Cloud native application delivery method and device, equipment, storage medium and program product

Abstract

The embodiment of the invention provides a cloud native application delivery method and device, equipment, a storage medium and a program product, and particularly relates to the technical field of cloud native application delivery. The method comprises the steps that when a target cloud native application is selected from a plurality of cloud native applications, application model information of the target cloud native application is obtained, and the application model information comprises defined component configuration, operation and maintenance characteristics, environment configuration strategies and workflows of the target cloud native application; and deploying the target cloud native application based on the application model information, and determining whether the target cloud native application meets a delivery requirement based on a deployment result. The method is used for achieving the effect of efficient and consistent deployment and delivery of cloud native applications.

Description

Technical Field

[0001] This application relates to the field of cloud-native application delivery technology, and in particular to a cloud-native application delivery method, apparatus, device, storage medium, and program product. Background Technology

[0002] With the rapid development of cloud-native technologies, containerization and microservice architectures have gradually become mainstream. Enterprise applications are rapidly evolving from monolithic to distributed architectures, and the division of labor between development, deployment, and operation and maintenance is becoming increasingly refined. However, traditional DevOps toolchains (such as the Kubernetes native API) only focus on component-level descriptions and lack standardized abstractions for complete applications (such as complex systems containing multiple microservices). This forces developers to get bogged down in detailed infrastructure configurations, requires operations personnel to repeatedly handle cross-environment adaptation issues, results in fragmented understandings of "applications" among different teams, and leads to high costs for cross-platform migration.

[0003] Against this backdrop, the Open Application Model (OAM) was proposed. It aims to unify the application description paradigm by defining core abstractions such as components, operational characteristics, and application boundaries, thereby decoupling the roles of development, operations, and infrastructure. It provides a cross-platform, scalable application delivery standard for the cloud-native ecosystem, filling the gap in the industry's application layer standardization.

[0004] While OAM is committed to standardizing application definitions, its core specification system is not yet perfect, resulting in an inefficient deployment and delivery process. Summary of the Invention

[0005] This application provides cloud-native application delivery methods, apparatus, devices, storage media, and program products to achieve efficient and consistent deployment and delivery of cloud-native applications.

[0006] In a first aspect, embodiments of this application provide a cloud-native application delivery method, including:

[0007] When selecting a target cloud-native application from multiple cloud-native applications, the application model information of the target cloud-native application is obtained. The application model information includes the component configuration, operation and maintenance characteristics, environment configuration strategy, and workflow of the target cloud-native application. The component configuration defines the workload corresponding to each microservice. The operation and maintenance characteristics define the operation and maintenance parameters corresponding to each component. The environment configuration strategy defines the configuration information and configuration strategy corresponding to the development and testing environment, the pre-release environment, and the production environment. The workflow defines the pipeline information corresponding to the development and testing environment, the pre-release environment, and the production environment.

[0008] The target cloud-native application is deployed based on the application model information, and the deployment results are used to determine whether the target cloud-native application meets the delivery requirements.

[0009] Secondly, embodiments of this application provide a cloud-native application delivery device, comprising:

[0010] The acquisition module is used to acquire the application model information of the target cloud-native application when selecting a target cloud-native application from multiple cloud-native applications. The application model information includes the defined component configuration, operation and maintenance characteristics, environment configuration strategy, and workflow of the target cloud-native application. The component configuration defines the workload corresponding to each microservice. The operation and maintenance characteristics define the operation and maintenance parameters corresponding to each component. The environment configuration strategy defines the configuration information and configuration strategy corresponding to the development and testing environment, the pre-release environment, and the production environment. The workflow defines the pipeline information corresponding to the development and testing environment, the pre-release environment, and the production environment.

[0011] The deployment and determination module is used to deploy the target cloud-native application based on the application model information, and determine whether the target cloud-native application meets the delivery requirements based on the deployment results.

[0012] Thirdly, embodiments of this application provide a cloud-native application delivery device, including: a memory and a processor;

[0013] The memory stores computer-executable instructions;

[0014] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0015] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0016] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0018] Figure 1 A schematic diagram illustrating the scenario of the cloud-native application delivery method provided in this application;

[0019] Figure 2 A flowchart illustrating the cloud-native application delivery method provided in this application. Figure 1 ;

[0020] Figure 3 A schematic diagram of the application model provided in this application;

[0021] Figure 4 A flowchart illustrating the cloud-native application delivery method provided in this application. Figure 2 ;

[0022] Figure 5 A schematic diagram of the delivery process for the cloud-native application delivery method provided in this application;

[0023] Figure 6 A schematic diagram of the overall implementation process for cloud-native application delivery provided in this application;

[0024] Figure 7 A schematic diagram of the cloud-native application delivery device provided in this application;

[0025] Figure 8 A schematic diagram of the cloud-native application delivery device provided in this application.

[0026] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0027] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0028] First, let me explain the terms used in this application:

[0029] Kubernetes is a portable, scalable, open-source cloud platform management tool for managing containerized services.

[0030] Application Model: The application model defines a standard model for describing cloud-native applications. By defining a series of core concepts and abstractions, it enables developers and operations personnel to understand and operate applications more clearly and consistently.

[0031] Application delivery: The entire process of an application from building and testing to official release and production environment, including deployment for development and testing, deployment for pre-release and deployment for production.

[0032] Pipeline: A process in which a set of tasks, abstracted from business logic, are executed in a pre-defined sequence according to a pre-defined template. This application mainly involves continuous integration / continuous deployment (CI / CD) pipelines, pre-release pipelines, and production release pipelines.

[0033] Cloud-native: It uses open-source technology stacks (Kubernetes + Docker) for containerization, improves flexibility and maintainability based on microservice frameworks, supports continuous iteration and operation and maintenance automation with agile methodologies and DevOps concepts, and uses cloud platform facilities to achieve elastic scaling, dynamic scheduling, and optimize resource utilization.

[0034] DevOps: In traditional software development processes, development and operations teams are typically separate entities. Developers are responsible for writing code, while operations personnel are responsible for deploying and maintaining the software. This separation can lead to poor communication, inefficiency, and problems during software delivery. DevOps is a culture and practice that promotes close collaboration between development and operations teams to improve the efficiency and quality of software development and delivery.

[0035] Platform engineering is an engineering discipline that focuses on building and maintaining internal software development and operation platforms for enterprises. It aims to provide standardized platform services and work with DevOps toolchains to improve application delivery efficiency.

[0036] The development of cloud-native applications has evolved from traditional software engineering methodologies to a stage primarily based on DevOps practices. To better advance DevOps practices, platform engineering proposes the goal of enabling platform services and DevOps toolchains to collaborate effectively. This aims to ensure developers fully adhere to these practices without requiring every developer to be a DevOps expert, making development simpler and more efficient, continuously optimizing the development experience, and further improving application delivery efficiency. Platform engineering leverages DevOps toolchains to promote collaboration and integration between development and operations, reducing manual intervention and improving delivery efficiency. Simultaneously, it further builds and maintains an integrated internal development self-service platform through platform services, providing standardized development and deployment services and tools to improve the developer experience and increase development efficiency.

[0037] An application model, within the context of cloud-native and microservice architectures, is a high-level abstract representation used to describe and define the characteristics, behaviors, and deployment requirements of an application. It typically decomposes the application into independently deployable and scalable components, defining the configuration, dependencies, operational characteristics, and overall lifecycle management of these components. The core objective of the application model is to simplify the development and operational configuration process of cloud-native applications, reducing manual configuration, improving configuration accuracy, and enhancing application maintainability, portability, and scalability. It allows developers to focus on implementing business logic, while the operations team manages application deployment, monitoring, and scaling, thus achieving separation of development and operations.

[0038] Currently, the standardization of application model information for cloud-native applications is insufficient, such as the lack of defined components, types of operational characteristics, and detailed attributes. This application, based on platform engineering principles, provides a model-driven cloud-native application delivery solution. This solution mainly includes the design and definition of application models, the design of application delivery processes, and the specific implementation of a unified and standardized application model-driven application delivery process. The aim is to enable developers to focus on business function development and innovation through standardized application models and model-driven cloud-native application delivery design, providing an application-centric, integrated delivery experience, shielding the underlying complex infrastructure, reducing cloud usage complexity, minimizing learning costs, and improving the efficiency of cloud-native application delivery.

[0039] Figure 1 A schematic diagram illustrating the scenario of the cloud-native application delivery method provided in this application, such as... Figure 1 As shown, during the delivery of cloud-native applications, development / testing environments, pre-release environments, and production environments are typically deployed on different cloud servers to ensure isolation, security, and stability. Users configure application model information through terminal device 101 and deploy the selected cloud-native application to different environments (development / testing, pre-release, and production). Application model information includes component configurations, operational characteristics, environment configuration policies, and workflows. Terminal device 101 can be various types of computing devices, including desktop computers, laptops, and tablets.

[0040] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0041] Figure 2 A flowchart illustrating the cloud-native application delivery method provided in this application. Figure 1 ,like Figure 2 As shown, the method includes:

[0042] S201. When selecting a target cloud-native application from multiple cloud-native applications, obtain the application model information of the target cloud-native application. The application model information includes the defined component configuration, operation and maintenance characteristics, environment configuration strategy, and workflow of the target cloud-native application. The component configuration defines the workload corresponding to each microservice. The operation and maintenance characteristics define the operation and maintenance parameters corresponding to each component. The environment configuration strategy defines the configuration information and configuration strategy corresponding to the development and testing environment, the pre-release environment, and the production environment. The workflow defines the pipeline information corresponding to the development and testing environment, the pre-release environment, and the production environment.

[0043] In this embodiment, a target cloud-native application can be selected from multiple cloud-native applications, and the application model information of the target cloud-native application can be obtained. (Refer to...) Figure 3 The diagram shown illustrates the structure of the application model provided in this application. Specifically, a cloud-native application consists of multiple components, representing a 1:N correspondence. The application model of a cloud-native application includes the attribute information of these components. Components can be front-end components, middleware, and back-end components, etc. The diagram shows two types of components: front-end microservice components and back-end microservice components. The attribute information of each component can include component configuration, operational characteristics, environment configuration strategies, and workflows.

[0044] Component configuration describes the specific workload of a component within an application. A component can be a microservice; that is, the component configuration defines the specific workload of a microservice, ensuring that the microservice can run independently and complete its specific business functions. Specifically, the component configuration defines attributes such as basic component information, component type, component name, and environment variables.

[0045] Operational characteristics describe the parameters and capabilities required by a component during operation and maintenance, such as resource requirements (CPU, memory), number of replicas, affinity, annotations, etc., to ensure the stability and performance of the component in different environments. Operational characteristics also define operational attributes such as liveness probes and ready probes.

[0046] The environment configuration policy describes the component's configuration information and strategies in different environments, such as development and testing environments, pre-release environments, and production environments, ensuring that the component can be correctly configured and run in different environments. The environment configuration policy describes the information of each environment, including environment name, environment type, cluster name, namespace name, and organization name.

[0047] Workflows describe the workflow of components in different environments, ensuring that application components can be developed, tested, deployed, and monitored according to predetermined processes. Workflows define parameters for generating continuous integration and continuous deployment pipelines, pre-release pipelines, and production release pipelines. Specific pipeline parameters include runtime pools, code repositories, code branches, and pipeline variables.

[0048] These elements together form a complete framework for component management in cloud-native application architecture, ensuring that each component of the application can run efficiently and reliably in different environments. By clearly defining these elements, development teams can better manage and optimize different parts of the application, thereby improving overall application performance and user experience.

[0049] An application model consists of four parts: all components required for application deployment, various operational characteristics, environment configuration strategies, and workflows. The application model configuration format is as follows:

[0050]

[0051] S202. Deploy the target cloud-native application based on the application model information, and determine whether the target cloud-native application meets the delivery requirements based on the deployment results.

[0052] The target cloud-native application is deployed in different environments using the application model information obtained above. The deployment results are then used to determine whether the target cloud-native application meets the expected delivery requirements.

[0053] The cloud-native application delivery method provided in this application selects a target application from multiple cloud-native applications and obtains its application model information, including component configuration, operational characteristics, environment configuration strategies, and workflows. The automated deployment tool understands the application model information and automatically executes deployment tasks based on this information. The tool should support multiple cloud environments and deployment strategies to adapt to different deployment needs. After deployment, it automatically verifies whether the application meets delivery requirements. Automated deployment reduces manual operations, shortens deployment time, and improves deployment efficiency. Standardized application model information and automated deployment tools ensure deployment consistency across different environments and time points. Automatic verification after deployment ensures the application meets delivery requirements, improving application quality and reliability. By utilizing application model information, the automatic generation of deployment configuration parameters and the automation of the deployment process are achieved, effectively simplifying the complexity of the underlying infrastructure. This process greatly promotes rapid and convenient application delivery, significantly reducing users' manual operation needs and learning costs. In this way, users can focus more on the core business logic of the application without being troubled by the underlying technical details, thereby improving overall work efficiency and application quality. Cloud-native applications can achieve efficient and consistent deployment and delivery.

[0054] Figure 4 A flowchart illustrating the cloud-native application delivery method provided in this application. Figure 2 ,like Figure 4 As shown, in this embodiment... Figure 2 Based on the examples, the cloud-native application delivery method is described in detail, which includes:

[0055] S401. When selecting a target cloud-native application from multiple cloud-native applications, obtain the application model information of the target cloud-native application. The application model information includes the defined component configuration, operation and maintenance characteristics, environment configuration strategy, and workflow of the target cloud-native application. The component configuration defines the workload corresponding to each microservice. The operation and maintenance characteristics define the operation and maintenance parameters corresponding to each component. The environment configuration strategy defines the configuration information and configuration strategy corresponding to the development and testing environment, the pre-release environment, and the production environment. The workflow defines the pipeline information corresponding to the development and testing environment, the pre-release environment, and the production environment.

[0056] S402. Based on the application model information, instantiate the component configuration, operation and maintenance features, environment configuration strategy, and workflow to obtain the target cloud-native application instance.

[0057] During the application delivery preparation phase, application model information is instantiated into specific configurations and processes.

[0058] In one possible implementation, component configuration instantiation, operational feature instantiation, environment configuration policy instantiation, and workflow instantiation are performed based on application model information to obtain the target cloud-native application instance. Specifically, this may include the following steps:

[0059] Based on the component configuration in the application model information, the basic information of the application to which the component belongs, the basic information of the component, and the component type are instantiated to obtain the component configuration instantiation information;

[0060] Based on the operation and maintenance characteristics in the application model information, and combined with the application resource requirement information, the operation and maintenance parameters in the operation and maintenance characteristics are instantiated into corresponding configuration parameters in different deployment environments to obtain the operation and maintenance characteristic instantiation information.

[0061] Based on the environment configuration strategy in the application model information, instantiate the environment configuration information of the application deployment to obtain the environment configuration strategy instantiation information.

[0062] Based on the workflow in the application model information, the pipeline information of the application deployment is instantiated to obtain the workflow instantiation information;

[0063] Based on component configuration instantiation information, operation and maintenance feature instantiation information, environment configuration policy instantiation information, and workflow instantiation information, the target cloud-native application instance is obtained.

[0064] In this implementation, cloud-native application instances are created based on application model information, specifically including:

[0065] Component configuration instantiation: Instantiate the basic information of the application to which the component belongs (such as application ID, name, etc.), instantiate the basic information of each component (such as component ID, name, etc.), and component type (such as front-end, back-end, etc.), so as to transform the component configuration in the application model into specific instantiation information.

[0066] Operation and maintenance feature instantiation: Based on the application's resource requirements, the operation and maintenance parameters (such as resource allocation, number of replicas, affinity, etc.) in the operation and maintenance features are instantiated into configuration parameters suitable for development, testing, pre-release and production environments to ensure that the application can be effectively supported in different environments.

[0067] Environment configuration strategy instantiation: Instantiate the configuration information of the application in the development and testing environment, pre-release environment and production environment.

[0068] Workflow instantiation: Instantiation is used for continuous integration and continuous deployment pipeline information in development and testing environments, for pre-release pipeline information in pre-release environments, and for formal release pipeline information in production environments.

[0069] Instantiated application deployment pipeline information, including continuous integration and continuous deployment pipelines, pre-release pipelines, and formal release pipeline information.

[0070] Integrate all instantiated information into a complete cloud-native application instance.

[0071] S403. Deploy the target cloud-native application instance to the development and testing environment to obtain the first deployment result.

[0072] Deploying target cloud-native application instances in a development and testing environment aims to quickly verify whether the code meets expectations. Continuous integration and continuous deployment pipelines can be used to automate the entire deployment process.

[0073] In one possible implementation, the workflow instantiation information includes instantiated continuous integration and continuous deployment pipeline information, deploying the target cloud-native application instance to the development and testing environment to obtain a first deployment result, which may specifically include the following steps:

[0074] The instantiated continuous integration and continuous deployment pipeline information is merged with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information, and environment configuration policy instantiation information to generate the first pipeline execution parameters;

[0075] Based on the first pipeline execution parameters, create an application image, deploy the application image in the development and testing environment, and obtain the first deployment parameters and the first pipeline execution details;

[0076] Based on the first deployment parameters and the first pipeline execution details, the first deployment result is generated.

[0077] The deployment process for the development and testing environment may specifically include:

[0078] 1. Obtain continuous integration and continuous deployment pipeline information: This can be extracted from workflow instantiation information, including basic information of the continuous integration and continuous deployment pipeline, code repository information, pipeline variables, etc.

[0079] 2. Initialize the continuous integration and continuous deployment pipeline: Integrate the continuous integration and continuous deployment pipeline information with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information and environment configuration strategy instantiation information to generate pipeline execution parameters for deploying the development and testing environment, i.e., the first pipeline execution parameters.

[0080] 3. Execute the continuous integration and continuous deployment pipeline: First, build the application image based on the execution parameters of the first pipeline. Second, deploy the built application image to the specified development and testing environment and allocate resources to it to complete the deployment in the development and testing environment. Finally, save the deployment parameters and pipeline execution details to the database.

[0081] 4. Development, testing, and deployment result verification: After completing the application deployment in the development and testing environment, quickly verify whether the code meets expectations based on the deployment parameters and pipeline execution details.

[0082] S404. If the first deployment result is verified, the target cloud-native application instance will be deployed to the pre-release environment to obtain the second deployment result.

[0083] If the initial deployment passes verification, the integrated code can be deployed to a pre-release environment for testing, where the pre-release pipeline can be used to automate the entire deployment process.

[0084] In one possible implementation, the workflow instantiation information includes instantiated pre-release pipeline information, which deploys the target cloud-native application instance to the pre-release environment to obtain a second deployment result. Specifically, this may include the following steps:

[0085] The instantiated pre-release pipeline information is merged with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information, and environment configuration policy instantiation information to generate the second pipeline execution parameters;

[0086] Based on the second pipeline execution parameters, the application image verified in the development and testing phase is deployed to the pre-release environment to obtain the second deployment parameters and the second pipeline execution details;

[0087] The second deployment result is generated based on the second deployment parameters and the second pipeline execution details.

[0088] The deployment process for a pre-release environment may specifically include:

[0089] 1. Obtain pre-release pipeline information: This can be extracted from workflow instantiation information, including basic information of the pre-release pipeline, pipeline variables, and application images that have been verified during the development and testing phases.

[0090] 2. Initialize the pre-release pipeline: The pre-release pipeline information is merged with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information and environment configuration policy instantiation information to generate pipeline execution parameters for deploying the pre-release environment, namely the second pipeline execution parameters.

[0091] 3. Execute the pre-release pipeline: Deploy the application image that has passed the development and testing phase to the specified pre-release environment and allocate resources to it to complete the deployment in the pre-release environment. Afterwards, the deployment parameters and pipeline execution details can be saved to the database.

[0092] 4. Pre-release deployment result verification: After completing the pre-release application deployment, verify whether it meets expectations based on the deployment parameters and pipeline execution details. If the verification passes, it proves that the application has reached a deliverable state and can be deployed to the production environment.

[0093] S405. If the second deployment result is verified, the target cloud-native application instance is deployed to the production environment to obtain the third deployment result.

[0094] If the second deployment result is verified, the integrated code can be deployed to the production environment and made available to users. The deployment process can be automated by relying on the official release pipeline.

[0095] In one possible implementation, the workflow instantiation information includes the formal release pipeline information of the instantiation, deploying the target cloud-native application instance to the production environment to obtain a third deployment result, which may specifically include the following steps:

[0096] The instantiated formal release pipeline information is merged with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information, and environment configuration strategy instantiation information to generate the third pipeline execution parameters;

[0097] Based on the third pipeline execution parameters, the application image from the pre-release stage will be deployed to the production environment to obtain the third deployment parameters and third pipeline execution details;

[0098] The third deployment result is generated based on the third deployment parameters and the third pipeline execution details.

[0099] The deployment process for the production environment may specifically include:

[0100] 1. Obtain information about the official release pipeline: This can be extracted from the workflow instantiation information, including basic information about the official release pipeline, pipeline variables, and application images that have been validated in the pre-release phase.

[0101] 2. Initialize the production pipeline: The production pipeline information is merged with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information and environment configuration strategy instantiation information to generate pipeline execution parameters for deploying to the production environment, namely the third pipeline execution parameters.

[0102] 3. Execute the formal release pipeline: Deploy the application image that has passed the pre-release phase to the designated production environment and allocate resources to it to complete the deployment in the production environment. Afterwards, the deployment parameters and pipeline execution details can be saved to the database.

[0103] 4. Production Deployment Result Verification: After completing the application deployment in the production environment, verify whether it meets expectations based on the deployment parameters and pipeline execution details. If the verification passes, the application is officially released to users.

[0104] S406. If the third deployment result is verified, a delivery confirmation message is generated, indicating that the target cloud-native application meets the delivery requirements.

[0105] The application delivery process uses application model information to generate deployment configuration parameters and automate deployment, shielding users from complex underlying infrastructure and helping them deliver applications quickly and easily, reducing manual operation and learning costs.

[0106] Reference Figure 5The diagram illustrates the delivery process of the cloud-native application delivery method provided in this application, including an application model layer and an application delivery layer. The application model layer primarily consists of component configurations, operational characteristics, workflows, and environment configuration strategies. This information collectively constitutes the application model, providing the foundation for application instantiation and delivery. Based on a standardized application model, the basic information, characteristics, behaviors, and deployment requirements of the application can be effectively described and defined, spanning different stages of cloud-native application development and delivery. The application delivery layer, driven by the application model, implements full lifecycle management of the application, including design, development testing, pre-release, and production stages, providing developers with a standardized cloud-native application delivery process. The overall implementation process of cloud-native application delivery is as follows: Figure 6 As shown.

[0107] This application's technical solution provides a unified design and definition for the application model, shielding it from complex underlying infrastructure, various cloud-native definitions, and YAML specifications. This effectively reduces cloud usage complexity and learning costs. The model-driven cloud-native application delivery solution proposed in this application avoids switching between multiple technology platforms during application delivery and reduces the workload of user configuration pipelines, thereby significantly improving delivery efficiency. Inconsistent descriptions of application characteristics, behaviors, and deployment requirements lead to poor maintainability. Frequent manual intervention by users in the application delivery process often results in decreased configuration accuracy and efficiency. This solution's unified application model definition and application delivery process effectively improves application stability and accelerates upper-layer business iteration. The application model in this application is independent of specific application systems, possessing portability and scalability. As long as the application system defines its own modular component configurations and operational characteristics, a suitable application architecture and operational capabilities can be quickly built.

[0108] The cloud-native application delivery method provided in this application selects a target application from multiple cloud-native applications and obtains its application model information, including component configuration, operational characteristics, environment configuration strategies, and workflows. The automated deployment tool understands the application model information and automatically executes deployment tasks based on this information. The tool should support multiple cloud environments and deployment strategies to adapt to different deployment needs. After deployment, it automatically verifies whether the application meets delivery requirements. Automated deployment reduces manual operations, shortens deployment time, and improves deployment efficiency. Standardized application model information and automated deployment tools ensure deployment consistency across different environments and time points. Automatic verification after deployment ensures the application meets delivery requirements, improving application quality and reliability. By utilizing application model information, the automatic generation of deployment configuration parameters and the automation of the deployment process are achieved, effectively simplifying the complexity of the underlying infrastructure. This process greatly promotes rapid and convenient application delivery, significantly reducing users' manual operation needs and learning costs. In this way, users can focus more on the core business logic of the application without being troubled by the underlying technical details, thereby improving overall work efficiency and application quality. Cloud-native applications can achieve efficient and consistent deployment and delivery.

[0109] Figure 7 A schematic diagram of the structure of the cloud-native application delivery device provided in this application is shown below. Figure 7 As shown, the cloud-native application delivery device 70 provided in this embodiment includes:

[0110] The acquisition module 701 is used to acquire the application model information of the target cloud-native application when selecting the target cloud-native application from multiple cloud-native applications. The application model information includes the defined component configuration, operation and maintenance characteristics, environment configuration strategy and workflow of the target cloud-native application. The component configuration defines the workload corresponding to each microservice, the operation and maintenance characteristics define the operation and maintenance parameters corresponding to each component, the environment configuration strategy defines the configuration information and configuration strategy corresponding to the development and testing environment, the pre-release environment and the production environment, and the workflow defines the pipeline information corresponding to the development and testing environment, the pre-release environment and the production environment.

[0111] The deployment and determination module 702 is used to deploy the target cloud-native application based on the application model information, and determine whether the target cloud-native application meets the delivery requirements based on the deployment results.

[0112] In one possible implementation, the deployment and determination module is specifically used for:

[0113] Based on application model information, component configuration instantiation, operation and maintenance feature instantiation, environment configuration strategy instantiation, and workflow instantiation are performed to obtain the target cloud-native application instance;

[0114] Deploy the target cloud-native application instance to the development and testing environment to obtain the first deployment result;

[0115] If the first deployment result is verified, the target cloud-native application instance will be deployed to the pre-release environment to obtain the second deployment result;

[0116] If the second deployment result is verified, the target cloud-native application instance will be deployed to the production environment to obtain the third deployment result;

[0117] If the third deployment result is verified, a delivery confirmation message is generated, indicating that the target cloud-native application meets the delivery requirements.

[0118] In one possible implementation, the deployment and determination module is specifically used for:

[0119] Based on the component configuration in the application model information, the basic information of the application to which the component belongs, the basic information of the component, and the component type are instantiated to obtain the component configuration instantiation information;

[0120] Based on the operation and maintenance characteristics in the application model information, and combined with the application resource requirement information, the operation and maintenance parameters in the operation and maintenance characteristics are instantiated into corresponding configuration parameters in different deployment environments to obtain the operation and maintenance characteristic instantiation information.

[0121] Based on the environment configuration strategy in the application model information, instantiate the environment configuration information of the application deployment to obtain the environment configuration strategy instantiation information.

[0122] Based on the workflow in the application model information, the pipeline information of the application deployment is instantiated to obtain the workflow instantiation information;

[0123] Based on component configuration instantiation information, operation and maintenance feature instantiation information, environment configuration policy instantiation information, and workflow instantiation information, the target cloud-native application instance is obtained.

[0124] In one possible implementation, the workflow instantiation information includes instantiated continuous integration and continuous deployment pipeline information, with the deployment and determination module specifically used for:

[0125] The instantiated continuous integration and continuous deployment pipeline information is merged with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information, and environment configuration policy instantiation information to generate the first pipeline execution parameters;

[0126] Based on the first pipeline execution parameters, create an application image, deploy the application image in the development and testing environment, and obtain the first deployment parameters and the first pipeline execution details;

[0127] Based on the first deployment parameters and the first pipeline execution details, the first deployment result is generated.

[0128] In one possible implementation, the workflow instantiation information includes instantiated pre-release pipeline information, and the deployment and determination module is specifically used for:

[0129] The instantiated pre-release pipeline information is merged with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information, and environment configuration policy instantiation information to generate the second pipeline execution parameters;

[0130] Based on the second pipeline execution parameters, the application image verified in the development and testing phase is deployed to the pre-release environment to obtain the second deployment parameters and the second pipeline execution details;

[0131] The second deployment result is generated based on the second deployment parameters and the second pipeline execution details.

[0132] In one possible implementation, the workflow instantiation information includes the instantiated formal release pipeline information, and the deployment and determination module is specifically used for:

[0133] The instantiated formal release pipeline information is merged with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information, and environment configuration strategy instantiation information to generate the third pipeline execution parameters;

[0134] Based on the third pipeline execution parameters, the application image from the pre-release stage will be deployed to the production environment to obtain the third deployment parameters and third pipeline execution details;

[0135] The third deployment result is generated based on the third deployment parameters and the third pipeline execution details.

[0136] The cloud-native application delivery device provided in this embodiment can execute the methods provided in the above method embodiments. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0137] Figure 8 A schematic diagram of the cloud-native application delivery device provided in this application. Figure 8 As shown, the cloud-native application delivery device 80 provided in this embodiment includes at least one processor 801 and a memory 802. Optionally, the device 80 further includes a communication component 803. The processor 801, memory 802, and communication component 803 are connected via a bus.

[0138] In a specific implementation, at least one processor 801 executes computer execution instructions stored in memory 802, causing at least one processor 801 to perform the above-described method.

[0139] The specific implementation process of processor 801 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0140] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this application can be directly manifested as execution by a hardware processor, or execution by a combination of hardware and software modules within the processor.

[0141] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0142] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0143] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0144] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0145] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0146] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0147] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0148] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0149] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0150] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0151] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0152] Finally, it should be noted that other embodiments of this application will readily conceive of by those skilled in the art upon consideration of the specification and practice of the application disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and alterations may be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A cloud-native application delivery method, characterized in that, include: When selecting a target cloud-native application from multiple cloud-native applications, the application model information of the target cloud-native application is obtained. The application model information includes the component configuration, operation and maintenance characteristics, environment configuration strategy, and workflow of the target cloud-native application. The component configuration defines the workload corresponding to each microservice. The operation and maintenance characteristics define the operation and maintenance parameters corresponding to each component. The environment configuration strategy defines the configuration information and configuration strategy corresponding to the development and testing environment, the pre-release environment, and the production environment. The workflow defines the pipeline information corresponding to the development and testing environment, the pre-release environment, and the production environment. The target cloud-native application is deployed based on the application model information, and the deployment results are used to determine whether the target cloud-native application meets the delivery requirements.

2. The method according to claim 1, characterized in that, The process of deploying the target cloud-native application based on the application model information and determining whether the target cloud-native application meets the delivery requirements based on the deployment results includes: Based on the application model information, component configuration instantiation, operation and maintenance feature instantiation, environment configuration strategy instantiation, and workflow instantiation are performed to obtain the target cloud-native application instance; Deploy the target cloud-native application instance to the development and testing environment to obtain the first deployment result; If the first deployment result is verified, the target cloud-native application instance is deployed to the pre-release environment to obtain the second deployment result; If the second deployment result is verified, the target cloud-native application instance is deployed to the production environment to obtain the third deployment result; If the third deployment result is verified, a delivery confirmation message is generated, indicating that the target cloud-native application meets the delivery requirements.

3. The method according to claim 2, characterized in that, The instantiation of component configuration, operation and maintenance features, environment configuration strategy, and workflow based on the application model information to obtain the target cloud-native application instance includes: Based on the component configuration in the application model information, the basic information of the application to which the component belongs, the basic information of the component, and the component type are instantiated to obtain the component configuration instantiation information; Based on the operation and maintenance characteristics in the application model information, and combined with the application resource requirement information, the operation and maintenance parameters in the operation and maintenance characteristics are instantiated into corresponding configuration parameters in different deployment environments to obtain the operation and maintenance characteristic instantiation information. Based on the environment configuration strategy in the application model information, instantiate the environment configuration information for application deployment to obtain environment configuration strategy instantiation information. Based on the workflow in the application model information, the pipeline information of the application deployment is instantiated to obtain the workflow instantiation information; Based on the component configuration instantiation information, the operation and maintenance feature instantiation information, the environment configuration policy instantiation information, and the workflow instantiation information, the target cloud-native application instance is obtained.

4. The method according to claim 3, characterized in that, The workflow instantiation information includes instantiated continuous integration and continuous deployment pipeline information. Deploying the target cloud-native application instance to the development and testing environment to obtain the first deployment result includes: The instantiated continuous integration and continuous deployment pipeline information is fused with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information, and environment configuration policy instantiation information to generate the first pipeline execution parameters; Based on the first pipeline execution parameters, an application image is created, and the application image is deployed in the development and testing environment to obtain the first deployment parameters and the first pipeline execution details. The first deployment result is generated based on the first deployment parameters and the first pipeline execution details.

5. The method according to claim 3, characterized in that, The workflow instantiation information includes instantiated pre-release pipeline information. Deploying the target cloud-native application instance to the pre-release environment to obtain a second deployment result includes: The instantiated pre-release pipeline information is fused with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information, and environment configuration policy instantiation information to generate the second pipeline execution parameters; Based on the second pipeline execution parameters, the application image verified in the development and testing phase is deployed to the pre-release environment to obtain the second deployment parameters and the second pipeline execution details; The second deployment result is generated based on the second deployment parameters and the second pipeline execution details.

6. The method according to claim 3, characterized in that, The workflow instantiation information includes the instantiated formal release pipeline information. The step of deploying the target cloud-native application instance to the production environment to obtain a third deployment result includes: The instantiated formal release pipeline information is fused with the corresponding component configuration instantiation information, operation and maintenance feature instantiation information, and environment configuration strategy instantiation information to generate the third pipeline execution parameters; Based on the third pipeline execution parameters, the application image from the pre-release stage will be deployed to the production environment to obtain the third deployment parameters and the third pipeline execution details; The third deployment result is generated based on the third deployment parameters and the third pipeline execution details.

7. A cloud-native application delivery device, characterized in that, include: The acquisition module is used to acquire the application model information of the target cloud-native application when selecting a target cloud-native application from multiple cloud-native applications. The application model information includes the defined component configuration, operation and maintenance characteristics, environment configuration strategy, and workflow of the target cloud-native application. The component configuration defines the workload corresponding to each microservice. The operation and maintenance characteristics define the operation and maintenance parameters corresponding to each component. The environment configuration strategy defines the configuration information and configuration strategy corresponding to the development and testing environment, the pre-release environment, and the production environment. The workflow defines the pipeline information corresponding to the development and testing environment, the pre-release environment, and the production environment. The deployment and determination module is used to deploy the target cloud-native application based on the application model information, and determine whether the target cloud-native application meets the delivery requirements based on the deployment results.

8. A cloud-native application delivery device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-6.

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