110 results about "Continuous delivery" patented technology

The invention discloses an automatic code generation and optimization system based on multiple modes, which relates to the technical field of automatic programming, and comprises a task analysis module for analyzing task description and constraint conditions in combination with a CLIPS rule engine and a knowledge graph and original data, identifying task targets and requirements, and outputting a task risk assessment report and a task intention set; the optimization decision module is used for selecting an optimal modal data subset by using a particle swarm optimization algorithm and a path planning algorithm, performing optimization adjustment according to task requirements, and outputting a code generation strategy; and the test evaluation module is used for evaluating and improving the unit test and the integration test by utilizing the variation test, carrying out quality and performance evaluation on the code through continuous integration and continuous delivery, and outputting a code evaluation report and an optimization suggestion. According to the method, the optimal modal data subset is dynamically screened, and the data transmission path is optimized, so that the code performance is ensured, the computing resource consumption is reduced, and the global optimization of the code generation strategy is realized.

The invention relates to the technical field of continuous integration and continuous delivery, and discloses a Jenkins continuous integration method based on Kubernetes. According to the method, a Jenkins server is deployed in a Kubernetes cluster to serve as a control plane, a construction environment is created through a preset multi-container Pod template, and a Pod containing a plurality of containers is dynamically created based on the Pod template, so that each container executes different construction tasks. Containers in the Pod realize collaboration through sharing a network namespace and a storage volume, and a Jenkins server monitors task execution states of the containers in the Pod and performs dynamic scheduling according to task priorities and cluster load states. And after the task is completed, automatically destroying the Pod and releasing cluster resources. According to the method and the device, dynamic expansion and contraction of a construction environment and efficient parallel execution of tasks are realized, the problem that a traditional Jenkins static resource pool is difficult to deal with load changes is solved, the resource utilization rate is improved, the expandability of the system is enhanced, and an efficient and reliable solution is provided for an enterprise-level continuous integration system.

The invention discloses a method and a system for realizing automatic code generation by using multiple AI Agents, and relates to the field of electric digital data processing, a test driving agent receives a task transmitted by a previous node, and generates a task number, a task description, test data, a unit test script and a code statement; the code generation agent generates or updates codes according to the received task description and code declaration; the test driving agent returns an integrated test script and test data according to the task number; the continuous integration agent performs integration verification and regression test and feeds back information; the test driving agent returns a function test script, a performance test script and test data according to the task number; and the continuous deployment agent carries out continuous delivery and deployment and feeds back information. By means of mutual conversation and cooperative work of multiple AI Agents and in combination with a feedback mechanism, the problem that a single large model cannot complete complex software development tasks is solved, full-process operation automation can be achieved, and the code generation quality and efficiency can be improved.

In an example embodiment, a root cause of a CI / CD pipeline is identified automatically from event logs of the CI / CD pipeline. A solution is then suggested automatically using an artificial intelligence analysis. More particularly, the identified root cause (e.g., error) and contextual information about the system and / or application being examined may be passed to an AI engine to predict one or more solutions to the root case.

The invention relates to the technical field of Kubernetes cloud platforms, and discloses a cross-network multi-cloud multi-cluster application distribution method, device and equipment and a medium, and the method comprises the steps: creating a server application and a k8s APIService resource in a central cluster; proxy applications are created in the multiple access clusters, and remote procedure call requests are initiated to an API server through the proxy applications; when the API server receives a remote procedure call request of the proxy application, creating a bidirectional long connection tunnel of the server application and the proxy application; and creating an access cluster key for application distribution of the continuous delivery tool in the central cluster, and distributing applications to the plurality of access clusters through the bidirectional long connection tunnel by adopting the continuous delivery tool based on the access cluster key. According to the method, the advanced characteristic of ArgoCD multi-cluster distribution is fully played, the user cost is reduced, and the risk of leakage of the configuration file of the user access cluster is reduced.

The invention relates to a micro-service architecture system based on business function and data double isolation, and the system comprises a business function splitting module which splits a single application into independent micro-services; the data physical isolation module is used for distributing an independent database instance for each micro-service; the dynamic routing control module is used for dynamically distributing flow through a load sensing strategy and integrating a fusing mechanism; and the gray release module supports flow hierarchical diversion and abnormal automatic rollback, and ensures safe switching of service versions. According to the invention, by realizing double isolation of service functions and data, the independence and the expandability of the system are improved, and the data coupling degree and the maintenance cost are reduced; the stability and reliability of the system are ensured, and the risk in the migration process is reduced; according to the method, rapid iteration and continuous delivery can be realized, the development and deployment period of new functions is accelerated, and the user experience is improved through efficient service governance and data consistency guarantee, so that the system can better cope with challenges of high concurrent access and distributed transaction processing.

Systems and methods for capturing a disk image of a bare metal server, and then using the disk image to provision other bare metal servers. A method includes capturing a disk image of a first bare metal server and writing the disk image to a repository manager. The method includes launching a continuous delivery mode on a second bare metal server where the disk image is fetched from repository manager and written to second bare metal server, followed by configuring the unique identity.

A topology-reprogrammable test environment is provided that can support the needs of CI / CD / CV in the field. The system disclosed provides a highly scalable network architecture to simplify the implementation of network slicing, TaaS and network CI / CD, and solves problems related to the complexity of cloud-native network (CNN) deployments. A Network Cell (NC), comprises or consists of a Containerized Network Function (CNF), a Containerized Digital Twin (CDT), and a Containerized Test Agent (CTA). The CDT has at least two personalities, e.g., an emulator of the CNF in the same NC or a nodal of the CNF. The choice of personality of the CDT is controlled by the CTA of the NC. A number of NCs use a 3D IP address to interconnect and form a new kind of CNN over the infrastructure of VRs.

The embodiment of the invention relates to the technical field of computers, and provides a branch synchronization method, system and device for a low-code development platform and a readable storage medium, and the method comprises the steps: newly storing branch name fields for all data in a database to associate corresponding git branches; when a git branch is newly built on the platform, if the database has no branch data, synchronizing a corresponding branch code of the database; if the branch data exists in the database, developing based on the database; synchronizing the data of the git branch and the corresponding branch of the database so as to realize the addition and deletion of the operation branch of the client and the synchronous addition and removal of the data of the database; the same set of database table structure design is adopted according to different environments, and the data quantity is determined according to a user branch strategy. According to the embodiment of the invention, the characteristics of git can be fully utilized, code version management is carried out on low codes like high codes, a DevOps research and development process is better adapted, and a foundation is laid for continuous delivery of low code applications.

A computing platform may configure a dependency knowledge graph indicating file dependencies for mainframe applications, and an error knowledge graph indicating errors and corresponding solutions for the mainframe applications. The computing platform may receive mainframe source code. The computing platform may analyze, using the knowledge graphs, the mainframe source code to identify potential errors and corresponding solutions. Based on identifying an error in the mainframe source code, the computing platform may cause the mainframe source code to be updated according to the corresponding solution. The computing platform may analyze, using the dependency knowledge graph and the error knowledge graph, the updated mainframe source code to identify remaining errors. Based on identifying an absence of the remaining errors, the computing platform may send, to a mainframe build and deployment engine, the updated mainframe source code, which may cause the mainframe build and deployment engine to automatically execute a build process.

The invention provides a micro-service deployment method and system supporting non-stop release and a continuous delivery platform, and the method comprises the steps: receiving a version identification file corresponding to to-be-updated version data of a micro-service, selecting a part of service nodes in a first namespace currently running in a micro-service system to stop based on an elegant stop rule, and sending the selected part of service nodes to the micro-service system; switching and deploying the shutdown node to the second namespace; gateway dynamic routing switching is carried out to route the traffic to each service node of the second namespace; if the stable operation of the second namespace is confirmed, switching and deploying the remaining service nodes in the first namespace to the second namespace in sequence; according to the application, the problems of poor user experience, data loss and service unavailability caused by shutdown when the new version of the micro-service is released and the problems of complicated micro-service system development, compatibility need to be considered and tedious multi-version management caused by a non-shutdown mode can be solved at the same time, so that smooth upgrading and high availability of the micro-service system can be realized.

The invention relates to the technical field of ship manufacturing, and discloses a general assembly construction data service encapsulation and construction method based on a cloud native technology. The method comprises the following steps: dividing a ship final assembly construction data source into design, production, quality inspection, logistics and operation and maintenance data units, and determining a data type and an interface protocol; then, constructing an initial service model based on a micro-service architecture and a containerization technology; then, dynamic service packaging is carried out, and cross-model data routing and load balancing are achieved; dynamically allocating resources and scheduling tasks through a multi-target scheduling algorithm model; iteratively optimizing the service model by utilizing an incremental learning mechanism; and finally, realizing gray release and rolling update by continuously integrating and continuously delivering assembly line deployment to a cloud native platform. The ship general assembly construction data processing efficiency, the system performance and the service quality are improved, and the problems of disordered data management, low processing efficiency, unreasonable resource allocation and the like in a traditional mode are effectively solved.

The invention relates to the technical field of software development and testing, and discloses an automatic testing integrated system in a software development process, which comprises a testing management module used for formulating a testing plan, designing a testing case and managing testing execution; the automatic testing module is used for integrating and executing unit testing, function testing, regression testing, performance testing and safety testing; the continuous integration and continuous delivery module is used for automatically constructing, testing and deploying the process; the environment management module is used for configuring, simulating and virtualizing a test environment; and a reporting and analysis module. Various testing tools such as unit testing, function testing, regression testing, performance testing and safety testing are integrated into one system, so that the problems of diversity and integration difficulty of the testing tools are effectively solved. Different types of testing tools are managed and coordinated in a unified mode, the complexity of the testing process and the compatibility problem between the tools are reduced, and the testing efficiency is improved.

A method includes identifying a pipeline of a plurality of pipelines of a continuous integration and continuous delivery / deployment (CI / CD) system, selecting a repository of a plurality of repositories utilized by the identified pipeline, modifying the repository, determining whether to test the modified repository and responsive to determining to test the modified repository, executing the identified pipeline with the modified repository.

Various methods and processes, apparatuses or systems, and media for automating development, testing, and productionizing a pipeline for users are disclosed. A processor receives a request from a user to access an application, the request including user's credentials data; grants access to the application based on verifying the user's credentials data with prestored credentials data received by calling an authentication server; identifies the user's role within a computing environment; automatically presents a template that corresponds to the user's role allowing the user to write code to source data either by bringing the user's own data into the computing environment or by connecting to data that resides in a database; automatically integrates the written code with a continuous integration continuous delivery pipeline for production of a model; and deploys the model after training and testing the model while managing and maintaining all necessary guardrails from a control standpoint within the computing environment.

The invention provides an interface change risk management and control method and device based on multi-source evidence fusion, and the method comprises the steps: carrying out the standardization processing of interface call data from various heterogeneous evidence sources, and generating a unified endpoint set and a call relation set; fusing the multi-source data pointing to the same calling relationship to calculate the confidence of the multi-source data, and constructing a service dependency topological graph based on a high-confidence relationship; when an interface change is detected, analyzing an influence range of the change in the topological graph, quantitatively calculating an influence surface score, and dynamically judging a risk level; and implementing corresponding automatic management and control actions in the continuous integration / continuous delivery process according to the risk levels. According to the method and the device, the problem of frequent interface change online faults caused by inaccurate dependence identification, inaccurate change influence evaluation and risk management and control lagging can be solved, the risk discovery and management and control of interface definition destructive change can be advanced from online to before-online, and the online fault rate is further remarkably reduced.

A company that develops software applications for operating and managing autonomous vehicles has an array of developer teams working on many different projects. Successful continuous delivery of software applications for the company can depend on reliability of the cluster infrastructure. Platform owners may be most knowledgeable when it comes to setting up cluster group that spans multiple regions. A developer working on a project can select, on a project management system, a cluster group for deployment of the project. A cluster group can specify a name for the cluster group, a plurality of environment-stack channels, and one or more clusters in deployment infrastructure associated with each environment-stack channel. The project management system can seamlessly provision resources for the project according to the selected cluster group.

In an example, an apparatus may operate as a continuous delivery (CD) pipeline for application artifacts running on a target software platform. The apparatus may include a processor to operate an application upgrader for the target software platform, the application upgrader to: consume application artifacts from a continuous integration (CI) system, wherein the target software platform runs a version of the application artifacts; obtain a signed manifest output from the CI system, the signed manifest identifying the consumed application artifacts; and compare a signature of the application artifacts from the CI system to a signature of the version running on the target software platform to determine if an update of the version running on the target software platform is required. Other embodiments may be disclosed and / or claimed.

The invention provides a research and development delivery method and device, a computer program product and a development platform, and the method comprises the steps that a demand module obtains a business demand, the business demand is divided into at least one task, and the task is a procedural work for completing the business demand; the demand module establishes a workflow state flow diagram for the task; the demand module configures a trigger strategy for the workflow state of the workflow state flow diagram, so that a corresponding assembly line task is triggered when the workflow state is turned to; under the condition that the continuous delivery module completes the assembly line task corresponding to the workflow state, the demand module triggers the workflow state of the workflow state flow diagram to flow to the corresponding next workflow state until the workflow state flows to the last workflow state to complete the task; under the condition that the continuous delivery module completes all the tasks, the demand module obtains the media released by the tasks to complete delivery, and the problem that automatic delivery is difficult to achieve in research and development in the prior art is solved.

A topology-reprogrammable test environment is provided that can support the needs of CI / CD / CV in the field. The system disclosed provides a highly scalable network architecture to simplify the implementation of network slicing, TaaS and network CI / CD, and solves problems related to the complexity of cloud-native network (CNN) deployments. A Network Cell (NC), comprises or consists of a Containerized Network Function (CNF), a Containerized Digital Twin (CDT), and a Containerized Test Agent (CTA). The CDT has at least two personalities, e.g., an emulator of the CNF in the same NC or a nodal of the CNF. The choice of personality of the CDT is controlled by the CTA of the NC. A number of NCs use a 3D IP address to interconnect and form a new kind of CNN over the infrastructure of VRs.

A method of improving continuous integration, continuous delivery (CI / CD) pipelines includes receiving an indication of a failure of a CI / CD pipeline of a plurality of CI / CD pipelines. The method further includes processing build status information by a rule engine, the build status information indicative of builds executed within the plurality of CI / CD pipelines. The method further includes applying a set of rule to the build status information to select a subset of the plurality of CI / CD pipelines, wherein the set of rules includes one or more of a resource availability rule or a failure type rule. The method further includes executing the subset of CI / CD pipelines selected by the rule engine.

This application provides a method and device for acquiring observability data for Go source code. By connecting to the compilation enhancement capabilities provided by Golang, business systems can be non-invasively connected to the OpenTelemetry monitoring system. Compilation parameters are automatically embedded through the continuous integration / continuous delivery (CI / CD) system, without the business side being aware of them. Upgrade actions can also be automatically completed through the CI / CD system. This embodiment implements non-invasive support for OpenTelemetry through a proxy module, thereby expanding the application of compilation enhancement in the observability field, supporting traditional observability capabilities such as link tracing, monitoring indicators, and log enhancement, as well as emerging observability methods such as performance profiling.

In one embodiment, a method includes generating an application programming interface (API) definition by observing traffic. The API definition is associated with an API definition name and an API specification. The method also includes mounting the API definition with an application and deploying the application by a Continuous Integration / Continuous Delivery (CI / CD) pipeline. The method further includes implementing a runtime API and mapping the runtime API to the API definition.

Various embodiments comprise systems and methods for operating a data monitoring system to branch data models. In some examples, a data monitoring system maintains a series of models for a data stream. The data monitoring system adds a reference pointer to a position in the series of models. The data monitoring system generates a set of branch models for the data stream and appends the set of branch models to the series of models at the reference pointer. The data monitoring system compares ones of the set of branch models with corresponding ones of the series of models and generates test results based on the comparison. The data monitoring system reports the test results.

The invention discloses a software testing method and system based on a data analysis platform, and particularly relates to the technical field of software testing, and the method comprises the following steps: tracking business semantic change by constructing a semantic evolution perception map, and establishing a semantic-driven data label linkage mechanism to maintain the consistency of training samples of a defect recognition model; semantic consistency drifting is monitored, model output is controlled, a map-enhanced test case generation mechanism is introduced to achieve semantic synchronous generation, meanwhile, a semantic regression verification process is set to ensure alignment of a test case and evolution semantics, and a closed-loop test process covering a full path is formed; according to the method, semantic-driven label linkage and model synchronous updating are realized by constructing the semantic evolution perception map, and a map-enhanced test case generation and regression verification process is introduced, so that the test process is ensured to be consistent with the service semantic dynamic state, the defect identification accuracy and the test coverage integrity are improved, and the test efficiency is improved. The method is suitable for software quality guarantee in a continuous delivery environment.

Systems and methods for capturing a disk image of a bare metal server, and then using the disk image to provision other bare metal servers. A method includes capturing a disk image of a first bare metal server and writing the disk image to a repository manager. The method includes launching a continuous delivery mode on a second bare metal server where the disk image is fetched from repository manager and written to second bare metal server, followed by configuring the unique identity.

A continuous delivery preparation capable of being stably released and a preparation method therefor. The preparation comprises an active pharmaceutical ingredient and a gel carrier, and the gel carrier comprises a biodegradable polymer, an organic solvent, a hydrophobic additive, and an optional hydrophilic gel matrix material. Compared with an in-situ gel prepared by means of a conventional Atrigel technology, the delivery preparation has the effect of slowing down in vitro and vivo burst release of the drug after a small amount of the hydrophobic additive and the optional hydrophilic gel matrix material are added, and the in-vivo blood drug concentration can be maintained for more than one week in a safe and effective range. The preparation method of the preparation is simple.

The application provides a translation system and a method and device for calling a translation service, multiple basic translation function modules can be created to meet various complex translation requirements in multiple scenes and multiple fields, cloud-native container management and scheduling capabilities are combined on this basis, distributed containerized automatic deployment of various translation function modules in the translation system is realized, whole translation service on the cloud can be quickly and continuously delivered and dynamically expanded, service deployment cost and time are reduced, iteration efficiency is accelerated, and product update cycle is shortened.

The invention relates to a management and control method and device for a continuous delivery work chain and computer equipment. The method comprises the following steps: acquiring data information and demand information of each working chain of a continuous delivery working chain, and generating logic information of each working chain; identifying demand content and demand conditions of each piece of work chain demand information, and identifying work flow information and flow parameter information of each piece of work chain data information based on each piece of work chain logic information; based on the demand content and demand condition of each piece of work chain demand information, carrying out standardization processing on each piece of work chain data information to obtain standard demand information corresponding to each piece of work chain data information, and based on the work flow information, flow parameter information and standard demand information of each piece of work chain data information, carrying out standard processing on each piece of work chain data information; and generating multi-chain management and control information of the continuous delivery work chain. By adopting the method, the comprehensive management and control effect of continuously delivered work chains with different requirements can be improved.

The invention provides a big data cluster deployment method and device, electronic equipment and a storage medium, and realizes full-process automatic deployment of a big data cluster through a containerized continuous delivery platform and a parameterized assembly line. According to the scheme, mirror image construction, component compiling and cluster installation are automatically executed, the deployment period is shortened from several days to several hours, human errors are avoided while efficiency is remarkably improved, and deployment accuracy is guaranteed. Through the unified product warehouse and standardized construction parameters, the consistency of the basic mirror image and the component version in different environments is ensured, the component compatibility problem is fundamentally solved, and the cluster stability and the cross-platform deployment capability are enhanced. According to the finally constructed complete continuous integration and delivery system, rapid and repeatable automatic deployment is realized, and the operation and maintenance agility and the system reliability are greatly improved.