194 results about "Software deployment" patented technology

The present disclosure pertains to systems, computer program products, and methods for an automated mesh service-based deployment intelligence system. This system is designed to streamline the deployment of software by integrating a processing device and a non-transitory storage device. The storage device contains instructions that, when executed by the processing device, enable the ingestion of data from various sources such as monitoring systems, databases, and application performance management tools. Once ingested, the data is stored and processed to discern deployment patterns and detect any anomalies. Utilizing a machine learning model, the system anticipates potential deployment issues by analyzing this data. It then orchestrates the deployment of software artifacts accordingly, taking into account the insights gained from the machine learning model. Furthermore, the system is capable of real-time optimization of the deployment process to preemptively resolve any predicted issues, thereby enhancing the efficiency and reliability of software deployment operations.

Techniques are provided for software deployment pipeline generation using generative artificial intelligence (AI). One method comprises obtaining a trained generative AI model, trained using a plurality of continuous integration / continuous deployment (CI / CD) configuration files; obtaining information characterizing a selected software development project; and applying at least some of the information characterizing the selected software development project as one or more system prompts to the trained generative AI model, wherein the trained generative AI model predicts a portion of a software deployment pipeline associated with the selected software development project. The CI / CD configuration files used for training may be associated with an organization that is associated with the selected software development project. The predicted portion of the software deployment pipeline may comprise pipeline jobs, an automatic code completion and / or a correction of a syntax and / or a structure of at least one CI / CD configuration file being edited.

The invention discloses an agent-free honeypot mapping method and device, and relates to the technical field of network security. The method comprises the following steps: analyzing metadata of core switching equipment, and establishing a domain-address mapping matrix; periodically detecting an address space, constructing an IP asset dynamic portrait and generating an asset state map; deploying a cross-domain traffic forwarding protocol stack and a virtual domain identifier mapping rule; deploying a software-defined virtual switching unit and accessing the virtual honeypot probe cluster; allocating idle addresses for the probes and establishing a binding relationship; and periodically detecting and triggering a self-healing process when an address conflict occurs. The device comprises a core exchange and domain management unit, an IP asset detection unit, a network protocol configuration unit, a probe virtualization management unit, an address resource scheduling unit and a system cooperative control unit. According to the method, agency-free and automatic deployment of the honeypot is realized, and the problems that a traditional scheme depends on agency software, deployment is complex and IP conflict processing lags are solved.

The invention discloses a demand development method, device and equipment. The method comprises the following steps: calling a demand analysis agent to analyze a natural language demand into a structured function demand unit comprising an input specification, an output specification and an execution constraint; the calling code generation agent generates source codes corresponding to the development requirements according to data type definitions and function calling specifications in the structured function requirement unit and the local project code library; calling a code test agent to generate and execute a test case based on the source code and the structured function demand unit; and after determining that a software deployment condition is met based on a test result, calling a code deployment agent to generate a deployment script and configuration information, and submitting the deployment script and the configuration information to a deployment execution engine to complete automatic deployment. According to the application, end-to-end automatic development from natural language requirements to application deployment can be realized.

The invention belongs to the technical field of software deployment, and particularly discloses a Linux system equipment software remote deployment method and system and a program product, a software remote deployment mode is adopted, configuration files and operation commands compiled by a user are analyzed through a client side, all deployment operation commands are responded in sequence, and a Linux system host is remotely connected in a butt joint mode. Corresponding deployment process instructions are compiled and executed, so that deployment operations such as receiving verification, software version replacement and program restarting of software files are automatically completed. According to the method, human errors can be avoided, the software deployment operation process is simplified, time consumed by developers for updating software versions can be effectively saved, the software development efficiency is improved, meanwhile, instructions in the deployment process are transferred and compiled based on the compiling tool, and transmitted software files are verified, so that the software development efficiency is improved. And the security and reliability of the software deployment process can be effectively ensured.

The techniques described herein provide a risk assessment framework that enhances the functionality of software deployment systems in cloud-based platforms. Generally described, the present techniques evaluate and consolidate various risk scores to classify a given computing cluster within a software deployment strategy. In various examples, a deployment system collects node-level feature data from the computing cluster to generate a dataset to train a prediction model to calculate constituent risk scores. In another aspect, the deployment system aggregates constituent risk scores to determine an overall risk of software failure. Likewise, the deployment system considers diverse criteria such as virtual machine size and virtual machine density to determine an overall impact of software deployment failure. The deployment system then calculates a composite risk score for the computing cluster as a function of the risk of software deployment failure and the impact of software deployment failure.

The invention discloses a method for acquiring server error information by a BMC (baseboard management controller), and relates to the technical field of fault diagnosis, and the method comprises the following steps: mapping a host serial port to the BMC based on a CPLD (complex programmable logic device), assisting in judging a server stage and debugging the serial port through the CPLD, collecting starting data by the BMC in a power-on starting stage, and sending the starting data to the BMC; and data collection and error early warning are carried out according to serial port jack input or BMC in the operation stage. The technical problem that in the prior art, server error information collection has high requirements for hardware support and software deployment is solved, and the technical effect of simplifying the server error information collection process is achieved.

Systems, devices, methods, and computer readable media for determining potential issues with a software upgrade are disclosed. In one implementation, the disclosed system includes at least one processor and at least one non-transitory memory storing instructions to perform operations when executed by the at least one processor. The operations include training a machine learning model on historic trouble ticket data; receiving data relating to a planned software upgrade; providing the received data to the trained machine learning model, wherein the trained machine learning model generates a tag value; calculating a risk score based on the tag value; and determining a client-specific action to be performed relating to the planned software upgrade and based on the risk score.

A method includes identifying configuration information of a server being deployed, which includes a configuration and software requirements, and the server is managed by a management server through a management controller controlling a host hosting the server. The method includes retrieving a recommended setup of hardware and software for the server based on the configuration information and retrieving, from a deployment tracking module, a recommended deviation. The method includes creating a deployment file based on the recommended setup and deviation, and transmitting the deployment file to the management controller, which uses the deployment file to configure the server. The deployment tracking module monitors firmware, drivers and / or software deployments of servers for problems and software deployments, monitors websites / databases associated with firmware, drivers and / or software deployed on the servers for updates, analyzes information from monitoring the deployments and updates from the websites / databases, and manages recommended deviations from recommended setups.

The utility model relates to an AFE-based battery management system, which comprises a battery equalization driving circuit and an MCU unit, the battery equalization driving circuit comprises an AFE chip, a current balancing circuit, a charging control enabling circuit and a discharging control enabling circuit, the AFE chip is responsible for converting analog signals such as voltage, current and temperature of a battery into digital signals, and the MCU unit is responsible for outputting the digital signals. The MCU is connected with the AFE chip through an I2C bus, the MCU can conveniently read battery data collected by the AFE chip through the I2C bus and issue a control instruction according to needs, and meanwhile, due to the design, software deployment is also facilitated, and through coordinated control of the AFE chip and the current balancing circuit, the battery data can be further processed by the MCU, so that the service life of the battery can be prolonged, and the service life of the battery can be prolonged. And high-efficiency equalization of each single battery in the battery pack is realized through the internal current balancing circuit and the external current balancing circuit, so that each single battery can work in an optimal state, thereby improving the overall performance of the battery pack and prolonging the service life of the battery pack.

The invention provides a system installation and deployment method and system based on engineering metadata, and relates to the technical field of software deployment, and the method comprises the steps: determining a software installation mode, and obtaining the engineering metadata; checking an installation environment based on preposition dependency information prompted by the engineering metadata; after the safety of the installation environment is ensured, performing signature verification and integrity verification on the software package based on the engineering metadata abstract and the signature information; after verification and verification are passed, the software package is installed on the basis of the component list of the engineering metadata, and the software package is configured on the basis of the information configuration list of the engineering metadata; and acquiring a security policy of the engineering metadata, activating a security protection function, generating installation engineering metadata after the security policy is completed, and evaluating the installation process based on the security engineering metadata.

The invention discloses an automatic deployment method, device and equipment for Linux environment software and a medium, and relates to the technical field of software deploy.The method comprises the steps that Linux environment information is collected on the basis of a programming language and in combination with a Linux system command, and the collected Linux environment information is stored as structured data; creating an improved model, and training by adopting pre-collected Linux environment software deployment case data, so that the trained improved model outputs a deployment strategy based on the Linux environment information; and according to the output deployment strategy, downloading an installation package of the software to be deployed and carrying out analysis processing on a software installation dependency relationship so as to realize automatic installation and deployment of the software based on scripts. According to the method, the software deployment in the Linux environment can be efficiently realized, the deployment error rate is reduced, and the adaptability is enhanced.

The invention relates to a software deployment technology, in particular to a remote deployment method for a software platform user interface, which comprises the following steps: constructing an independent service process at a server, and providing an HTTP (Hyper Text Transfer Protocol) service by the service process; the service process communicates with a software platform process in real time to obtain a configuration file of a software platform user interface and operation data of a software platform application program, and the software platform is a third-party software platform; analyzing the configuration file of the software platform user interface through the service process, and locally generating a webpage containing the corresponding user interface at the server according to the information of each user interface in the configuration file; when the webpage is opened in a local browser of the server side, the service process obtains an opening behavior so as to refresh the operation data of the application program of the software platform to the webpage in real time; and / or, the service process responds to the user interface operation on the webpage so as to transmit an operation instruction to the software platform in real time, and then corresponding operation is executed through the software platform.

The invention discloses an incremental configuration file synchronous release method and device, computer equipment and a storage medium, and the method comprises the steps: executing an environment configuration operation on a code warehouse to generate an initial configuration file; carrying out construction processing on the configuration file in a deployment platform to form a task file which can be used for automatic deployment and automatic release; writing a newly added configuration item into the configuration file to generate a target configuration file; and according to the task archive, executing a synchronous publishing operation on the target configuration file on a deployment platform. By implementing the method disclosed by the invention, a tester does not need to manually debug and deploy scripts and verify environmental parameters, so that invalid human input during multi-environment adaptation is avoided, the software deployment period is effectively compressed, the possibility of operation negligence is reduced, deployment failure caused by operation sequence deviation during manual deployment is avoided, and the deployment efficiency is improved. The technical scheme can be applied to the financial field.

The invention provides an application software remote deployment method and device of a railway signal general safety system, and relates to the technical field of software deploying.The method comprises the steps that firstly, network transmission protocols supported by all servers and all clients in the railway signal general safety system are determined; then deploying the network transmission protocol to all the servers and all the clients; and finally, remotely deploying the application software in all the servers by using any one of all the clients. According to the application software remote deployment method of the railway signal general safety system, storage hardware equipment is not needed, manual updating on each server is not needed, time and resources are saved, and convenience, safety and isolation of remote deployment of the application software of the railway signal general safety system are improved.

Techniques are provided for failure mitigation in software deployment pipelines using generative artificial intelligence (AI). One method comprises obtaining a request to merge code changes associated with a first branch of software code with a second branch of the software code; in response to the request: obtaining information characterizing the software deployment pipeline; applying at least a portion of the information to a classification model to obtain a prediction that an implementation of the request will result in a failure; applying, in response to the prediction that the implementation of the request will result in the failure, at least a portion of the information to a generative AI model, with failure information characterizing reasons for the failure, to obtain mitigation actions to mitigate the failure; and automatically initiating processing steps associated with at least one of the mitigation actions to mitigate the failure.

The embodiment of the invention provides an updating instruction sending method and device, a storage medium and electronic equipment, and relates to the field of computers.The updating instruction sending method comprises the steps that server information of a target server is obtained through an information collection program, and the server information comprises software information in the target server; determining a corresponding software installation package set according to the server information; an updating instruction is sent to the target server, the updating instruction is used for indicating that the operating system of the target server is updated into the target operating system, and after the operating system of the target server is updated into the target operating system, corresponding software deployment operation is carried out on the target server according to the software installation package set. By adopting the technical scheme, the problem that the efficiency of migrating the operating system is relatively low is solved.

The invention provides a virtual machine index data monitoring method, device and equipment and a medium, and relates to the technical field of computers.The method comprises the steps that initial index data of a virtual machine is obtained from virtual data platforms for the virtual data platforms of multiple manufacturers; the virtual data platform is used for collecting initial index data of the virtual machine; performing unified processing on the initial index data corresponding to all the virtual data platforms to obtain monitoring index data corresponding to all the initial index data; and uploading the monitoring index data to a monitoring data service platform for monitoring. According to the technical scheme, the initial index data of the virtual machine is obtained from the virtual data platform of the manufacturer, software does not need to be arranged on the virtual machine, virtual machine resources are saved, monitoring flexibility is improved, and the situation that the index data cannot be collected due to software deployment failure is avoided.

A method performed by a system including a collector unit, an analyser unit, and a scheduler unit, comprises receiving a data comprising at least one of a hardware data, a traffic data and a service data related to one or more devices and one or more applications, feeding the data a trained model, determining, through the trained model, one or more patterns of the data, providing, an output from the trained model to the scheduler unit, performing, through the network, software deployment on the one or more devices based on the output.

The invention discloses an unmanned surface vehicle multi-source target detection method and related equipment based on a domestic deep learning software and hardware platform. In the method, a data acquisition unit senses the environment by using a visible light camera, an infrared camera and a laser radar multi-source sensor; the single-source data target detection unit performs target detection on each data source, and comprises a target detection algorithm based on a domestic deep learning reasoning framework MNN and a traditional laser radar point cloud target clustering algorithm; the multi-source data fusion analysis unit performs data synchronization and fusion analysis on output results of all algorithms to obtain a final accurate target detection result; the system provided by the invention overcomes the defect of sensing capability of a single sensor, supports all-day and all-weather operation, and improves the accuracy and confidence of a detection algorithm; algorithm software is deployed in a domestic ruggedized computer provided with a Feiteng D2000 processor and a Jingjia micro JH920 display card, and is autonomous and controllable.

The invention discloses a database hybrid deployment method and device.The method comprises the steps that a first request is obtained and used for requesting to apply for creating a first database service on a database platform, and the database platform comprises at least one server cluster and a software mirror image supporting multiple chip types; each server cluster comprises servers supporting at least one chip type; in a database software deployment process, aiming at each database node, according to a chip architecture selected by a user for the first database service, and screening a server supporting the chip type corresponding to the database node in a database cluster, screening a software mirror image supporting the chip type corresponding to the database node from a database platform, and deploying the database node on the first server according to the first software mirror image. Therefore, under the scene that multiple chip type servers are used at the same time, database services are deployed according to the chip architecture selected by a user by himself / herself, and the service requirements are met quickly.

The invention provides a software development application updating processing method and system based on cloud computing, and the method comprises the steps: analyzing a dependency relationship between software application components, and generating a software deployment topological graph; preheating the target computing resource on the cloud platform to generate a dynamic resource pool, and executing an application version replacement operation in the dynamic resource pool; when the triggered service is abnormal, switching the abnormal service traffic to a backup resource node, updating the abnormal software application component at the node, and generating an updated software application component; re-accessing the updated software application component into the dynamic resource pool so as to complete software development application updating processing; according to the method, accurate matching of the updating task and the computing resource is realized, the consistency of version replacement is guaranteed, and the problems of low deployment efficiency and insufficient stability caused by confusion of dependence of software updating in a traditional cloud environment are solved.

The invention discloses a software deployment construction operation and maintenance monitoring system, which relates to the technical field of operation and maintenance monitoring and comprises a system framework, an automatic deployment update management platform, a continuous integration delivery platform and an operation and maintenance management platform. The automatic deployment update management platform is deployed in a system framework and is used for maintaining related server information, associating a Git code version and replacing a program installation package version, and setting a program restart strategy at the same time; the continuous integration delivery platform is used for locally carrying out program development, submitting latest codes by Git, triggering an automatic test program to carry out automatic test on the codes, and configuring an upgrade packaging task for the codes passing the test through the automatic deployment update management platform so as to replace a program installation package version; the operation and maintenance management platform is used for monitoring the server state, the application performance and the network flow in real time, monitoring the program operation stability condition and the deployment operation success state, and meanwhile, is used for system fault detection; according to the operation and maintenance monitoring system, the program operation and maintenance cost is reduced.

The invention discloses a computer software development data processing system based on big data, relates to the field of software development, and solves the problem that the computer software development data processing system is poor in application effect. Comprising a development data module used for obtaining the function resource occupancy rate and the function static complexity corresponding to each software function to obtain software development function data, and a resource investment module used for obtaining the fund investment degree corresponding to each software function to obtain fund investment data, the function concurrence module is used for obtaining function concurrence complexity corresponding to each software function to obtain function concurrence data, and the software deployment module is used for performing server selection and deployment on the computer software according to the software development function data, the fund investment data and the function concurrence data. According to the method, the scientificity and applicability of a computer software deployment result can be improved.

Systems and methods of determining and providing optimized deployment plans for deploying software to vehicles are disclosed. In some embodiments, a vehicle software deployment system evaluates one or more cost functions to determine relative costs of different deployment configuration options for deploying software to a vehicle, such as resource costs (e.g., bandwidth, compute, memory, etc.), isolation costs (e.g., limited access to input information, limited connectivity to other ECUs, etc.), performance costs, etc. Based on the evaluation of the one or more cost functions, the vehicle software deployment system determines an optimized deployment plan. Also, the vehicle software deployment system receives telemetry data from the vehicle and automatically determines updated optimized deployment plans in response to changes in configuration of the vehicle indicated in the telemetry data.

This disclosure relates to a method and apparatus for obtaining application packages across distributions, belonging to the field of software development technology. The method includes: creating and running a temporary container corresponding to the base image based on a base image adapted to the target application using containerization technology; obtaining the file system of the temporary container and packaging it into an archive format to generate a base root file system; decompressing the base root file system and creating a target isolation environment with the base root file system as the root directory based on root directory switching technology; installing the target application and runtime resources supporting the target application in the target isolation environment to construct the target root file system; obtaining the code corresponding to multiple functional modules and generating an environment distribution package based on the code corresponding to the multiple functional modules and the target root file system. This application can improve the compatibility and convenience of software deployment across distributions.

The invention discloses a software deployment compatibility prediction method and system based on a LightGBM algorithm, and belongs to the technical field of data analysis. The method comprises the following steps: acquiring environmental parameters of a historical deployment task and a dichotomy deployment result; performing sample balance and weight distribution processing on the data to construct a full-amount training set; based on the training set, a two-stage LightGBM architecture is adopted to train a prediction model, a first classifier learns a global mapping relation and outputs an initial prediction probability, and after a boundary fuzzy sample set is screened out according to the initial prediction probability, a second classifier learns fine feature differences of the boundary fuzzy sample set so as to determine a final prediction result. According to the method, the problem of unbalanced category distribution is solved through cooperation of SMOTE oversampling and sample weight adjustment, the discrimination capability of boundary fuzzy samples is enhanced by using a two-stage classification mechanism, and the defect of low prediction accuracy of a traditional method in a complex heterogeneous industrial environment is effectively overcome; and the compatibility evaluation automation level and the prediction reliability before the printing industry software deployment are obviously improved.

The invention relates to the technical field of power grid operation, and provides a power grid operation safety distance accurate sensing device and method in a non-fixed scene, and the device comprises a hardware device and terminal software which is in communication connection with the hardware device. The hardware device is integrated and deployed on a movable support or a holder, and comprises a laser radar sensor which is used for rapidly scanning a power grid operation scene and obtaining three-dimensional point cloud data including three-dimensional coordinates, laser intensity and echo information; the high-definition visible light camera is approximately parallel to the optical axis of the laser radar sensor and is used for collecting real-time video images of the operation scene; an AI visual analysis module and a point cloud processing unit are arranged in the embedded processor; and the terminal software is deployed on the edge computing equipment or the background server and is used for receiving and processing the data from the hardware device. According to the invention, the safe distance can be accurately sensed.

Systems, devices, methods, and computer readable media for determining potential issues with a software upgrade are disclosed. In one implementation, the disclosed system includes at least one processor and at least one non-transitory memory storing instructions to perform operations when executed by the at least one processor. The operations include training a machine learning model on historic trouble ticket data; receiving data relating to a planned software upgrade; providing the received data to the trained machine learning model, wherein the trained machine learning model generates a tag value; calculating a risk score based on the tag value; and determining a client-specific action to be performed relating to the planned software upgrade and based on the risk score.

The invention provides a vehicle-based software deployment method and device, electronic equipment and a medium, and the method comprises the steps that a software configuration list of a target vehicle is called, the software configuration list comprises a plurality of configuration items, and each configuration item comprises a software identifier and a processing identifier; for each configuration item in the software configuration list, executing the following deployment processing: searching an actual processing unit corresponding to the software identifier of the configuration item in the software deployment list of the target vehicle, and if the actual processing unit corresponding to the configuration item is different from a preset processing unit, executing the deployment processing; and if not, replacing a processing identifier indicating a preset processing unit with a processing identifier corresponding to a software identifier corresponding to the configuration item in a software deployment list so as to execute software deployment for the target vehicle based on the software deployment list. Through the vehicle software deployment method and device, automatic verification and correction of the mapping relation between the software component and the processing unit are achieved, and the accuracy and execution efficiency of vehicle software deployment are improved.