Container application performance analysis method and device, medium and product

Abstract

The invention provides a container application performance analysis method and device, a medium and a product. The method comprises the steps that a visual container performance management platform is built; an application deployment function is established on the visual container performance management platform, Docker file editing is carried out, an application program is imported, a mirror image is constructed, and a container is generated; establishing mapping between the container and a performance analysis tool; according to the method, a container principle is combined with a performance analysis tool, the operation performance of an application in a container is monitored and displayed in real time, the application process is controlled, and the performance resources of the container are regulated and controlled in combination with a cgroup technology. Performance analysis and the container are combined, the container is visualized and transparent, the utilization rate of the container is greatly improved, the analysis speed of a user on internal application of the container is shortened through visualized real-time monitoring on container hotspots, and a contribution is made to further improvement of the container performance.

Description

Technical Field

[0001] The present invention belongs to the field of computer technology, and in particular relates to a container application performance analysis method, device, medium and product. Background Art

[0002] With the development of container virtualization technology, more flexible deployment and management methods for traditional applications have been achieved, while resource isolation and restriction have also been achieved, meeting the needs of rapid deployment and application diversification. However, based on the characteristics of container technology, the deployment and operation of applications are relatively black box mode, and in many scenarios, real-time monitoring of system conditions is required to ensure the normal operation of applications.

[0003] The current defects are summarized as follows: 1) Application performance is easily affected by the system environment, and it is difficult to accurately analyze the causes of performance fluctuations.

[0004] 2) Each performance analysis tool has a single purpose and is cumbersome to use.

[0005] 3) Containers are relatively black-boxed and cannot achieve a transparent container operating environment. Summary of the invention

[0006] The purpose of the present invention is to provide a container application performance analysis method, device, medium and product, which can enable users to quickly deploy simple applications into containers and realize real-time performance monitoring of container hot spots.

[0007] In order to achieve the above object, the technical solution of the present invention is implemented as follows: A container application performance analysis method, comprising: Build a visual container performance management platform; establish application deployment functions in the visual container performance management platform, edit Dockerfile files, import applications, build images, and generate containers; establish a mapping between containers and performance analysis tools; combine container principles with performance analysis tools to monitor and display the running performance of applications in containers in real time; control the application process, and combine cgroup technology to adjust the monitored container performance resources in real time.

[0008] Furthermore, it also includes file management functions, which can mount the container locally, enter the mount namespace of the target process, and run bash to obtain a list of container files; or create a data volume to bind the directory in the container to share the files in the container externally.

[0009] Furthermore, the method for establishing a mapping between a container and a performance analysis tool includes: setting a performance analysis tool storage pool to store performance analysis tool information and deploy startup commands; setting a container information storage pool to store container information and management commands; and providing a visual interface to read performance analysis tool information and deploy it.

[0010] Furthermore, the method for real-time monitoring of the running performance of the application in the container includes: A performance data fusion pool is established to create a dashboard with the acquired performance attributes. The fusion pool includes performance attributes, data, time, and style, and makes a separate performance display for each application as well as a performance analysis and comparison of all applications. Thresholds are set for each performance attribute, and alarms are triggered if the data exceeds the threshold.

[0011] Another aspect of the present invention further provides a container application performance analysis device, comprising: A visual container performance management platform, which mainly includes: Application deployment unit: edit Dockerfile files, import applications, build images, and generate containers; Mapping unit: establishes mapping between containers and performance analysis tools; Real-time performance monitoring unit: It combines container principles with performance analysis tools to monitor and display the running performance of applications in the container in real time; Processing and scheduling unit: Controls the application process and uses cgroup technology to adjust the monitored container performance resources in real time.

[0012] Furthermore, it also includes a container unit, which includes file management, mounting the container locally, entering the mount namespace of the target process, and running bash to obtain a list of container files; or creating a data volume to bind the directory in the container to realize external sharing of files in the container.

[0013] Furthermore, the mapping unit includes: Performance analysis tool storage pool, which stores performance analysis tool information and deployment startup commands; Container information storage pool, used to store container information and management commands; Interface: Provides a visual interface to read performance analysis tool information and deploy it.

[0014] Furthermore, the real-time performance monitoring unit includes: Performance data fusion pool: The acquired performance attributes are used to create a dashboard. The fusion pool includes performance attributes, data, time, and style, and makes separate performance displays for each application and performance analysis and comparisons for all applications. Thresholds are set for each performance attribute, and data above the threshold is alarmed.

[0015] The present invention also provides a computer-readable storage medium, wherein the storage medium stores a computer program, and the computer program is used to execute the above-mentioned container application performance analysis method.

[0016] The present invention also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the above-mentioned container application performance analysis method is implemented.

[0017] Compared with the prior art, the present invention has the following beneficial effects: (1) The present invention proposes a container application performance management platform, which combines performance analysis with containers, visualizes containers, and makes them transparent, greatly improving the application rate of containers. By visualizing real-time monitoring of container hotspots, the user's analysis speed of applications inside the container is shortened, contributing to further improving container performance.

[0018] (2) The present invention can deploy the application environment, quickly deploy and run the application for verification, and save user deployment time.

[0019] (3) The present invention makes container operation transparent and simple, allowing users to adjust application status in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of implementing a visual container performance management platform in this embodiment. DETAILED DESCRIPTION

[0021] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0022] The present invention provides a method for analyzing program performance inside a container, by which an application with edited code can be quickly imported into a container, quickly deployed and compiled, and performance analysis can be performed on the CPU occupancy rate of the application running in the container, so as to monitor the normal operation of the container. The present invention can monitor container performance in real time, and also shorten the location time for quickly solving performance problems later.

[0023] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0024] like Figure 1 As shown, the container application performance analysis method proposed by the present invention includes: Build a visual container performance management platform, utilize the existing front-end and back-end separation technology, use the vue framework and other technologies on the front end to create a visual container performance management interface, and combine container technology, cgroup, and performance analysis technology on the back end to provide file management, performance monitoring and other functions.

[0025] The visual container performance management platform is provided with an application deployment unit for establishing a visual application deployment function. The application deployment unit sets a Dockerfile file auxiliary editing function for editing the instructions for automatically building Docker images in the Dockerfile file. Users can edit the image name, the imported file address, and can choose the platform's default base image or a custom image. The Dockerfile file auxiliary editing function can be a visual editing function. After editing, the instructions in the Dockerfile file are called to generate a container according to the parameter settings. And the container information can be copied. The application deployment unit specifically includes: 1) The platform front end automatically analyzes the type of application to be deployed and the automatic deployment capability of the application inside the container, that is, it searches for the application deployment related dependency tools and related dependency information in the container, returns data from the container to the front end, and the front end provides application configuration. When the application is imported into the container, the environment is automatically deployed according to the configuration.

[0026] 2) Search for the required packages in the container through commands based on the language type of the application, write the missing dependent files into specific file information, and use shared volume technology to achieve communication between the container and the host and transfer files.

[0027] 3) Call the new terminal interface in the management platform to provide a terminal interface for executing commands, and call the start container foreground running command to start the application inside the container in the management platform.

[0028] The visual container performance management platform is also provided with a container unit, which has a file management function. Through the container unit, application files can be imported from the platform to the container, container services can be started, and the internal files of the started container can be viewed through the container unit. The container unit uses the container to open the container file list after the container is generated, and provides functions such as visual operation of the container list, import, delete, and rename files. Its main technology is to mount the container directory to a local folder through the container running -v and other mount commands, enter the mount namespace of the target process, and run bash to obtain a visual container list. (Or you can also create a data volume to bind the directory in the container, and share the files in the container externally).

[0029] The visual container performance management platform is also provided with a mapping unit for associating performance analysis tools with containers. The mapping unit uses mounting technology to provide a container and performance analysis tool interface to deploy the performance analysis tool selected by the user into the selected container. In the mapping unit, 1) a performance analysis tool storage pool is set up, and a database storage method is used to store the installation method of each type of performance analysis tool installation package, related dependencies, and configuration performance analysis tool deployment startup commands; 2) a container information storage pool is set up, and a json file is used to store container information and visual container management commands; 3) a visual interface is provided to read the performance analysis tool information selected by the user to be deployed from the database, and then the performance analysis tool is deployed to the specified container according to the container technology.

[0030] The visual container performance management platform also provides a real-time performance monitoring unit, which uses the cgroup principle of container technology in combination with the performance analysis tool to obtain the occupancy of resources such as the CPU in the container, and the hot spot situation, and transmits the data in the container in real time through the shared volume, displays it through the interface, and performs early warning processing. In the real-time performance monitoring unit, 1) a performance data fusion pool is set up to create a dashboard for the obtained performance attributes such as CPU and memory, and analyze the application more comprehensively; 2) the performance data fusion pool consists of performance attributes, data, time, style, etc. Make a separate performance display for each application and compare the performance of all applications; 3) set a threshold for each performance attribute, and alarm for data above the threshold.

[0031] The visual container performance management platform also establishes a processing and scheduling unit. When encountering application problems, the processing and scheduling unit promptly processes the application, such as timely pausing applications with high CPU occupancy. Obtain applications whose CPU occupancy exceeds the threshold from the performance analysis tool, and execute a stop command outside the container. In the processing and scheduling unit, 1) a command interface is provided for each application, providing stop and run functions; 2) cgroup technology is used to control each container process to limit and tune the CPU / IO / memory performance, thereby adjusting the internal resources of the container from the outside.

[0032] The above-mentioned embodiments are only preferred implementations of the present invention, and are only used to help understand the method and core ideas of the present application. The protection scope of the present invention is not limited to the above-mentioned embodiments. All technical solutions under the idea of ​​the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A container application performance analysis method, characterized in that: include: Build a visual container performance management platform; establish application deployment functions in the visual container performance management platform, edit Dockerfile files, import applications, build images, and generate containers; Establish a mapping between containers and performance analysis tools; By combining container principles with performance analysis tools, the running performance of applications in containers can be monitored and displayed in real time. The application process can be controlled, and the performance resources of the monitored containers can be adjusted in real time by combining cgroup technology.

2. The container application performance analysis method according to claim 1, characterized in that: It also includes file management functions, which can mount the container locally, enter the mount namespace of the target process, and run bash to obtain a list of container files; or create a data volume to bind the directory in the container to share the files in the container externally.

3. The container application performance analysis method according to claim 1, characterized in that: The method for establishing a mapping between a container and a performance analysis tool includes: setting a performance analysis tool storage pool to store performance analysis tool information and deploy startup commands; setting a container information storage pool to store container information and management commands; and providing a visual interface to read and deploy performance analysis tool information.

4. The container application performance analysis method according to claim 1, characterized in that: The method for real-time monitoring of the running performance of an application in a container includes: A performance data fusion pool is established to create a dashboard with the acquired performance attributes. The fusion pool includes performance attributes, data, time, and style, and makes a separate performance display for each application as well as a performance analysis and comparison of all applications. Thresholds are set for each performance attribute, and alarms are triggered if the data exceeds the threshold.

5. A container application performance analysis device, characterized in that: include: A visual container performance management platform, which mainly includes: Application deployment unit: edit Dockerfile files, import applications, build images, and generate containers; Mapping unit: establishes mapping between containers and performance analysis tools; Real-time performance monitoring unit: It combines container principles with performance analysis tools to monitor and display the running performance of applications in the container in real time; Processing and scheduling unit: Controls the application process and uses cgroup technology to adjust the monitored container performance resources in real time.

6. The container application performance analysis device according to claim 5, characterized in that: It also includes a container unit, which includes file management, mounting the container locally, entering the mount namespace of the target process, and running bash to obtain a list of container files; or creating a data volume to bind the directory in the container to realize external sharing of files in the container.

7. The container application performance analysis device according to claim 5, characterized in that: The mapping unit comprises: Performance analysis tool storage pool, which stores performance analysis tool information and deployment startup commands; Container information storage pool, used to store container information and management commands; Interface: Provides a visual interface to read performance analysis tool information and deploy it.

8. The container application performance analysis device according to claim 5, characterized in that: The real-time performance monitoring unit comprises: Performance data fusion pool: The acquired performance attributes are used to create a dashboard. The fusion pool includes performance attributes, data, time, and style, and makes separate performance displays for each application and performance analysis and comparisons for all applications. Thresholds are set for each performance attribute, and data above the threshold is alarmed.

9. A computer-readable storage medium storing a computer program, characterized in that: The computer program is used to execute the container application performance analysis method according to any one of claims 1 to 4.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the container application performance analysis method according to any one of claims 1 to 4 is implemented.

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