702 or a computer program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM703, various programs and data required for the operation of the device 700 can also be stored. The computing unit 701, the ROM 702, and the RAM703 are connected to each other by a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.

Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as various types of displays, speakers, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, modem, wireless communication transceiver, etc. The communication unit 709 allows the device 700 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.

Computing unit 701 may be a variety of general purpose and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The computing unit 701 performs the various methods and processes described above, such as the monitoring method of a distributed computing system. For example, in some embodiments, the monitoring method of the distributed computing system may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of a computer program may be loaded onto and/or installed onto device 700 via ROM 702 and/or communications unit 709. When the computer program is loaded into the RAM703 and executed by the computing unit 701, one or more steps of the monitoring method of the distributed computing system described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured by any other suitable means (e.g., by means of firmware) to perform the monitoring method of the distributed computing system.

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.

It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.

The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.