Efficiency insight method and device for water conservancy business product, and storage medium

Abstract

The invention discloses an efficiency insight method and device for a water conservancy business product and a storage medium, and the method comprises the steps: obtaining business resource use data, and carrying out the project dimension analysis of the business resource use data, so as to obtain resource relation optimization data; performing service cluster state monitoring on a preset service cluster to determine service cluster state parameters; performing environment service dimension analysis on the service cluster to obtain service adaptation parameters; obtaining workflow parameters, and performing efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters; according to preset project starting data, project deployment process parameters are determined through project dimension analysis; and based on the project deployment process parameters, service energy efficiency visual data is obtained through DevOps index analysis. According to the method, the technical problem that efficiency visualization and project full-life-cycle analysis cannot be realized on the construction condition of a business product in a water conservancy platform is solved.

Description

Technical Field

[0001] The present application relates to the technical field of water conservancy information management, and in particular to a method, device and storage medium for performance insight into water conservancy business products. Background Art

[0002] In recent years, with the continuous advancement of cloud computing and big data technologies, cloud-native applications have become a key force in promoting digital transformation in all walks of life. In the water conservancy industry, the application of cloud-native technologies has also shown great potential and value. In the process of water conservancy platform transformation to cloud-native, performance management has become a crucial link. Water conservancy platforms usually involve a large amount of real-time data processing, complex business logic, and cross-regional and cross-system data interaction, all of which place extremely high demands on the system's performance.

[0003] After users receive water conservancy business products, the construction of business products in the water conservancy platform needs to be evaluated so that users can compare different business products on the platform. Since users need to understand and track the business construction, progress, construction efficiency, etc. of business products, the business construction efficiency of the water conservancy business product platform needs to be fully understood and visualized. The existing technology cannot realize the performance visualization and full life cycle analysis of the construction of business products in the water conservancy platform. Summary of the invention

[0004] The embodiments of the present application provide a method, device and storage medium for performance insight into a water conservancy business product, which solves the technical problem that the construction of business products in a water conservancy platform cannot achieve performance visualization and full life cycle analysis of the project.

[0005] In a first aspect, an embodiment of the present application provides a method for gaining insight into the performance of a water conservancy business product, characterized in that the method includes: obtaining business resource usage data, and performing project dimension analysis on the business resource usage data to obtain resource relationship optimization data; performing business cluster status monitoring on a preset business cluster to determine business cluster status parameters; performing environmental service dimension analysis on the business cluster to obtain business adaptation parameters; obtaining workflow parameters, and performing efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters; determining project deployment process parameters through project dimension analysis based on preset project startup data; and obtaining business energy efficiency visualization data through DevOps indicator analysis based on the project deployment process parameters.

[0006] In one implementation of the present application, project dimension analysis is performed on business resource usage data to obtain resource relationship optimization data, specifically including: determining business resource consumption data through resource consumption analysis based on business resource usage data; tracking resource flow between businesses on the business resource consumption data to obtain resource consumption data between businesses; tracing resource dependencies on the business resource usage data to obtain business resource dependency data; and obtaining resource relationship optimization data based on the resource consumption data between businesses and the business resource dependency data.

[0007] In one implementation of the present application, a business cluster status is monitored for a preset business cluster to determine the business cluster status parameters, specifically including: performing a resource utilization analysis on the business cluster to determine the business resource utilization parameters; based on the business cluster, obtaining the business node health status through node health analysis; determining the scheduling efficiency data through cluster business scheduling efficiency evaluation based on the business node health status; and optimizing the cluster business status of the business resource utilization parameters, business node health status and scheduling efficiency data to obtain the business cluster status parameters.

[0008] In one implementation of the present application, an environmental service dimension analysis is performed on a business cluster to obtain business adaptation parameters, specifically including: monitoring the corresponding status of microservices in the business cluster to obtain the microservice response time; based on the microservice response time, determining the microservice quality parameters through microservice quality evaluation; wherein the microservice quality parameters include: microservice error rate parameters, microservice throughput parameters; performing environmental dimension judgment on the business cluster to determine the system environment status; determining the business adaptation parameters based on the microservice quality parameters and the system environment status.

[0009] In one implementation of the present application, an efficiency evaluation is performed on workflow parameters to obtain workflow efficiency optimization parameters, specifically including: performing a CI / CD workflow efficiency evaluation on workflow parameters to determine workflow efficiency data; obtaining key deployment parameters through bottleneck identification processing based on the workflow efficiency data; and containerizing the key deployment parameters to obtain workflow efficiency optimization parameters.

[0010] In one implementation of the present application, according to the preset project startup data, the project deployment process parameters are determined through project dimension analysis, specifically including: performing a build process analysis on the project startup data to obtain build process optimization parameters; wherein the build process analysis includes: build time monitoring, build success rate analysis; based on the build process optimization adoption number, the test quality data is determined through the test phase detection; wherein the test quality data includes: test coverage, test pass rate, execution time; according to the test quality data, the project deployment process parameters are obtained through deployment node analysis, wherein the project deployment process adoption number includes: deployment frequency, deployment success rate, rollback rate.

[0011] In one implementation of the present application, based on the project deployment process parameters, business energy efficiency visualization data is obtained through DevOps indicator analysis, specifically including: performing operation and maintenance deployment collaboration analysis on the project deployment process parameters to determine the deployment analysis parameters; wherein the deployment analysis parameters include: deployment time, deployment frequency; performing development failure status analysis on the project deployment process parameters to determine the change failure rate; and obtaining business energy efficiency visualization data based on the deployment analysis parameters and the change failure rate.

[0012] In one implementation of the present application, after obtaining business energy efficiency visualization data through DevOps indicator analysis based on project deployment process parameters, the method also includes: based on the business energy efficiency visualization data, obtaining a business construction update cycle through business implementation cycle iteration; according to the business construction update cycle, determining business optimization parameters through business construction quality analysis, and performing business construction updates on the business optimization parameters to obtain business iteration data.

[0013] In a second aspect, an embodiment of the present application also provides an efficiency insight device for a water conservancy business product, characterized in that the device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can: obtain business resource usage data, and perform project dimension analysis on the business resource usage data to obtain resource relationship optimization data; perform business cluster status monitoring on a preset business cluster to determine business cluster status parameters; perform environmental service dimension analysis on the business cluster to obtain business adaptation parameters; obtain workflow parameters, and perform efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters; determine project deployment process parameters through project dimension analysis based on preset project startup data; and obtain business energy efficiency visualization data through DevOps indicator analysis based on the project deployment process parameters.

[0014] On the third aspect, the embodiment of the present application also provides a non-volatile computer storage medium for performance insights of water conservancy business products, storing computer executable instructions, characterized in that the computer executable instructions are set to: obtain business resource usage data, and perform project dimension analysis on the business resource usage data to obtain resource relationship optimization data; perform business cluster status monitoring on preset business clusters to determine business cluster status parameters; perform environmental service dimension analysis on the business cluster to obtain business adaptation parameters; obtain workflow parameters, and perform efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters; determine project deployment process parameters through project dimension analysis based on preset project startup data; and obtain business energy efficiency visualization data through DevOps indicator analysis based on project deployment process parameters.

[0015] The embodiments of the present application provide a method, device and storage medium for performance insight into water conservancy business products. By building a water conservancy cloud-native integrated platform and performing performance insight analysis on the platform's business products, the technical problem that the construction of business products in the water conservancy platform cannot achieve performance visualization and project full life cycle analysis is solved, and performance insight and visualization of water conservancy business products are achieved, the life cycle analysis efficiency of the water conservancy cloud-native integrated platform is improved, and a data foundation is provided for optimizing the DevOps process. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings: Figure 1 A flow chart of a method for insight into the effectiveness of a water conservancy business product provided in an embodiment of the present application; Figure 2 A schematic diagram of the internal structure of an efficiency insight device for a water conservancy business product provided in an embodiment of the present application. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0018] The embodiments of the present application provide a method, device and storage medium for performance insight into water conservancy business products. By building a water conservancy cloud-native integrated platform and performing performance insight analysis on the platform's business products, the technical problem that the construction of business products in the water conservancy platform cannot achieve performance visualization and project full life cycle analysis is solved, and performance insight and visualization of water conservancy business products are achieved, the life cycle analysis efficiency of the water conservancy cloud-native integrated platform is improved, and a data foundation is provided for optimizing the DevOps process.

[0019] The technical solution proposed in the embodiments of the present application is described in detail below with reference to the accompanying drawings.

[0020] Figure 1 This is a flow chart of a method for analyzing the performance of a water conservancy business product provided in an embodiment of the present application. Figure 1 As shown, the embodiment of the present application provides a method for insight into the effectiveness of a water conservancy business product, which specifically includes the following steps: Step 101: Obtain business resource usage data, and perform project dimension analysis on the business resource usage data to obtain resource relationship optimization data.

[0021] Specifically, it includes: determining business resource consumption data through resource consumption analysis based on business resource usage data; tracking resource flows between businesses based on business resource consumption data to obtain resource consumption data between businesses; tracing resource dependencies on business resource usage data to obtain business resource dependency data; and obtaining resource relationship optimization data based on resource consumption data between businesses and business resource dependency data.

[0022] This application obtains business resource usage data and performs project dimension analysis on the business resource usage data to obtain resource relationship optimization data, thereby realizing project dimension resource status analysis of project products built in the water conservancy cloud-native integrated platform.

[0023] In the examples of the present application, detailed explanation is given by the following Example 1.

[0024] Example 1: The Water Conservancy Cloud Native Integrated Platform is a water conservancy cloud native all-in-one system that integrates cloud computing, containerization, microservice architecture, and automated operation and maintenance management functions. It aims to improve the construction efficiency, operation and maintenance convenience, and data security of the water conservancy industry information system.

[0025] On this platform, users can select corresponding business products according to their actual needs. For the platform, in the process of business product development, it is necessary to monitor and visualize the development process of business products to facilitate users to compare and monitor business products.

[0026] First, use monitoring tools such as Prometheus and Grafana to collect and analyze resource usage data in real time. Through feedback loops, performance bottlenecks can be discovered and resolved in a timely manner, resource allocation can be optimized, and resource waste can be avoided.

[0027] Then, by regularly conducting resource assessments, identify underutilized and over-configured resources, analyze resource usage data, understand the causes of costs, and find ways to reduce unnecessary expenses. Use elastic scaling services to dynamically adjust resources based on demand.

[0028] Finally, optimize server size, shut down unused resources, and use strategies such as reserved instances to reduce costs. Use tools such as dependency graphs to identify all dependencies of your application, including direct dependencies, indirect dependencies, third-party libraries, infrastructure, etc. Use a version control system (such as GitLab) to manage versions of dependencies to ensure that applications do not use outdated or conflicting versions.

[0029] Step 102: Monitor the status of a preset service cluster to determine service cluster status parameters.

[0030] Specifically, it includes: performing resource utilization analysis on the business cluster to determine the business resource utilization parameters; obtaining the business node health status through node health analysis based on the business cluster; determining the scheduling efficiency data through cluster business scheduling efficiency evaluation based on the business node health status; optimizing the cluster business status based on the business resource utilization parameters, business node health status and scheduling efficiency data to obtain the business cluster status parameters.

[0031] The present application implements business cluster status monitoring by monitoring the business cluster status of a preset business cluster to determine the business cluster status parameters, thereby improving the health status and scheduling efficiency of the business cluster.

[0032] In the examples of the present application, detailed explanation is given by the following Example 2.

[0033] Example 2: In container orchestration platforms such as Kubernetes (K8S), a business cluster refers to deploying multiple related applications together, using containerization technology to achieve high availability, scalability, and flexibility, thereby more effectively managing and running the business.

[0034] Therefore, in the process of building business products for the water conservancy cloud-native integrated platform, it is necessary to monitor cluster resource utilization, node health, scheduling efficiency, etc. to ensure efficient and stable operation of the cluster.

[0035] First, perform resource utilization analysis on the service cluster to determine the service resource utilization parameters. Based on the service cluster, perform node health analysis to obtain the health status of the service node.

[0036] Then, according to the health status of the service nodes, the scheduling efficiency data is determined through cluster service scheduling efficiency evaluation. The cluster service status is optimized for the service resource utilization parameters, the health status of the service nodes and the scheduling efficiency data to obtain the service cluster status parameters.

[0037] Step 103: Perform environmental service dimension analysis on the business cluster to obtain business adaptation parameters.

[0038] Specifically, it includes: monitoring the corresponding status of microservices in the business cluster to obtain the microservice response time; determining the microservice quality parameters through microservice quality evaluation based on the microservice response time; among which, the microservice quality parameters include: microservice error rate parameters and microservice throughput parameters; determining the environmental dimension of the business cluster to determine the system environment status; determining the business adaptation parameters based on the microservice quality parameters and the system environment status.

[0039] This application analyzes the business cluster from the perspective of environmental service dimensions to obtain business adaptation parameters, thereby evaluating and adjusting the quality of microservices and the business operating environment, and improving the adaptability and service quality of business products.

[0040] Step 104: Acquire workflow parameters and perform efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters.

[0041] Specifically, it includes: conducting CI / CD workflow efficiency evaluation on workflow parameters to determine workflow efficiency data; obtaining key deployment parameters through bottleneck identification and processing based on workflow efficiency data; and containerizing key deployment parameters to obtain workflow efficiency optimization parameters.

[0042] This application obtains workflow parameters and performs efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters, thereby optimizing the workflow and improving the workflow efficiency of business construction.

[0043] Step 105: Determine the project deployment process parameters through project dimension analysis based on the preset project startup data.

[0044] Specifically, it includes: conducting a build process analysis on the project startup data to obtain build process optimization parameters; wherein, the build process analysis includes: build time monitoring, build success rate analysis; based on the build process optimization adoption number, the test quality data is determined through testing in the test phase; wherein, the test quality data includes: test coverage, test pass rate, and execution time; based on the test quality data, the project deployment process parameters are obtained through deployment node analysis, wherein the project deployment process adoption number includes: deployment frequency, deployment success rate, and rollback rate.

[0045] This application determines the project deployment process parameters based on the preset project startup data through project dimension analysis, and realizes the visualization of project construction and other parameters.

[0046] In the examples of the present application, this is explained in detail through the following Example 3.

[0047] Example 3: Use a CI / CD process to ensure dependencies are managed throughout the development and deployment process. Use automated tools to build and deploy applications, including managing dependencies. Monitor dependencies to detect issues, and set up alerts to notify relevant personnel when problems arise.

[0048] Optimize resource allocation and project collaboration, and clarify resource requirements and priorities. At the beginning of a project, identify the resources required for the project, including hardware, software, and human resources. Assess the importance of each resource to the success of the project and set priorities accordingly.

[0049] Use automation tools (such as Kubernetes, Docker, etc.) to dynamically allocate and manage resources to improve resource utilization. Use IaC (Infrastructure as Code) tools to automatically configure and manage infrastructure to ensure consistency and repeatability of the environment.

[0050] Step 106: Based on the project deployment process parameters, business energy efficiency visualization data is obtained through DevOps indicator analysis.

[0051] Specifically, it includes: conducting operation and maintenance deployment collaborative analysis on project deployment process parameters to determine deployment analysis parameters; deployment analysis parameters include: deployment time and deployment frequency; conducting development failure status analysis on project deployment process parameters to determine change failure rate; and obtaining business energy efficiency visualization data based on deployment analysis parameters and change failure rate.

[0052] After obtaining the business energy efficiency visualization data through DevOps indicator analysis based on the project deployment process parameters, the method also includes: obtaining the business construction update cycle through business implementation cycle iteration based on the business energy efficiency visualization data; determining the business optimization parameters through business construction quality analysis according to the business construction update cycle, and performing business construction updates on the business optimization parameters to obtain business iteration data.

[0053] The above is an embodiment of the method proposed in this application. Based on the same inventive concept, the embodiment of this application also provides a device, whose structure is as follows Figure 2 shown.

[0054] Figure 2 This is a schematic diagram of the internal structure of a device provided in an embodiment of the present application. Figure 2 As shown, the device includes: at least one processor 201; and, a memory 202 communicatively connected to the at least one processor; The memory 202 stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor 201 to enable at least one processor 201 to: Obtain business resource usage data and perform project dimension analysis on the business resource usage data to obtain resource relationship optimization data; perform business cluster status monitoring on the preset business cluster to determine the business cluster status parameters; perform environmental service dimension analysis on the business cluster to obtain business adaptation parameters; obtain workflow parameters and perform efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters; determine the project deployment process parameters through project dimension analysis based on the preset project startup data; obtain business energy efficiency visualization data through DevOps indicator analysis based on the project deployment process parameters.

[0055] Some embodiments of the present application provide corresponding Figure 1 A non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured as follows: Obtain business resource usage data and perform project dimension analysis on the business resource usage data to obtain resource relationship optimization data; perform business cluster status monitoring on the preset business cluster to determine the business cluster status parameters; perform environmental service dimension analysis on the business cluster to obtain business adaptation parameters; obtain workflow parameters and perform efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters; determine the project deployment process parameters through project dimension analysis based on the preset project startup data; obtain business energy efficiency visualization data through DevOps indicator analysis based on the project deployment process parameters.

[0056] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the IoT device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0057] The system and medium provided in the embodiments of the present application correspond one-to-one to the method. Therefore, the system and medium also have similar beneficial technical effects to the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the system and medium will not be repeated here.

[0058] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0059] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0060] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0061] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0062] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0063] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0064] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0065] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0066] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A method for gaining insight into the effectiveness of a water conservancy business product, characterized in that: The method comprises: Acquire business resource usage data, and perform project dimension analysis on the business resource usage data to obtain resource relationship optimization data; Performing business cluster status monitoring on the preset business cluster to determine business cluster status parameters; Performing environmental service dimension analysis on the business cluster to obtain business adaptation parameters; Acquiring workflow parameters and performing efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters; According to the preset project startup data, determine the project deployment process parameters through project dimension analysis; Based on the project deployment process parameters, business energy efficiency visualization data is obtained through DevOps indicator analysis.

2. The method for obtaining an insight into the effectiveness of a water conservancy business product according to claim 1, characterized in that: Performing project dimension analysis on the business resource usage data to obtain resource relationship optimization data, specifically including: Based on the business resource usage data, determining business resource consumption data through resource consumption analysis; Tracking the resource flow between services on the service resource consumption data to obtain the resource consumption data between services; Tracing resource dependencies of the business resource usage data to obtain business resource dependency data; The resource relationship optimization data is obtained according to the inter-service resource consumption data and the service resource dependency data.

3. The method for obtaining an insight into the effectiveness of a water conservancy business product according to claim 1, characterized in that: Monitor the status of the preset business cluster to determine the business cluster status parameters, including: Performing resource utilization analysis on the service cluster to determine service resource utilization parameters; Based on the business cluster, obtaining the health status of the business node through node health analysis; According to the health status of the service node, determining the scheduling efficiency data through cluster service scheduling efficiency evaluation; Cluster service status optimization is performed on the service resource utilization parameter, the service node health status and the scheduling efficiency data to obtain the service cluster status parameter.

4. The method for obtaining an insight into the effectiveness of a water conservancy business product according to claim 1, characterized in that: Perform environmental service dimension analysis on the business cluster to obtain business adaptation parameters, including: Monitor the corresponding status of microservices in the business cluster to obtain the microservice response time; Based on the microservice response time, determine the microservice quality parameters through microservice quality evaluation; wherein the microservice quality parameters include: microservice error rate parameters and microservice throughput parameters; Performing environmental dimension determination on the business cluster to determine the system environmental status; The business adaptation parameter is determined according to the microservice quality parameter and the system environment state.

5. The method for obtaining an insight into the effectiveness of a water conservancy business product according to claim 1, characterized in that: Efficiency evaluation is performed on the workflow parameters to obtain workflow efficiency optimization parameters, specifically including: Performing a CI / CD workflow efficiency evaluation on the workflow parameters to determine workflow efficiency data; According to the workflow efficiency data, key deployment parameters are obtained through bottleneck identification processing; The deployment key parameters are containerized to obtain the workflow efficiency optimization parameters.

6. The method for obtaining an insight into the effectiveness of a water conservancy business product according to claim 1, characterized in that: According to the preset project startup data, the project deployment process parameters are determined through project dimension analysis, including: Performing a construction process analysis on the project startup data to obtain construction process optimization parameters; wherein the construction process analysis includes: construction time monitoring and construction success rate analysis; Based on the optimization adoption number of the construction process, the test quality data is determined through testing in the test phase; wherein the test quality data includes: test coverage, test pass rate, and execution time; According to the test quality data, the project deployment process parameters are obtained through deployment node analysis, wherein the project deployment process adoption number includes: deployment frequency, deployment success rate, and rollback rate.

7. The method for obtaining an insight into the effectiveness of a water conservancy business product according to claim 1, characterized in that: Based on the project deployment process parameters, business energy efficiency visualization data is obtained through DevOps indicator analysis, including: Performing operation and maintenance deployment collaborative analysis on the project deployment process parameters to determine deployment analysis parameters; wherein the deployment analysis parameters include: deployment time and deployment frequency; Performing development failure status analysis on the project deployment process parameters to determine the change failure rate; Based on the deployment analysis parameters and the change failure rate, the business energy efficiency visualization data is obtained.

8. The method for obtaining an insight into the effectiveness of a water conservancy business product according to claim 1, characterized in that: After obtaining the business energy efficiency visualization data through DevOps indicator analysis based on the project deployment process parameters, the method further includes: Based on the business energy efficiency visualization data, the business construction update cycle is obtained through business implementation cycle iteration; According to the service construction update cycle, the service optimization parameters are determined through service construction quality analysis. The business optimization parameters are updated through business construction to obtain business iteration data.

9. A performance insight device for water conservancy business products, characterized in that: The device comprises: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: Acquire business resource usage data, and perform project dimension analysis on the business resource usage data to obtain resource relationship optimization data; Performing business cluster status monitoring on the preset business cluster to determine business cluster status parameters; Performing environmental service dimension analysis on the business cluster to obtain business adaptation parameters; Acquiring workflow parameters and performing efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters; According to the preset project startup data, determine the project deployment process parameters through project dimension analysis; Based on the project deployment process parameters, business energy efficiency visualization data is obtained through DevOps indicator analysis.

10. A non-volatile computer storage medium for providing performance insights into water conservancy business products, storing computer executable instructions, characterized in that: The computer executable instructions are configured to: Acquire business resource usage data, and perform project dimension analysis on the business resource usage data to obtain resource relationship optimization data; Performing business cluster status monitoring on the preset business cluster to determine business cluster status parameters; Performing environmental service dimension analysis on the business cluster to obtain business adaptation parameters; Acquiring workflow parameters and performing efficiency evaluation on the workflow parameters to obtain workflow efficiency optimization parameters; According to the preset project startup data, determine the project deployment process parameters through project dimension analysis; Based on the project deployment process parameters, business energy efficiency visualization data is obtained through DevOps indicator analysis.

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