100 results about "Deployment environment" patented technology

The invention discloses an intelligent file service system generation method based on a low-code development mode. The method comprises the following steps: constructing a file service core data model, defining file metadata fields, a storage structure and an association relationship, and forming a standardized data architecture. According to the method, the core data model, the visual page component library and the drag-and-drop workflow template are constructed, linkage binding of data-component-process is achieved in combination with a low-code engine, and the efficiency bottleneck of a traditional development mode is broken through; through a three-way real-time synchronization mechanism, real-time hot repair and dynamic branch judgment, page layout and flow rule adjustment can take effect immediately through visual configuration, and the problem of dynamic demand response lag is solved; through the intelligent resource scheduling logic compiled through environment adaptation, a differentiation scheme is generated for different deployment environments, the configuration difference influence under a private cloud and server mixed deployment scene is remarkably reduced, the deployment failure rate is greatly reduced, and the system online stability is improved.

The invention discloses a heterogeneous document structured data extraction system and method based on multi-modal fusion, and the method comprises the following steps: S1, receiving a heterogeneous document, and carrying out the preprocessing; s2, extracting visual and semantic modal information based on the visual backbone network and an OCR module, and fusing spatial coordinates, text content and layout features; s3, receiving a dynamic target mode Schema, executing field-level semantic matching, and calculating semantic similarity; s4, performing consistency verification, verifying and filling the field values, and correcting the associated fields; s5, converting the format into a data file in a specified format, and reserving fields to be mapped with an original document semantic block; s6, automatically switching a cloud mode and a local mode according to a deployment environment; and S7, outputting the data file of the target field. According to the method, high-precision and low-delay structured data extraction of the heterogeneous format document can be realized, and the automatic processing efficiency and the data credibility are improved.

The invention provides a software deployment method which can be applied to the technical field of artificial intelligence. The software deployment method comprises the following steps: in response to received code data uploaded by a user, analyzing the code data to obtain a dependency relationship among software items in the code data, and determining a priority corresponding to the dependency relationship; according to the priorities, the software projects are constructed in sequence to generate target software; according to the deployment requirement of the target software, searching from a pre-constructed knowledge base to obtain configuration information matched with the deployment requirement, and configuring a target deployment environment according to the configuration information; and extracting deployment parameters from the target deployment environment, and deploying the target software to the target deployment environment according to the deployment parameters. The invention further provides a software deployment device and equipment, a medium and a program product.

The invention discloses a multi-model intelligent management scheduling method and system. The method comprises the following steps: receiving a to-be-registered model and corresponding metadata, and executing integrity check to generate an integrity check result; generating a model identifier for the to-be-registered model according to an integrity check result, and storing the model identifier into a model storage warehouse; receiving a deployment request, and extracting a target model file and target metadata according to the deployment request; selecting a target computing node according to the target metadata; configuring a running environment according to a deployment environment requirement, and combining the target model file with the running environment to obtain a container mirror image; creating a containerized operation instance based on the container mirror image, and configuring a network access endpoint; predicting the page view of the network access endpoint to obtain predicted page view data; and adjusting the number of the containerized operation instances according to the predicted page view data and the system resource use data. By implementing the technical scheme, the problems of hysteresis and lack of perspectiveness of resource adjustment based on a real-time system load are solved.

The invention discloses a Web-based visual editing method, belongs to the technical field of industrial configuration, and aims to solve the problems of complex deployment of traditional configuration software and insufficient Web scheme performance. The method comprises the following steps: constructing a front-end architecture (Vue. Js + Konva.js) containing a graphic element module, a canvas management module and the like; the primitive adopts JavaScript prototype chain inheritance + SVG / Canvas double-layer rendering, and a canvas is divided into four layers and is provided with a quadtree index; an editor and an expression engine are generated by using a factory pattern for attribute configuration; page management supports state capture recovery; real-time communication is based on WebSocket + PubSub, and data aggregation and incremental updating optimization are combined. Cross-platform zero deployment and Web environment near-desktop performance are achieved, editing efficiency is improved, industrial protocols such as OPC UA are compatible, and the method is suitable for the field of energy and intelligent manufacturing.

An MLOps extension method and apparatus in a multi-cloud native environment, and a medium, relating to the technical field of multi-cloud heterogeneity. The method comprises: receiving a user-defined infrastructure template, configuration parameters, and access credentials of different cloud platforms, and collecting cloud computing resources from a plurality of clouds; putting model code and a data processing script into a version control system, and uploading data to a data storage service; pre-allocating computing resources and storage resources, and installing and verifying all dependencies in a pre-deployment environment; creating isolated sandbox environments on the cloud platforms to run comprehensive simulation tests; packaging models and applications, and deploying same in production environments on the cloud platforms; configuring a monitoring tool to monitor the performance of the models and the applications in real time, and on the basis of monitoring data, optimizing model parameters and application configurations. The present invention can reduce incompatibility and failures in a multi-cloud environment, and improve the reliability and efficiency of model services and continuous application deployment.

The invention provides a PXE network card initialization method and device compatible with 64-bit addressing and a medium, and relates to the technical field of network card initialization, and the method comprises the steps: discovering a network card device; reading a PCI configuration space of the network card equipment, obtaining information of an extended ROM base address register, and mapping a network card Option ROM to a memory shadow region; when the access of the memory mapping input and output mode fails, the initialization code performs read-write operation on the hardware register through a self-defined capability structure in a PCI configuration space of the network card equipment; based on the successfully accessed hardware register, network card hardware initialization is completed, and a PXE protocol stack structural body is established in a memory; registering system firmware as PXE starting equipment, and entering a protocol interaction stage with a PXE server; according to the invention, smooth development of a subsequent network boot flow is guaranteed, and the deployment success rate and the system stability in a large-scale batch installation scene are improved.

The present application provides a cloud-edge collaborative 1+6+N smart thermal power plant intelligent infrastructure system and deployment method. The system comprises: a lightweight IaaS layer, a lightweight PaaS layer, and a lightweight SaaS layer. The lightweight IaaS layer is used for a user to independently deploy and run any software or application program, to implement basic computing, storage, and calling of network resources for the smart thermal power plant intelligent infrastructure system. The lightweight PaaS layer is used to configure an application program development and deployment environment for any software or application program deployed by the user, and to access data of a terminal sensing device and a control device of the smart thermal power plant intelligent infrastructure system. The lightweight SaaS layer is used to deploy applications and services used in the smart thermal power plant intelligent infrastructure system in the form of a microservice architecture, to meet various service requirements of the smart thermal power plant intelligent infrastructure system. The technical problems of how to provide an efficient, safe and visual solution for improving infrastructure management, operation and maintenance of a thermal power plant, and how to significantly improve the infrastructure management level and efficiency of operation and maintenance the power plant, are resolved.

The invention discloses a Java JAR packet encryption protection method and device, equipment and a medium, and the Java JAR packet encryption protection method comprises the steps: splitting a JAR packet decryption key into two fragments, and statically storing the two fragments in a starter program and a dynamic link library in a nonlinear confusion structure, thereby avoiding the exposure of a key plaintext. During starting, the starter transmits the first secret key fragment to the dynamic link library through secure inter-process communication, and the first secret key fragment is combined with the second fragment in the memory to restore a complete secret key. And during class loading, the Java agent intercepts a request and transmits an encrypted class byte code to the dynamic link library through the JNI, the encrypted class byte code is decrypted by using the restored key, and a plaintext is returned for loading. According to the method, static decompilation and dynamic memory dump attacks are prevented, and the anti-reverse and anti-leakage capabilities of Java software in a privatized deployment environment are remarkably improved.

The application relates to the technical field of data center computer room energy-saving, and discloses a computer room cold aisle sealing management method, a device and terminal equipment, the method comprises the following steps: obtaining a cold aisle state through a deployment environment monitoring node, constructing a heat-flow coupling model and a stability function, designing a feedback controller to generate a damper and refrigeration control instruction, realizing linkage regulation of air flow rate and temperature, constructing a closed-loop control, and realizing efficient energy-saving management of the cold aisle; the device comprises an environment monitoring module, a state modeling module, a stability evaluation module, a state feedback control module and an execution linkage module. Through state fusion updating, component control structure, stability function driving strategy and linkage execution mechanism, the application realizes fine adjustment and efficient collaborative control of the cold aisle temperature and airflow, improves regulation stability and response efficiency, significantly reduces energy consumption, and solves the problems of poor control precision and weak linkage of the existing system.

The invention provides a fault root cause positioning method and device and electronic equipment, and belongs to the technical field of artificial intelligence. The fault root cause positioning method provided by the embodiment of the invention comprises the following steps: identifying an architecture type of a deployment environment to which a micro-service cluster belongs, and determining a corresponding architecture type confidence coefficient according to the architecture type; obtaining operation data and environmental factor data of the micro-service cluster, determining fault features of the micro-service cluster according to the operation data and the environmental factor data, and determining a fusion weight vector according to the operation data, the environmental factor data and the architecture type confidence; and using the fault features of the micro-service cluster, the fusion weight vector and the architecture type to construct a cue word, and using a preset large language model to infer the fault root cause of the micro-service cluster according to the cue word to obtain a fault root cause result. The fault root cause positioning method can improve the accuracy of fault root cause positioning.

This application provides a satellite ephemeris configuration method, a service support system, a satellite network system, a terminal device, a storage medium, a chip system, and a program product, relating to the field of communication technology. This application writes satellite ephemeris data into a user identification card (BIC), allowing the terminal device to obtain ephemeris data from the BIC. This avoids the convenience, reliability, and security issues associated with manual operation, while also lowering the requirements for the terminal device's deployment environment. It also addresses the problem of ephemeris data becoming invalid due to prolonged inactivity of the terminal device, eliminating the need for the terminal to be returned to the factory or undergo after-sales firmware updates. Furthermore, when a user replaces their terminal device, the new device can still obtain ephemeris data from the BIC and directly search and track the constellation for which the user has registered. This application effectively lowers the barrier to obtaining valid ephemeris data upon terminal device activation, assisting terminal devices in quickly acquiring valid satellite ephemeris data, enabling satellite search and tracking, and improving the user's network access experience.

The invention discloses an RPA-based power dispatching service auxiliary method, system and device, and a medium. The method comprises the following steps: logging in a power dispatching OMS system by using an RPA automation technology; interactively triggering an operation management function through a target control, and sequentially executing UI element clicking, interface component activation operation and event distribution to a CLOW node to jump to a scheduling operation page; obtaining the number of executed work orders by adopting a selenium technology, triggering work order operation instructions in sequence, and extracting planned operation time, operation content and advance notice unit names in the work orders; on the basis of the extracted work order information, target grouping check and message content input and sending including operation content, time and ticket changing signature are completed in a message management module; generating massive controlled training sample sets through an RPA model, and performing parallel training on the sample sets by adopting a deep reinforcement learning algorithm; and carrying out adaptive process design based on a training result, and adjusting and perfecting a business process through iterative development testing and according to a deployment environment.

The application discloses a real-time disaster recovery backup method for a communication database in a mixed deployment environment and particularly relates to the technical field of communication database disaster recovery, which is used to solve the problems of difficult guarantee of session-level consistency of the communication database in the mixed deployment environment and easy omission or repetition of billing records caused by master-backup switching. The application introduces session domain modeling indexed by a session identifier in the mixed deployment environment, combines session idempotent keys, session fingerprints and double-anchor time base record writing processes, and utilizes session consistency fields, session consistency scores and node disaster recovery health degree evaluation to drive the new master node to remove, sequentially rearrange and compensate missing data according to the session idempotent keys in the switching stage, so that session granularity unified sorting and accurate water level locking are realized under the link and clock fluctuation conditions of the local node, the edge node and the cloud node, billing record repetition or omission is avoided, and the continuous consistency of key signaling and billing sessions under failure is guaranteed.

The application relates to the technical field of servers, in particular to a server load balancing method and system based on edge computing, which comprises the following steps: monitoring state data of heterogeneous server nodes based on an edge computing scenario, identifying parameter fluctuation abnormal nodes, analyzing task scheduling and resource change trends, screening and grouping nodes, evaluating node continuous online and communication active performance, classifying nodes according to grading standards, and obtaining an availability distribution structure. The application realizes hierarchical dynamic collection of node availability by real-time mining of the coupling rules of load fluctuation, resource cooperation and bandwidth flow dynamic change among nodes, the resource grouping result is continuously optimized according to the node task bearing capacity and multi-time window communication activity, the node scheduling and distribution fully adapt to the network state and heterogeneous computing power scene, the task flow and node distribution tend to be balanced, the resource utilization and grouping structure of the cluster as a whole are more flexible, and the problems of high-frequency change and resource unevenness under the edge deployment environment can be adapted.

The application discloses a kind of enterprise-level private material library box security access and intelligent management system and method, it is related to computer network and cloud computing technical field, system includes: Connector service module establishes HTTPS outbound connection and establishes communication channel, box end equipment publishes file class operation task or AI class operation task, cloud SaaS platform publishes operation instruction according to operation task, double strategy check module executes double security authentication according to file operation instruction, LLM calls proxy module sends call command according to AI operation instruction in specific deployment environment, Token quota management module calls large model according to call command when quota is sufficient, deducts Token usage amount.The application eliminates the risk of inbound attack by only outbound connection architecture, combined with long polling technology to achieve real-time response of seconds, and builds a safe, real-time and controllable hybrid cloud material management system.

The application provides a version of an environment deployment method, device and electronic equipment, the method is applied to a server, the server pre-stores a packaging script, and the packaging script is run to execute the following steps: obtaining a pre-added build deployment file corresponding to a to-be-deployed version; obtaining version configuration information corresponding to a to-be-deployed environment of the to-be-deployed version; based on the version configuration information, replacing a corresponding part in the to-be-deployed version according to a preset replacement item to generate a new version corresponding to the to-be-deployed version; generating a software package corresponding to the to-be-deployed version according to the new version corresponding to the to-be-deployed version; and deploying the software package corresponding to the to-be-deployed version to the to-be-deployed environment. The application can quickly and conveniently deploy the software package of the to-be-deployed version to different environments through the build deployment file added in the to-be-deployed version.

The invention relates to a product automatic deployment method and device and computer equipment. The method comprises the steps of obtaining an environment packaging package, deployment planning resources and an installation package of a product corresponding to a product needing to be deployed, and constructing a product deployment environment corresponding to the product through a virtual environment deployment strategy based on the environment packaging package; on the basis of the deployment planning resources, identifying a configuration file of a product needing to be configured, and deploying and generating product configuration information corresponding to the product through a configuration deployment strategy on the basis of the configuration file; and based on the product configuration information, deploying the installation package of the product in the product deployment environment through an intelligent deployment strategy to complete an automatic deployment task of the product. By adopting the method, the product deployment efficiency can be improved.

The application provides a PXE network card initialization method, device and medium compatible with 64-bit addressing, relates to the technical field of network card initialization, and comprises the following steps: discovering a network card device; reading the PCI configuration space of the network card device, acquiring extended ROM base address register information, and mapping the network card Option ROM to a memory shadow area; when memory mapping input / output mode access fails, the initialization code performs read / write operation on the hardware register through a self-defined capability structure in the PCI configuration space of the network card device; based on the successfully accessed hardware register, network card hardware initialization is completed, and a PXE protocol stack structure body is established in the memory; the system firmware is registered as a PXE starting device, and a protocol interaction stage with a PXE server is entered; and the application guarantees the smooth development of a subsequent network booting process, and improves the deployment success rate and system stability in a large-scale batch deployment environment.

The invention discloses a wind turbine generator reliability rating method and system, a medium and computer equipment. The method comprises the steps of data preparation and alignment; aRIMA / seasonal ARIMA modeling is carried out, and characteristic indexes are obtained; aRIMA output is structured into enhanced features available for a tree model, and the enhanced features are fused with time coding, lagging and rolling statistics and unit static parameters; a CART or gradient boosting tree is adopted to output'reliability grade / risk score 'and provide an interpretable rule path, and online updating and auditing are carried out to cope with concept drift and seasonal variation. The reliability rating method which is more stable, explainable and audible is formed, and the accuracy rate, the recall rate and the cross-seasonal stability are remarkably improved; and low-cost operation can be realized through lightweight feature calculation and periodic updating in an edge deployment environment.

The invention relates to a few-sample visual model optimization system and method based on end-cloud collaboration. The system comprises edge equipment and a cloud server. The edge device collects an environment image of the current deployment environment and sends the environment image to the cloud server; the cloud server is configured to extract an image sample from a pre-training data set after receiving the environment image, and fuse the image sample with the environment image based on a block-level mixing mode to generate an environment perception training sample; adjusting and optimizing the backbone network based on an environment perception training sample and an optimization strategy including mixed perception contrast learning and a multi-task auxiliary target to generate a lightweight adjusting and optimizing module; sending the generated tuning module to the edge device; and the edge device loads the tuning module to perform a few-sample reasoning task. The system provided by the invention has the advantages of low training and communication overhead, no need of extra annotation information, remarkable tuning effect and the like, and can be widely applied to edge intelligent vision application with frequent environment change and limited samples.

The application provides a development deployment environment processing method and device, and mainly solves the technical problem that the actual deployment link still runs abnormally in the traditional scheme. The method part comprises the following steps: collecting the development behavior data of a developer, and identifying a current development scene based on the development behavior data; generating a dynamic verification rule based on the development scene and the deployment environment parameters corresponding to a target deployment environment; and performing verification on a to-be-deployed object in a development environment by using the dynamic verification rule to obtain a checking result.

A user-friendly platform provides a simplified procedure for end users to deploy models that utilize generative AI to perform tasks (hereinafter simply “AI model”) in a deployment environment (e.g. in a data center). Upon selection of an AI model to be deployed, the platform orchestrates deployment and allocation of resources that satisfy hardware requirements of the AI model. The platform includes an agent that communicates with infrastructure of the cloud provider or virtualization platform that manages deployed resources tracks allocation of hardware resources to virtual / cloud resources running on the deployment environment. The platform handles deployment of resources for deployment of the AI model “behind-the-scenes” from the user's perspective based on the monitored availability of hardware resources. For added security, the platform performs DLP scanning of data uploaded to the platform for input to an AI model that has been deployed.

This invention provides a data access method, apparatus, storage medium, and electronic device, belonging to the field of computer network technology. The method includes: acquiring raw message data; identifying the protocol type corresponding to a target data source based on the raw message data; determining whether the protocol type corresponding to the target data source is a candidate protocol based on the initial confidence probability of each candidate protocol; if the protocol type corresponding to the target data source is determined to be a non-candidate protocol, probing the protocol type of the target data source, and determining a predicted protocol type based on the probing results and the initial confidence probability of each candidate protocol; and accessing the target data source based on the predicted protocol type. This method overcomes the limitation of traditional static rule bases that can only identify standard ports and public protocols, significantly improving adaptability to private protocols and non-standard deployment environments.

This application provides a data center load balancing method and apparatus based on temperature sensing and path selection, belonging to the field of data center load balancing technology. The method provided in this application: determines virtual machines to be migrated from overheated servers based on resource utilization; determines candidate target servers from servers in the data center based on resource requirements; calculates a comprehensive score for each candidate target server based on its temperature factor, load utilization factor, and heat accumulation factor; calculates the migration probability of each virtual machine to be migrated to each candidate target server based on pheromone concentration and comprehensive score; iteratively solves for the optimal solution based on the migration probability and ant colony optimization algorithm; determines the target server based on the optimal solution; and migrates the set of virtual machines to be migrated. The method and apparatus provided in this application are used to achieve synergy between data center thermal management and energy consumption optimization in ultra-dense deployment environments.

A request to perform scalability analysis of a constituent service of an application at a first deployment environment is received. The constituent service is deployed to a plurality of host groups of the deployment environment. A data set which indicates a collection of front end request routers configured to distribute service requests among hosts of a collection of deployment environments including the first deployment environment is obtained. Analysis of the data set is used to identify a resource scaling unit which indicates a set of host groups, including a particular host group of the plurality of host groups, such that individual hosts within the set of host groups have the same estimated workload level as other hosts within the set of host groups. A representation of the resource scaling unit is stored.

Systems and methods for automated generation of customer journeys are disclosed. A method may include: receiving, by a computer program and from a design interface tool, an application flow for a computer application comprising a plurality of pages and a plurality of links that link the pages together graphically; traversing, by the computer program, the application flow to identify a plurality of customer journeys from the plurality of pages and the links; generating, by the computer program, a simplified file with data for the plurality of customer journeys; generating, by the computer program, code comprising scenarios and steps for the data for each of the plurality of customer journeys; and deploying, by the computer program, the steps and scenarios to a deployment environment.

The embodiment of the invention discloses a font automatic collection and missing font supplementation method applied to a DWG drawing. The font automatic collection and missing font supplementation method comprises the following steps: establishing a font storage space and a database at a server side; loading a font management module in CAD software of a user side; when a user opens a DWG drawing, the module automatically analyzes a file to obtain a used font identifier, uploads locally missing fonts to a server for storage, and records the fonts in a database at the same time; and when other users open the same drawing, the module automatically compares and downloads, and silently installs the locally missing fonts. In addition, after the user edits and stores the drawing, the module analyzes the drawing again and uploads newly added fonts, and dynamic updating of the database is achieved. According to the method, automatic collection, centralized management and on-demand distribution of font files are achieved, the problem of drawing display abnormity caused by font missing is thoroughly solved, collaborative design efficiency and data sharing accuracy are remarkably improved, and the method is suitable for various deployment environments such as a cloud server, a wide area network and a local area network.

The invention discloses a distributed node dynamic deployment and data flow cooperative monitoring system and method. The distributed node dynamic deployment and data flow cooperative monitoring system comprises a distributed node dynamic deployment and data flow cooperative monitoring system and a distributed node dynamic deployment and data flow cooperative monitoring method. The system comprises a business data classification module, a communication category module, a communication protocol module, a hardware node module, a software node module, a deployment environment configuration module, a deployment environment publishing module and a deployment environment real-time monitoring module. The method comprises the following steps: configuring data classification, communication category, communication protocol, hardware node and software node; the deployment environment configuration module carries out visual dynamic deployment; the deployment environment publishing module maps the deployment environment into a configuration file; and the deployment environment real-time monitoring module monitors the deployment environment. Visual dragging configuration and monitoring of hardware nodes, software nodes and data streams in a distributed system are achieved, configuration efficiency and accuracy are improved, and flexibility, maintainability and reliability are enhanced.

The invention discloses a database script deployment method and device, equipment and a storage medium, and relates to the technical field of database management, and the method comprises the steps: sending a database change script for a target product to a user side, and carrying out the data extraction, so as to obtain a target script identifier and product version information; determining a complete script corresponding to the database change script based on the target script identifier and the product version information, and generating a script execution sequence corresponding to the complete script based on the product version information; generating a corresponding script deployment environment in a preset sandbox, and executing deployment of a complete script in the preset sandbox based on the script execution sequence to obtain a script deployment sandbox simulation result; checking based on a preset auditing verification method; and if the verification is passed, determining a current to-be-deployed script from the complete scripts based on the current to-be-deployed environment of the target product, and deploying the current to-be-deployed script to the current to-be-deployed environment. In this way, the script execution consistency and security under multiple database types and multiple environments can be ensured.