31 results about "Operational costs" patented technology

The invention relates to the technical field of packaging, in particular to an intelligent metering method for remnant base paper rolls of a corrugated paper board assembly line. The intelligent metering method for the remnant base paper rolls of the corrugated paper board assembly line comprises steps as follows: a plurality of base paper feeding positions are arranged in the conveying direction of the assembly line at intervals, a base paper feeding frame is arranged in each base paper feeding position, and two base paper feeding rolls located on two sides of each base paper feeding frame are arranged on the base paper feeding frame; each base paper feeding roll is provided with lap recording sensors and incremental encoders, the lap recording sensors are used for monitoring the number of paper feeding laps of base paper clamped on the corresponding base paper feeding roll, the incremental encoders are used for monitoring the length of each lap after the base paper on the base paper feeding roll passes by one lap, and the lap recording sensors and the incremental encoders are connected with a controller. Intelligent metering can be realized, the operation cost of an enterprise is reduced, labor is saved, and the utilization rate of enterprise resources is increased.

The invention discloses an Internet of Things multi-stage communication method and system for city management, and relates to the technical field of Internet of Things communication, and the method comprises the following steps: monitoring the state of Internet of Things equipment, collecting the state data of the equipment, analyzing the historical use data of the Internet of Things equipment, and determining the data transmission demands of the Internet of Things equipment. According to the Internet of Things multi-stage communication method and system for city management, through the energy consumption and performance analysis module, the operation state and performance of the Internet of Things equipment are monitored and evaluated in real time, the energy consumption bottleneck and the performance decline sign of the equipment are identified, early warning is given out in time, and corresponding optimization measures are suggested to be taken, so that the city management efficiency is improved. The service life of the equipment is effectively prolonged, downtime and maintenance cost caused by equipment faults are reduced, meanwhile, parameter settings such as a dormancy awakening strategy are intelligently adjusted according to the actual use condition of the equipment, and the energy consumption and operation cost of the equipment are further reduced.

The invention relates to the technical field of high-performance computing resource management, and discloses a computing resource allocation method for a distributed supercomputing center. The method comprises the following steps: on the basis of obtaining real-time computing task and supercomputing center resource data and uniformly quantifying, integrally predicting resource requirements of future tasks; constructing a mixed integer linear programming model with the minimization of the total operation cost as a single target, wherein the total operation cost is the sum of the energy cost, the carbon emission cost, the data transmission cost and the SLA default penalty cost; solving the model by taking the time-varying electricity price, the green energy ratio, the resource capacity and the network parameters of each center as constraint conditions to generate an optimal resource allocation scheme; and then, by dynamically monitoring the resource state and the task progress, the model is triggered to resolve when the resource utilization rate is detected to be unbalanced or default risks, so that self-adaptive adjustment is realized. According to the invention, global collaborative resource allocation across super computing centers is realized, and operation economy, environmental sustainability and service reliability are considered.

The invention discloses a management method and system for a PUE value of a data center, relates to the technical field of data centers, and solves the problem that related parameters of operation equipment are not effectively adjusted based on energy consumption association change among different operation equipment. According to the energy consumption correlation ratio and the equipment energy consumption change data, whether the energy consumption change of other running equipment is abnormal or not can be quickly and accurately evaluated; corresponding and clear evaluation modes are provided for single-item and multi-item associated equipment sets, and once abnormal energy consumption equipment is determined, operation parameters of the abnormal energy consumption equipment can be adjusted in time, such as voltage and current reduction, so that the energy consumption is recovered to be normal; if the operation parameters are reduced to the lowest value and still cannot reach the standard, whether personnel intervention is needed or not can be determined by re-confirming the PUE value, and the hierarchical processing mode effectively guarantees the stability and reasonability of the energy consumption of the data center, improves the energy utilization efficiency, reduces the operation cost, and guarantees the efficient and stable operation of the data center.

The invention discloses a template turnover calculation application software design method based on an intelligent algorithm. The method comprises the steps that a data source is transferred from an original turnover area to a target area and from an excess material library to the target area; the fixing rule comprises template use frequency constraint, turnover constraint of different types of templates and leftover material definition; the variable rule comprises a turnover template carrying distance constraint and a turnover template cutting proportion constraint; turnover calculation, turnover object model pairing and paired model inner template calculation; and the turnover result gradually solidifies the rule according to different scenes. The method has the advantages that through the integrated calculation module, automatic calculation of the template turnover efficiency is achieved, manual intervention is not needed, and the calculation efficiency and accuracy are greatly improved; an advanced algorithm and a data processing technology are adopted, the accuracy of a calculation result is ensured, template turnover calculation requirements in different scenes can be met, and the resource utilization rate is improved and the operation cost is reduced by accurately calculating the template turnover efficiency.

The invention discloses a micro-service-based intelligent equipment management method and system, a medium and equipment, and the method comprises the following steps: S1, creating a micro-service management system which is responsible for equipment registration, equipment information storage and updating, real-time equipment operation state monitoring, equipment health data collection, and equipment sensor data collection through an Internet of Things protocol, a remote control instruction of a user is processed and issued to the equipment, and equipment faults are predicted by using a machine learning model; s2, equipment registration; s3, collecting equipment data; s4, equipment state monitoring; s5, user remote control; and S6, equipment fault prediction. The method has the advantages that the modules related to each step link can be independently developed and deployed, the development and online speed can be improved, the addition, modification and deletion of the equipment can be more quickly completed, the equipment management process is optimized, the equipment use efficiency is improved, the fault shutdown is reduced, the maintenance process is optimized, the operation efficiency is comprehensively improved, and the maintenance cost is reduced. Therefore, the total operation cost of an enterprise is reduced for a long time.

The invention discloses an application version release time consumption prediction method and apparatus, a device and a storage medium. The method comprises the steps of obtaining version information of a target application version; for each release link, determining a plurality of time consumption influence factors based on a target time consumption prediction model corresponding to the release link; based on the version information, determining factor values respectively corresponding to the plurality of time consumption influence factors; through a target time consumption prediction model, the release time consumption is predicted based on the factor value, and the release time consumption represents the manual time consumption for releasing the application version; the target time consumption prediction model is obtained based on the historical version release time consumption of the plurality of application versions in the release link and the plurality of time consumption influence factors through fitting. According to the embodiment of the invention, quantitative traceability of time consumption influence corresponding to a plurality of links can be realized, the accuracy of predicting release time consumption is improved, the actual optimization of an application version release process is guided, the delivery quality and the delivery efficiency of the application version are improved, and the optimal control of the operation cost is realized.

The invention discloses a resource scheduling method and a related device, relates to the field of software services, and determines the tenant category of a target tenant according to the attribute information of the target tenant and the similarity between preset tenant category clusters. And according to the tenant category and the tenant business required to be used by the target tenant, determining the content which needs to adjust the tenant feature adaptation of each tenant business according to the features of the tenant business. And then adjusting the attribute information according to the adjustment content so as to obtain each piece of adjusted attribute information. And according to the similarity between each piece of adjusted attribute information and the attribute information of each piece of platform service, determining the platform service correspondingly used by each tenant service. The platform service resources are distributed in a targeted mode according to the tenant attributes and the similarity between the tenant services needed by the tenants and the platform services, then reasonable distribution of the platform resources is effectively improved, and meanwhile the operation cost of the tenants can be reduced.

The invention discloses a credible low-cost reward method giving consideration to improvement of data quality and coverage rate, and aims to improve data quality, task coverage rate and cost control of crowd-sourcing network data collection. According to the method, a trust mechanism and an incentive strategy based on the task coverage rate and the data quality are introduced, and recovery of compensation reward is considered at the same time, so that the task coverage rate can be improved while workers are incentive to provide high-quality data, and the operation cost of a platform is remarkably reduced. Compared with the prior art, the method effectively solves the problems that the data quality is difficult to guarantee, the task coverage rate is insufficient and the cost is too high in the conventional method, so that the balance optimization of the data quality, the coverage rate and the cost control is realized while the requirements of different application scenes are met.

The invention relates to a method and a device for formulating a data element standard in the field of nuclear power station equipment, a storage medium and electronic equipment. The method comprises the following steps of formulating a data element standard template; identifying key factors formulated by a data element standard; according to the key factors for formulating the data element standard, determining a principle for formulating the data element standard; key data items are identified according to a rule formulated by a data element standard; and formulating a data element standard according to the key data item and the data element standard template. By making the data element standard, a set of unified data language is provided for the equipment management service of the nuclear power station, the understanding ambiguity is eliminated, the data integration is promoted, the barrier of a data island is broken, the data operation and maintenance difficulty is reduced, the data quality is improved, and effective support is provided for the equipment management service and analysis decision. In addition, accuracy and consistency of the data can be ensured, time and resources required to be invested due to data errors and inconsistency are reduced, working efficiency is improved, and operation cost is reduced.

The invention discloses an IT operation and maintenance management software operation monitoring method based on artificial intelligence, and relates to the technical field of intelligent operation and maintenance. The method comprises the following steps: constructing an IT operation and maintenance management overall framework; the overall architecture comprises a data acquisition layer, a communication layer, a data storage layer, a logic calculation layer and a user service layer. IT system data are collected in real time and preprocessed; classifying the data into basic data, operation data, security data, performance data and business data; establishing a BP neural network model to carry out operation and maintenance fault diagnosis, and obtaining a fault category, a fault position and a fault evaluation coefficient; fault reason judgment is carried out by utilizing association rule mining, and fault repair work is guided; comprehensive monitoring and intelligent operation and maintenance of the IT system are achieved, system faults can be diagnosed, performance bottleneck can be predicted, operation and maintenance efficiency and system stability are effectively improved, fault response time is shortened, operation cost is reduced, and meanwhile long-term efficient operation of the system is guaranteed through continuous performance optimization suggestions.

This invention provides a mine management system that can help improve the operating costs or efficiency of dump trucks in mines, even when sufficient operational data for dump trucks in mines has not been accumulated. [Solution] The mine management system 1 comprises a storage device 10 for storing the driving history of a dump truck 101, an information processing device 20, and a terminal device 3. If the driving history of an input route input from the terminal device 3 is not stored in the storage device 10, the information processing device 20 selects a route similar to the input route from among the routes for which the driving history is stored in the storage device 10 as a similar route, and calculates an estimated loading time, which is an estimated value of the loading time of the dump truck 101 on the input route, and an estimated waiting time, which is an estimated value of the waiting time of the dump truck 101 on the input route, based on the driving history of the similar route, and outputs the estimated loading time and estimated waiting time to the terminal device 3.

The invention provides a low-power-consumption storage system, method and device and a storage medium, and is applied to the technical field of computers, the system comprises a host and a host bus adapter HBA, and the host is connected with the HBA through a PCIe bus; the HBA comprises a first controller, a processor unit and a cache unit, and the first controller is used for obtaining a first target request from a submission queue of a host memory; the cache unit is used for storing to-be-processed information carried by the first target request; the processor unit is used for processing the to-be-processed information and generating response information of the to-be-processed information according to the type of the first target request; and writing the response information into the cache unit, and feeding back the response information to a completion queue of the host memory. According to the technical scheme, a transmission mechanism is optimized, so that power consumption is greatly reduced, the operation cost pressure is relieved, and heat is reduced so as to reduce heat dissipation cost. And high-efficiency data transmission and system stability are guaranteed in performance.

The present invention relates to a system (120) and method (400) for predicting the one or more anomalies associated with one or more UEs (110) is disclosed The system (120) includes a receiving unit (220) configured to receive a first set of data corresponding to each of the one or more UEs (110) from one or more data sources. The system (120) includes a training unit (225) configured to train a model utilizing the received data to identify trends in the received data. The system (120) includes a predicting unit (230) configured to predict the one or more anomalies based on the identified trends in the received data. The system (120) optimizes resource allocation, minimizing operational costs and resource wastage.

The invention discloses a cost reimbursement transparent tracking method, device and equipment and a storage medium, and the method comprises the steps: verifying the user identity of a current user, and allowing the user to submit a reimbursement application after the verification is passed; after the reimbursement application is received, auditing the reimbursement application, and recording an auditing result on a block chain; when the auditing result is that auditing is passed, a fund payment instruction is triggered, reimbursement funds are paid to the current user, and a reimbursement tracking auditing report is generated, so that automation, transparency and high efficiency of a cost reimbursement process can be realized, the transparency of the reimbursement process is improved, the operation cost of an enterprise is reduced, and the user experience is improved. The method has high practical value and market prospect, can effectively prevent data from being tampered, thereby reducing fraud and errors, improves the robustness and anti-attack ability of the system through decentration, and improves the speed and efficiency of expense reimbursement transparent tracking.

The embodiment of the invention provides an automatic data processing method and device, equipment, a medium and a product, and the method comprises the steps: obtaining a marked service type in response to an automatic data processing event; automatically adjusting the service data according to the automatic execution processing logic of the service type; in response to the fact that the automatic adjustment result is limited adjustment, generating a to-do task based on the first data which does not execute the automatic adjustment; and when the first data in the to-do task meets the limiting factor and the next automatic processing event is detected to be met, continuing to perform automatic processing on the first data. According to the technical scheme, when automatic data processing of the data is limited and adjusted, the to-do task is generated, automatic processing continues to be executed in the next automatic processing event, processing which cannot be completed in time is managed by a system queue and automatically retried, manual intervention and operation cost are reduced, and the efficiency of data processing is improved. And the effect of improving the completion rate of automatic treatment is achieved.

The invention relates to an edge container deployment and power distribution service quick response method. The method aims at the technical field of power systems and information, fully considers the response time, resource utilization rate, error rate and data consistency of micro-services, constructs micro-service processing quality indexes, expands or shrinks the capacity of a container based on the processing quality of the micro-services in the container, predicts the number of the micro-services by using historical data, and improves the quality of the micro-services. The capacity of all the containers is expanded or shrunk uniformly, so that the system adapts to the long-term change trend, resource overload and performance bottleneck are avoided, and the stability and reliability of the system are improved by reducing over-configured resources and reducing the operation cost. Allocating containers for the app based on the micro-service quantity and the data quantity generated by the app in the current time slot and the container computing resources, and allocating the micro-service quantity processed by each container according to the micro-service processing index of the last time slot of the container, according to the method, the saturation degree of each container under an initial allocation strategy is calculated based on the micro-service data volume, the data complexity, the computing resources, the CPU occupancy rate and the storage resources, and the deployment strategy of the edge containers in the same app is adjusted based on the saturation degree of each container, so that unnecessary container migration is reduced, the continuity and consistency of services are kept, the user experience is improved, and the user experience is improved. Therefore, the quick response of the power distribution service is realized.

The present invention relates to the field of engineering management technology, and discloses a management system and method for project supply materials supplied by the first party. The system includes: an interactive module for obtaining supply materials management instructions and sending the supply materials management instructions to the project supply materials management module; the project supply materials management module is connected to a database module and an interactive module, respectively, and is used to call multiple business type data stored in the database module based on the supply materials management instructions, and use RPA automated scripts based on the business type data to perform acceptance management, allocation and accounting management of the supply materials supplied by the first party. The present invention effectively avoids human errors that may exist in manual operations, ensures data accuracy, improves the management efficiency of project supply materials supplied by the first party, and helps reduce the operating costs of enterprises.

A system for calculating revenue, costs, and margin per man-month for project management, consisting of: a data acquisition module with a data input interface configured to capture or receive project-related financial data, personnel data, and operating cost data from multiple sources and users; a workforce classification module that includes a classification processor configured to categorize the workforce into overseas employees, domestic employees, and third-party hired employees, and calculates man-months for each category separately based on standard working hours and rest and rotation leave cycles; a central calculation module connected to the data acquisition module and comprising an artificial intelligence processor connected to a memory to perform calculations of revenue, costs and margin, wherein the central calculation module comprises the following: a revenue calculation unit configured to: calculate total revenue from multiple sources, including unit rates, labor costs, subcontract revenue, and material delivery revenue; calculate net revenue by subtracting subcontract and material revenue from total revenue; and determine revenue per man-month by dividing net revenue by the total number of man-months; a cost accounting unit configured to: aggregate direct and indirect costs, including consumables, own personnel costs, personnel rental costs, food and accommodation costs, own equipment and vehicle costs, third-party vehicle and rental costs, fuel costs, general expenses, and depreciation; exclude material costs, subcontracting costs, and financing costs from the cost per man-month calculation; and calculate the cost per man-month by dividing the total costs by the total number of man-months; a margin calculation unit configured to: calculate the gross margin by subtracting total personnel costs from net sales; calculate the net margin by further subtracting financing costs, individual business unit overheads, and corporate overheads from the gross margin; and determine the margin per man-month based on the calculated net margin; a benchmarking analysis module that is connected to the central calculation module and offers the following configuration: regular benchmarking analyses of revenues, margins and costs per man-month on a project basis, comparison of financial key figures of similar projects and multiple locations, and identification of performance deviations, trends and inefficiencies; a reporting module that is connected to the benchmarking analytics module and configured to generate monthly benchmarking reports for management, including rolling forecasts and variance analyses; and A user interface module that is connected to the central calculation module, the benchmarking module, and the data entry module, and is configured to: display calculated results for revenue, cost, and margin per man-month; present benchmarking analysis results and performance metrics; provide input forms for data entry and system configuration; and generate monthly benchmarking reports and rolling forecasts for user review.

This invention relates to a dynamic data masking strategy allocation method and system based on data usage paths. The method acquires the data usage path from the data source to the data output end, inputs the data usage path into a pre-configured strategy allocation engine, performs structured parsing based on the key characteristics of the data usage path, and dynamically matches the corresponding data masking strategy based on the parsing results to perform data masking processing. The system includes a path acquisition module, a strategy allocation module, and a strategy execution module, with the strategy execution module decoupled from the business logic. This invention ensures data availability while meeting compliance requirements, significantly improves system adaptability and scalability, reduces operating costs, and has strong scenario adaptability, especially for closed-source tasks. It enables centralized reuse and simplified configuration of masking logic, facilitates maintenance, and reduces the degree of intrusion into existing business system code; it also improves data security and usage compliance, meeting the masking needs of diverse usage scenarios.

The embodiment of the application provides a kind of electromechanical equipment regulation and control method and system, it is related to electromechanical equipment management technical field.The method uses user equipment as computing node to greatly reduce additional hardware investment, it is convenient to expand electromechanical equipment regulation and control system along with the increase of user number, while reducing operating cost, improve system scalability.User equipment completes privacy processing of sensitive data locally, generates spatial information containing space number and crowd type information, only needs to upload spatial information to regulation and control platform, does not need to upload all user data, can reduce data transmission volume, reduce network delay, improve the real-time performance and efficiency of data processing, while effectively guaranteeing user information security.Regulation and control platform directly regulates and controls electromechanical equipment corresponding to space mark according to the spatial information uploaded by each user equipment, to ensure that regulation and control platform responds to environmental changes in real time under low load, so as to improve energy efficiency and environmental comfort.

The present invention discloses a digital twin method and system for edge computing, wherein the method includes: using an external network to network a MEC physical system with a digital twin of the MEC system; the MEC physical system is communicated through an external network based on information, and the digital twin of the MEC system is communicated through an external network to monitor the MEC physical system to obtain monitoring results, and the monitoring results are analyzed and evaluated to obtain evaluation results, so as to complete the mirroring of the MEC physical system; and the constructed MEC physical system is digitally twinned, and the closed-loop optimization control of the MEC physical system is completed based on the evaluation results; the unconstructed MEC physical system is digitally twinned, and the optimization design of the MEC physical system is completed based on the evaluation results. The present invention can continuously optimize the MEC physical system through the digital twin of the MEC physical system, improve the management efficiency and resource utilization efficiency of the system, and reduce the operating cost and investment expenditure cost of the MEC service.

The present application discloses a mobile base station computing power management method and related devices, which relate to the field of software technology, monitor the system load of the mobile base station, and predict the load change trend of the mobile base station based on the historical system load closest to the current moment; if the load change trend is no-load, determine the first computing task to be executed, allocate the first container resource matching its task type to the first computing task in the resource pool of the mobile base station, and execute the container instance of the first computing task based on the first container resource; if the load change trend is overload, determine the second computing task in execution, release the second container resource occupied by the second computing task, and recycle the computing power resources of the resource pool by adjusting the capacity size of the resource pool. Under the premise of ensuring the normal operation of communication services, the present application maximizes the use of idle computing power resources of mobile base stations, efficiently processes computing tasks, optimizes resource utilization, and reduces the operating cost of edge computing.

The invention discloses a multistage phase change air cooling coupling server intelligent control system, and belongs to the technical field of server heat dissipation. Through combination of the multi-stage phase change cooling device, the air cooling condensation device, the intelligent control module, the fault monitoring and self-recovery system, the user interaction interface and remote monitoring module and the data recording and analysis function module, accurate control and optimization of the heat dissipation requirement of the server are achieved, the stability and reliability of the server are improved, and the service life of the server is prolonged. The method also reduces the energy consumption and operation cost, provides a powerful guarantee for the efficient operation of the server, guarantees the safe and stable operation under various conditions through the real-time monitoring and adjustment of the operation state of the data center, reduces the demands of manual intervention through the self-learning and self-adaptive capabilities of the intelligent control system, and improves the safety of the data center. Therefore, the maintenance cost is reduced.

The invention discloses a production scheduling method based on an NB-IoT (Narrow Band Internet of Things) acquisition technology. The method comprises the following steps: carrying out legality verification on accessed equipment, dynamically distributing network resources to equipment in a queue to be processed, locally processing data by utilizing an edge computing technology, dynamically adjusting the bandwidth of the equipment according to real-time requirements, and sending the network resources to the equipment in the queue to be processed. A machine learning algorithm is used to predict production abnormity and adjust a production plan in advance, and a data caching function is set at an equipment end. According to the invention, the demand of manual intervention is reduced through automatic scheduling, and finally, the production efficiency is greatly improved and the operation cost is effectively reduced.

The invention relates to a double-recording system design method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining at least one target service, recognizing the service function of each target service, dividing a service function recognition result, obtaining a function set of each target service, and storing the function set of each target service; generating a service configuration rule corresponding to the function set of each target service, and designing a workflow template of each target service according to the service configuration rule, and when the workflow template of each target service meets a preset approval condition, executing the approval operation of each target service; and controlling the workflow template of each target service to execute the corresponding target service based on the service configuration rule, thereby solving the problems of poor experience, frequent problems, too high operation cost and the like of an agent and a client in a double-record sales process, and by carrying out modular splitting on complex services, by adopting a double-dimensional node model and a each-dimensional rule model, the service performance of the agent and the client is improved. Therefore, a three-party mechanism can access the double-recording system to carry out self-defined configuration, and the understanding capability of service visual configuration is improved.

The present application provides a multi-data center management method, device, equipment, and storage medium, which belongs to the field of data center microgrid scheduling. The management method includes: obtaining a first predicted value of renewable energy, a second predicted value of thermal energy demand, and a third predicted value of workload of each data center microgrid in the multi-data center microgrid; determining the operating cost of the multi-data center microgrid based on the first predicted value and the second predicted value; determining the data migration constraint based on the third predicted value; optimizing the operating cost of the multi-data center microgrid based on the data migration constraint, and obtaining the data migration status between each data center microgrid and the workload response status of each data center microgrid. The embodiment of the present application can effectively reduce the operating cost of the multi-data center microgrid architecture while maintaining the stability of the multi-data center microgrid system.

The invention provides a non-standard equipment information management and control method and device, which can be used in the technical field of artificial intelligence, and the method comprises the steps: carrying out the conflict detection of received input attribute information through an attribute constraint relation in a pre-constructed non-standard equipment information organization structure; if the input conflict is detected, generating a conflict correction message; if the input conflict is not detected, writing the input attribute information into a non-standard equipment information organization structure, and generating a non-standard equipment information organization model; according to the input query elements, the non-standard equipment information organization model is matched, the non-standard equipment information query result is generated, the non-standard equipment information organization structure can be dynamically adjusted according to the process requirements, the requirements for flexibility and variability of the non-standard equipment component structure are met, and the non-standard equipment information query efficiency is improved. Information sharing of the non-standard devices is achieved through the non-standard device information organization structure, the data structure is simplified, the retrieval efficiency is improved, and therefore the operation cost and the time cost of an enterprise are reduced.

The embodiment of the present invention discloses an information processing method, device and energy storage system, the method comprising: collecting status information of key components in the energy storage system; the status information comprises electrical parameters and usage data; performing status evaluation on the key components according to the collected status information combined with preset evaluation conditions to obtain status evaluation results reflecting the current status of the key components; performing corresponding processing on the key components according to the status evaluation results and preset processing strategies. Through the above method, the life of components in the system can be predicted, which is convenient for maintenance personnel to maintain the system in time, and the system can automatically handle faults after faults occur, thereby reducing operating costs and improving the safety of the system.

The present invention belongs to the technical field of network monitoring services, and discloses a microservice link tracking and performance analysis method, system, device and application. The microservice link tracking and performance analysis method is based on the microservice architecture, and provides a variety of integration methods for microservices. Microservices can be integrated into the system according to the actual environment and hardware conditions; there is no intrusion into the microservices, and the microservices can be combined with service logs and probes to analyze the complete link of requests and responses in real time, and conduct a comprehensive evaluation of the link. The present invention supports three integration methods. During integration, there is no intrusion into the microservices; and in the process of monitoring link information, it does not affect the user experience, and can ensure that the link information analysis of the service is met without occupying too much system resources; it improves the overall operation and maintenance capabilities of the system, and saves operation and maintenance and operating costs for enterprises. Automatically display services, endpoints, and functions with lower performance, without manual intervention throughout the process.