A server-side interface call indicator monitoring and statistical method and system

Abstract

The present invention relates to a server interface call index monitoring and statistical method and system, the method comprising: obtaining the call information of one or more interfaces of each server and counting their performance indicators, the call information comprising interface name, interface parameters, service name, call mode and input and output rate, the performance indicators comprising TPS, QPS, average call duration, throughput, access rate and call rate; obtaining resource occupancy information and / or call information of each server, dynamically adjusting the load of its corresponding server; dynamically adjusting the flow of one or more interfaces of the server according to the QPS and response time distribution of each server interface. The present invention improves the comprehensiveness of interface testing and also improves the refinement of server operation and maintenance by counting interface call information and the actual status of the server.

Description

Technical Field

[0001] The present invention belongs to the technical field of server operation and maintenance, and in particular relates to a server-side interface call index monitoring and statistical method and system. Background Art

[0002] The server occupies a dominant position in business data processing. According to the complexity of the business process, the server interface processing capabilities will also change accordingly. With the popularity of microservice architecture, more and more service architectures are beginning to use microservices to build or reconstruct their own business systems, but ignore whether their own business volume or business complexity really requires microservices or distributed architecture transformation, which may cause waste of server resources and increase investment costs. Because there is no definite data support to determine the choice of server configuration and architecture optimization plan, the general monitoring plan mainly focuses on the overall status monitoring of the server, such as CPU usage, memory occupancy, IO read and write rate, etc., and will not monitor the actual processing of the interface. Summary of the invention

[0003] In order to monitor the server interface call and load balancing issues, a server interface call indicator monitoring and statistics method is provided in the first aspect of the present invention, including: obtaining the call information of one or more interfaces of each server and counting their performance indicators, the call information including interface name, interface parameters, service name, call mode and input and output rates, and the performance indicators including TPS, QPS, average call time, throughput, access rate and call rate; obtaining resource occupancy information and / or call information of each server, and dynamically adjusting the load of the corresponding server; dynamically adjusting the traffic of one or more interfaces of the server according to the QPS and response time distribution of each server interface.

[0004] In some embodiments of the present invention, the acquisition of resource occupancy information and / or call information of each server and the dynamic adjustment of the load of the corresponding server include: collecting the composition information, resource occupancy rate and current resource occupancy information of each service of each server; the composition information of the server includes CPU main frequency, memory bandwidth and disk space; based on the resource occupancy information and server resource occupancy rate of all services of multiple server ends, the services whose resource occupancy rate exceeds the threshold in the current server end are allocated to other server ends.

[0005] In some embodiments of the present invention, dynamically adjusting the traffic of one or more interfaces of the server according to the QPS and response time distribution of each server interface includes: counting the QPS and response time distribution of each server interface; removing one or more services with the shortest interface response time from the load balancing list; if the response time of more than a preset number of interfaces among the remaining interfaces exceeds a threshold, determining whether a new server node needs to be added based on the number of concurrent application threads and the maximum number of supported threads of the server.

[0006] Furthermore, if the response time of the remaining interfaces exceeding a preset number exceeds a threshold, then judging whether a new server node needs to be added according to the number of concurrent application threads and the maximum number of supported threads on the server includes: dividing the response time of the multiple interfaces into four intervals from small to large, and counting the proportion of each interval; if the response time of the interfaces exceeding the preset number falls within the maximum two intervals, judging whether a new server node needs to be added according to the number of concurrent application threads and the maximum number of supported threads on the server.

[0007] Optionally, judging whether a new server node needs to be added based on the number of concurrent application threads and the maximum number of supported threads of the server includes: judging whether the ratio of the number of concurrent application threads corresponding to the interface to the maximum number of supported threads exceeds a preset value; if so, judging that a new server node needs to be added.

[0008] In the above-mentioned embodiment, the method of obtaining the call information of one or more interfaces of each server and counting their performance indicators includes: in response to the call request of each interface, obtaining the call information of each interface through a behavior-oriented programming method; persisting the call information of each interface in a database; and using a big data component to count the persisted call information to obtain one or more performance indicators of each interface.

[0009] The second aspect of the present invention provides a server interface call indicator monitoring and statistical system, including: an acquisition module, used to obtain the call information of one or more interfaces of each server and count their performance indicators, the call information includes interface name, interface parameters, service name, call mode and input and output rate, and the performance indicators include TPS, QPS, average call time, throughput, access rate and call rate; a first adjustment module, used to obtain resource occupancy information and / or call information of each server, and dynamically adjust the load of its corresponding server; a second adjustment module, used to dynamically adjust the traffic of one or more interfaces of the server according to the QPS and response time distribution of each server interface.

[0010] The third aspect of the present invention provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors implement the server interface call indicator monitoring and statistical method provided in the first aspect of the present invention.

[0011] A fourth aspect of the present invention provides a computer-readable medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the server-side interface call indicator monitoring and statistical method provided in the first aspect of the present invention.

[0012] The beneficial effects of the present invention are:

[0013] Since servers provide services to the outside world through interfaces, monitoring interface calls can directly reflect the actual status of the server. Accurate data can not only provide developers with guidance on business optimization, but also provide server optimization suggestions for operation and maintenance personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A basic flow chart of a method for monitoring and counting indicators called by a server interface in some embodiments of the present invention;

[0015] Figure 2 A schematic diagram of the implementation architecture of a server-side interface call indicator monitoring and statistical method in some embodiments of the present invention;

[0016] Figure 3 A flowchart of a method for monitoring and counting call indicators of a registration interface in some embodiments of the present invention;

[0017] Figure 4 A schematic diagram of an implementation architecture for collecting interface call information at the server end in some embodiments of the present invention;

[0018] Figure 5 A schematic diagram of a process of dynamic adjustment of a server in some embodiments of the present invention;

[0019] Figure 6 A schematic diagram of a flow chart of adjusting the flow of an interface by a server in some embodiments of the present invention;

[0020] Figure 7 A schematic diagram of the structure of a server-side interface call indicator monitoring and statistics device in some embodiments of the present invention;

[0021] Figure 8 It is a schematic diagram of the structure of an electronic device in some embodiments of the present invention. DETAILED DESCRIPTION

[0022] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The examples given are only used to explain the present invention and are not used to limit the scope of the present invention.

[0023] refer to Figure 1 and Figure 2 In the first aspect of the present invention, a server interface call indicator monitoring and statistical method is provided, including: S100. Obtaining the call information of one or more interfaces of each server and counting their performance indicators, the call information including interface name, interface parameters, service name, call mode and input and output rates, the performance indicators including TPS, QPS, average call time, throughput, access rate and call rate; S200. Obtaining the resource occupancy information and / or call information of each server, and dynamically adjusting the load of the corresponding server; S300. Dynamically adjusting the traffic of one or more interfaces of the server according to the QPS and response time distribution of each server interface.

[0024] It should be noted that the server in the present disclosure generally refers to a server; without loss of generality, each server can be one or more virtual server images generated by a cloud server or a server cluster. Whether the server corresponds to a single physical server or a virtual server image, it does not affect the application of the method in the present disclosure. When a service or interface is distributed, the corresponding server corresponds to multiple servers. In the present disclosure, a certain interface corresponds to one or more services, and a service may also correspond to one or more interfaces; multiple services are arranged according to certain logical rules or executed according to the rules to form an application; usually, each application is executed on a process of the server, and each process can be executed concurrently through multiple threads.

[0025] It can be understood that TPS is the number of transactions processed per second by the interface. Taking the registration interface as an example, when calling the registration interface, user data will definitely be written. After the transaction is submitted, a transaction is completed. When Hadoop performs statistics, the registration interface name and transaction submission success are used as statistical indicators. All data that meet this requirement within 1 day are counted and finally converted into seconds. In this way, the actual TPS data can be obtained, and the interface call volume can be counted according to the time period to view the interface call peak.

[0026] QPS refers to the number of queries processed per second by the interface. Taking the login interface as an example, login involves a large number of user information queries. Hadoop uses the login interface name and query success as statistical indicators, and calculates the relevant data of QPS in the same way as above.

[0027] Interface call duration distribution uses a single interface name as a statistical indicator to calculate the total duration of all interfaces / total number of calls within a day, so as to obtain the average call duration of a single interface. At the same time, the maximum and minimum duration of a single interface in a fixed time period can be counted.

[0028] The success or exception call rate uses the return parameters of a single interface as the statistical indicator. The success call rate can be obtained by dividing the successful requests by the total number of requests per unit time. Similarly, the failure call rate = failed requests / total number of requests per unit time.

[0029] refer to Figure 2 In step S100 of the above embodiment of the present disclosure, the obtaining of the call information of one or more interfaces of each server and counting of their performance indicators include: S101. In response to the call request of each interface, obtaining the call information of each interface by a behavior-oriented programming method; S102. Persisting the call information of each interface in a database; S103. Using a big data component to count the persisted call information to obtain one or more performance indicators of each interface.

[0030] Specifically, in step S100 of the above-mentioned embodiment, the obtaining of the call information of one or more interfaces of each server and counting of their performance indicators include: S101. In response to the call request of each interface, obtaining the call information of each interface through a behavior-oriented programming method; S102. Persisting the call information of each interface in a database; S103. Using a big data component to count the persisted call information to obtain one or more performance indicators of each interface. When the server A and B interfaces are called, the interface call details (detailed information) are obtained through AOP (Action oriented programming), and the details are sent to the monitoring system asynchronously through the thread pool. After receiving the details, the monitoring system (receiver) extracts the interface name, interface parameters, service name, call method, IO rate and other data, and after the business processing is completed, the interface return data, interface time consumption, etc. are persisted to the database. Next, the data statistics component begins to perform data statistics on these interface data from the specified dimensions, such as the TPS of the write data interface, the QPS of the read data interface, the interface time consumption distribution (30%, 50%, 80% interface average time consumption), all interface throughput, interface normal access rate, abnormal access rate, interface call rate, etc. The data statistics component is generally implemented using big data components, such as HDFS distributed file system, HBase database, Hive data warehouse, streaming stream processing engine, Hadoop, Kafka, etc., and is the core of the data statistics of the entire monitoring system.

[0031] For example, reference Figure 3, taking the user registration interface as an example, the process of calling the above interface and counting its performance indicators is explained. After the user initiates a user registration request through the client, the server registration interface will be called. After the registration is completed, the interface input and output parameters and interface-related data will be sent to the monitoring system in the form of messages. After the monitoring system receives the data, it will be stored in the Hive data warehouse according to a specific format. The monitoring system will use Hadoop to statistically organize the data in the data warehouse within the set time period, such as interface TPS, QPS, average interface call time, interface throughput, normal call rate, abnormal call rate, etc. After the statistics are completed, the statistical data will be written to the HBase library for persistence. Finally, the statistical data is accessed through the view layer and displayed on the front-end page.

[0032] refer to Figure 4 In the embodiment based on the above steps, the process of collecting information on the service end (server) includes the following:

[0033] 1. Set up the monitoring software client to collect indicator information every 3 seconds and push server information to the middleware;

[0034] 2. The server starts the self-start monitoring program and connects to the middleware to maintain a long connection (persistent connection);

[0035] 3. After receiving the information, the middleware pushes it directly to the message queue;

[0036] 4. The message queue is consumed and saved to the database.

[0037] In step S200 of some embodiments of the present invention, the acquisition of resource occupancy information and / or call information of each server and the dynamic adjustment of the load of the corresponding server include: S201. Collecting the composition information, resource occupancy rate and current resource occupancy information of each service of each server; the composition information of the server includes CPU main frequency, memory bandwidth and disk space; S202. Based on the resource occupancy information and server resource occupancy rate of all services of multiple servers, the services whose resource occupancy rate exceeds the threshold in the current server are allocated to other servers.

[0038] Specifically, refer to Figure 5, based on the collected server information, server configuration information (including CPU and memory), server resource usage (disk, bandwidth, CPU usage, memory usage, corresponding service memory and CPU usage) information, automatically and evenly distribute applications to each server to run, and maximize the use of server resources; when server resources are insufficient, automatically start idle services or create new server resources. It can be understood that the above process is equivalent to the load balancing process, which usually corresponds to multiple servers or multiple server nodes, and multiple servers or multiple server nodes constitute a service cluster or data center.

[0039] In step S300 of some embodiments of the present invention, dynamically adjusting the traffic of one or more interfaces of the server according to the QPS and response time distribution of each server interface includes: S301. Counting the QPS and response time distribution of each server interface; S302. Removing one or more services with the shortest interface response time from the load balancing list; S303. If the response time of more than a preset number of interfaces among the remaining interfaces exceeds a threshold, determining whether a new server node needs to be added based on the number of concurrent application threads and the maximum number of supported threads of the server.

[0040] It can be understood that the above steps dynamically adjust the number of interface clusters based on interface monitoring data, QPS, server, CPU, memory, response time and other indicator data, and control interface traffic to the designated server for load balancing, and unify the interface traffic with low QPS to one service without participating in load balancing.

[0041] For further reference, Figure 6 In step S303, if the response time of the remaining interfaces exceeding the preset number exceeds the threshold, then judging whether a new server node needs to be added is performed according to the number of concurrent application threads and the maximum number of supported threads of the server, including: dividing the response time of the multiple interfaces into four intervals from small to large, and counting the proportion of each interval; if the response time of the interfaces exceeding the preset number falls within the maximum two intervals, judging whether a new server node needs to be added is performed according to the number of concurrent application threads and the maximum number of supported threads of the server.

[0042] For example, reference Figure 7 , the determining whether a new server node needs to be added according to the number of concurrent application threads and the maximum number of supported threads of the server includes: determining whether the ratio of the number of concurrent application threads corresponding to the interface to the maximum number of supported threads exceeds a preset value: if so, determining that a new server node needs to be added. The four intervals correspond to 0-1 seconds, 1-2 seconds, 3-4 seconds, and 4-5 seconds.

[0043] Example 2

[0044] refer to Figure 7 According to a second aspect of the present invention, a server interface call index monitoring and statistical system 1 is provided, comprising: an acquisition module 11, for acquiring the call information of one or more interfaces of each server and counting their performance indicators, wherein the call information comprises interface name, interface parameters, service name, call mode and input and output rates, and the performance indicators comprise TPS, QPS, average call duration, throughput, access rate and call rate; a first adjustment module 12, for acquiring the resource occupancy information and / or call information of each server, and dynamically adjusting the load of the corresponding server; a second adjustment module 13, for dynamically adjusting the traffic of one or more interfaces of the server according to the QPS and response time distribution of each server interface.

[0045] Furthermore, the first adjustment module 12 includes: a collection unit, which is used to collect the composition information, resource occupancy rate and resource occupancy information of each service end; the composition information of the server end includes CPU main frequency, memory bandwidth and disk space; an allocation unit, which is used to allocate the services whose resource occupancy rate exceeds the threshold in the current server end to other server ends according to the resource occupancy information and server resource occupancy rate of all services of multiple server ends.

[0046] Example 3

[0047] refer to Figure 8 According to a third aspect of the present invention, an electronic device is provided, comprising: one or more processors; a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method of the first aspect of the present invention.

[0048] The electronic device 500 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 501, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0049] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 8 The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead. Figure 8 Each block shown in the figure may represent one device, or may represent multiple devices as required.

[0050] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through a communication device 509, or installed from a storage device 508, or installed from a ROM 502. When the computer program is executed by the processing device 501, the above functions defined in the method of the embodiment of the present disclosure are executed. It should be noted that the computer-readable medium described in the embodiment of the present disclosure can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more conductors, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In an embodiment of the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, an apparatus, or a device. In an embodiment of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, an apparatus, or a device. The program code embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wire, optical cable, RF (radio frequency), etc., or any suitable combination of the foregoing.

[0051] The computer-readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device. The computer-readable medium carries one or more computer programs. When the one or more programs are executed by the electronic device, the electronic device:

[0052] Computer program code for performing the operations of embodiments of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, Python, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as a separate software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0053] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0054] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A server-side interface call indicator monitoring and statistical method, characterized in that: include: Obtain the call information of one or more interfaces of each server and count their performance indicators. The call information includes interface name, interface parameters, service name, call mode and input and output rate. The performance indicators include TPS, QPS, average call duration, throughput, access rate and call rate. Obtain resource usage information and / or call information of each server, and dynamically adjust the load of the corresponding server; According to the QPS and response time distribution of each server interface, dynamically adjust the traffic of one or more interfaces of the server: count the QPS and response time distribution of each server interface; One or more services with the shortest interface response time are removed from the load balancing list; if the response time of more than a preset number of interfaces among the remaining interfaces exceeds the threshold, determine whether a new server node needs to be added based on the number of concurrent application threads and the maximum number of supported threads on the server.

2. The server-side interface call index monitoring and statistical method according to claim 1, characterized in that: The obtaining of resource occupancy information and / or call information of each server and dynamically adjusting the load of the corresponding server includes: Collecting the composition information, resource occupancy rate and resource occupancy information of each service end; the composition information of the server end includes CPU main frequency, memory bandwidth and disk space; According to the resource occupancy information of all services of multiple servers and the server resource occupancy rate, the services whose resource occupancy rate exceeds the threshold in the current server are allocated to other servers.

3. The server-side interface call index monitoring and statistical method according to claim 1, characterized in that: If the response time of the remaining interfaces exceeding the preset number exceeds the threshold, judging whether a new server node needs to be added according to the number of concurrent application threads and the maximum number of supported threads of the server includes: Divide the response time of the multiple interfaces into four intervals from small to large, and count the proportion of each interval; If the response time of more than a preset number of interfaces falls within the two largest intervals, it is determined whether a new server node needs to be added based on the number of concurrent application threads and the maximum number of supported threads of the server.

4. The server-side interface call index monitoring and statistical method according to claim 3 is characterized in that: The determining whether a new server node needs to be added according to the number of concurrent application threads and the maximum number of supported threads of the server comprises: Determine whether the ratio of the number of concurrent application threads corresponding to the interface to the maximum number of supported threads exceeds the preset value: if so, determine that a new server node needs to be added.

5. The server-side interface call indicator monitoring and statistical method according to any one of claims 1 to 4, characterized in that: The obtaining of the call information of one or more interfaces of each server and counting the performance indicators thereof includes: In response to the call request of each interface, the call information of each interface is obtained through the behavior-oriented programming method; Persist the call information of each interface in the database; The big data component is used to collect statistics on the persisted call information to obtain one or more performance indicators of each interface.

6. A server-side interface call indicator monitoring and statistical system, characterized in that: include: An acquisition module is used to acquire the call information of one or more interfaces of each server and to count their performance indicators. The call information includes interface name, interface parameters, service name, call mode and input and output rate. The performance indicators include TPS, QPS, average call duration, throughput, access rate and call rate. A first adjustment module is used to obtain resource occupancy information and / or call information of each server and dynamically adjust the load of the corresponding server; The second adjustment module is used to dynamically adjust the traffic of one or more interfaces of the server according to the QPS and response time distribution of each server interface: count the QPS and response time distribution of each server interface; One or more services with the shortest interface response time are removed from the load balancing list; if the response time of more than a preset number of interfaces among the remaining interfaces exceeds the threshold, determine whether a new server node needs to be added based on the number of concurrent application threads and the maximum number of supported threads on the server.

7. The server-side interface call index monitoring and statistical system according to claim 6, characterized in that: The first adjustment module includes: A collection unit, used to collect the composition information, resource occupancy rate and resource occupancy information of each service end; the composition information of the server end includes CPU main frequency, memory bandwidth and disk space; The allocation unit is used to allocate services whose resource occupancy rate exceeds a threshold in the current server to other servers according to the resource occupancy information of all services of multiple servers and the server resource occupancy rate.

8. An electronic device comprising: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the server interface call indicator monitoring and statistical method as described in any one of claims 1 to 5.

9. A computer readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the server interface call indicator monitoring and statistical method as described in any one of claims 1 to 5 is implemented.

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