CN116594740A - Polymorphic application cloud loading method based on industry heterogeneous cloud environment - Google Patents
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Abstract
The invention provides a polymorphic application cloud loading method based on an industry heterogeneous cloud environment, which belongs to the technical field of cloud platform management and comprises the following steps: accessing a virtualized environment; step two: resource intelligent scheduling configuration; step three: scheduling service resources; step four: application running support. The problems of difficult cloud loading, slow cloud loading, uncontrollable cloud loading and the like caused by different cloud loading requirements of traditional monomer applications, distributed architecture applications, cloud primary application containerized deployment and the like under an industry heterogeneous cloud computing environment are solved, and the automatic deployment delivery and full life cycle management of the applications in various forms under the industry heterogeneous cloud environment are realized through three modes of a virtual machine, a cloud application engine and a container, so that the cloud loading difficulty of the applications is reduced, and the cloud loading efficiency of the applications is improved.
Description
Technical Field
The invention relates to the technical field of cloud platform management, in particular to a polymorphic application cloud loading method based on an industry heterogeneous cloud environment.
Background
In the actual industry production environment, the informatization construction of the clients is gradual, the construction of the clients in an infrastructure layer also undergoes continuous evolution and alternation, and the wide use from the past physical machine clusters to the virtualization technology and the popularization of the containerization technology lead to the fact that the basic resource environment of the clients always has a plurality of heterogeneous resource pools and has a certain technical difference, so that a unified cloud service management platform is constructed on the basic resource pool of the clients, and the construction of a service operation environment is realized by scheduling different bottom layer resources.
The cloud service management platform provides an application running environment for an upper business system by adapting heterogeneous IaaS resources of a bottom layer, encapsulates resources such as calculation, storage, network, security, database, big data calculation, application middleware, general application support components and the like into services, covers the IaaS field and PaaS field comprehensively, shields the technical difficulty of the bottom layer, meets the service requirements of clients with different roles in the ecological environment, and provides rich services with different fields and different layers for further data analysis and application innovation.
Secondly, the applied architecture is updated and iterated continuously, and the single application in the past is gradually developed to be distributed and containerized, so that the development period is long and the technical span is large in the current industrial informatization development process, and not all service systems are developed or modified by adopting the latest technical architecture due to the limitation of various reasons such as the software maintenance period, the technical capability of application developers and the like. In the reality, the business system technical architecture, the deployment architecture and the running environment of the client coexist in various forms, and how to ensure the running support of the multi-form application of the client in the industry in the heterogeneous cloud environment is a real problem to be solved.
The basic resource layer is mainly divided into the following resource levels:
the first layer contains server, storage and network resources, being the lowest hardware resources. Servers can be classified into general types, computing I/O types and computing storage types according to the type of cloud application service carried and the performance characteristics of the servers. The I/0 performance of a storage device varies from storage medium to storage medium.
The second layer is an available partition layer, which is used for logically partitioning computing, storing and network resources in an IaaS environment, and one available partition is not affected by faults of other available partitions. A plurality of available partitions can be arranged in one area, the internal networks among the available partitions are communicated, and resources among different available partitions are isolated, so that the independence of the available partitions is ensured, and low-cost and low-delay network connection is provided.
The third layer is a virtual data center layer, the virtual data center is a group of packaged computing, storage and network resource sets, the ultimate implementation of the virtualization technology in the data center is realized, and the virtualization technology is ubiquitous in the data center in the future. The data center can be called VDC when the data center fully performs virtualization. VDC integrates all hardware (including servers, memory, and networks) into a single logical resource, thereby improving the efficiency and flexibility of use of the system, as well as the availability and scalability of application software.
The fourth layer is a virtual resource pool layer, a plurality of virtual data center resources are contained in one virtual resource pool, fusion of heterogeneous resources is realized, the virtual resource pool is bound with business organization institutions of industries, the use authority of users in the current organization on the resources in the current pool is regulated, and meanwhile, the distribution and control of the enterprises information center and other institutions on the whole resources are realized in a quota management mode.
On the basis of the basic resources, according to the application requirements of the industry business system, basic resource class services (computing resource services, storage resource services, network resource services) and platform support services (computing services, storage services, development services and support services) can be provided.
The service system can be divided into different types such as single application, distributed architecture application, containerized application and the like according to the technical architecture characteristics.
Monomer application: also known as a monolithic system or a monolithic architecture. It is an architecture that couples all the functions, modules in the system into one application. I.e., project organization in which all code and functions are contained in one WAR packet. The system consists of a plurality of modules (all resources) which are arranged into a war package and run on a server, namely a process is run.
Distributed application: compared with single application, the distributed architecture application firstly splits middleware and a database used by the application, and the application running environment and the database are changed from the original single node to distributed high-availability architecture deployment, so that the reliability of the application is improved; in addition, certain applications carry out certain granularity splitting and decoupling on the modules of the applications on the basis, and each module is independently deployed, so that the service system can be more conveniently and flexibly expanded.
Containerized application: this process of integrating and running applications into containers is called "containerization" (sometimes also called "dockerination"). Containers are native to the application, and in particular, containers can simplify the build, deployment, and execution processes of the application.
Disclosure of Invention
In order to solve the technical problems, the invention provides a polymorphic application cloud loading method based on an industry heterogeneous cloud environment. The problems of difficult cloud loading, slow cloud loading, uncontrollable cloud loading and the like caused by different cloud loading requirements of traditional monomer applications, distributed architecture applications, cloud primary application containerized deployment and the like under an industry heterogeneous cloud computing environment are solved, and the automatic deployment delivery and full life cycle management of the applications in various forms under the industry heterogeneous cloud environment are realized through three modes of a virtual machine, a cloud application engine and a container, so that the cloud loading difficulty of the applications is reduced, and the cloud loading efficiency of the applications is improved.
The technical scheme of the invention is as follows:
a polymorphic application cloud loading method based on an industry heterogeneous cloud environment, comprising:
step one: accessing a virtualized environment;
step two: resource intelligent scheduling configuration;
step three: scheduling service resources;
step four: application running support.
Further, the method comprises the steps of,
the management and the scheduling of the cloud platform to the underlying IaaS resources are realized, and the connection between the cloud platform and the IaaS environment is opened from the following four dimensions
(1) The north interface of the IaaS is scheduled to realize data synchronization, mirror synchronization and full life cycle management of the virtual machine of the bottom resource pool;
(2) Receiving various asynchronous operation and management instructions issued by a cloud platform by installing a deployment Agent on a virtual machine, and realizing issuing, automatic deployment and full life cycle management of cloud middleware and a database in the virtual machine;
(3) Through the IaaS layer north interface and the Agent, the on-line monitoring of the virtual machine and the cloud service component is realized;
(4) By setting monitoring and alarming indexes in the cloud platform, the health conditions of the virtual machine and the cloud service assembly are calculated and evaluated.
Further, the method comprises the steps of,
to realize intelligent scheduling of resources, firstly, labeling processing of the resources is required, classification labels are used for achieving the functions of identification and classification, and labeling is carried out on available subareas according to the characteristics of the resources through a cloud service management platform, so that grouping and classification of resource objects are realized.
After the interface and the labeling configuration of the bottom layer resources are completed, the resource demands of the business departments for calculation, storage and network are collected by taking the departments as units, and the cloud platform resources are distributed layer by layer through the virtual resource pool and the virtual resource center.
After the three steps of configuration are completed, the intelligent scheduling of the resources can be realized through the cloud service management platform.
Further, the method comprises the steps of,
the cloud service management platform provides application online management capability, realizes classified storage of different application program packages through newly built application programs, can store more than one version of each application program, and can ensure the safety and stability of the storage of the program package media by uploading the application program packages to more than one copy in the cloud platform object storage for storage.
The system also provides the functions of uploading, downloading, editing, deleting, transferring the program package to mirror image and accessing the application, and needs to support uploading of program packages in common formats such as war, zip, jar, and support uploading of full-volume packages and incremental packages so as to facilitate incremental updating of the application by users.
Providing a unified application instance management interface, realizing full life cycle management of application creation, deletion, starting, stopping, restarting and upgrading, and in addition, the application list visually shows the running state of the application and provides a quick application access entry;
when creating the application, the user can select different deployment modes according to the type of the application medium, including virtual machine deployment, application engine deployment and containerization deployment.
Based on a virtual machine deployment mode, uploading and starting an application program package of a developer to the virtual machine through an automatic shell script, and providing an application access function;
based on an application engine deployment mode, a developer applies for a distributed application engine service provided by a cloud service management platform, the platform calls underlying basic resources, the distributed application engine service is automatically deployed, and the high concurrency requirement of an application system in a period of time can be met by providing the characteristics of load balancing, session maintenance and session sharing;
based on the containerized deployment approach, support for kustmize and Chart packages is required for managing application templates based on the Kubernetes Helm standard through a template repository.
The invention has the beneficial effects that
Aiming at the problems of difficult cloud loading, slow cloud loading, uncontrollable cloud loading and the like caused by different cloud loading requirements of traditional single application, distributed architecture application, cloud primary application containerized deployment and the like in an industry heterogeneous cloud computing environment, the cloud loading efficiency of the application is greatly improved, and the cloud loading management quality is improved.
Drawings
FIG. 1 is a schematic diagram of hierarchical scheduling of service resources in accordance with the present invention;
FIG. 2 is a diagram of a polymorphic application cloud approach.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by those skilled in the art without making any inventive effort based on the embodiments of the present invention are within the scope of protection of the present invention.
The invention provides a polymorphic application cloud loading method based on an industry heterogeneous cloud environment, which comprehensively considers factors such as technical architecture, application scene, resource requirement and the like of different applications, provides a plurality of application automation deployment strategies, realizes application cloud loading of a business system with a plurality of forms in the heterogeneous cloud environment, and comprises the following steps:
step one: accessing virtualized environments
To realize management and scheduling of the cloud platform to the underlying IaaS resources, connection between the cloud platform and the IaaS environment needs to be opened from the following four dimensions.
(1) And through the north interface of the dispatching IaaS, the data synchronization, the mirror synchronization, the full life cycle management of the virtual machine and the like of the bottom resource pool are realized.
(2) By means of installing the deployment Agent on the virtual machine, various asynchronous operation and management instructions issued by the cloud platform are received, and issuing, automatic deployment and full life cycle management of services such as cloud middleware and databases in the virtual machine are realized.
(3) And realizing on-line monitoring of the virtual machine and the cloud service component through the IaaS layer northbound interface and the Agent.
(4) By setting monitoring and alarming indexes in the cloud platform, the health conditions of the virtual machine and the cloud service assembly are calculated and evaluated.
Step two: resource-intelligent scheduling configuration
To realize four-level intelligent scheduling of resources, firstly, labeling processing is performed on the resources, classification labels are used for playing a role in identification and classification, and labeling is performed on available partition layers according to the characteristics of the resources through a cloud service management platform, so that grouping and classification of resource objects are realized.
After the interface and the labeling configuration of the bottom layer resources are completed, the resource demands of the business departments for calculation, storage and network are collected by taking the departments as a unit and taking the construction demands of the application system as a basis, and the cloud platform resources are distributed layer by layer through the virtual resource pool and the virtual resource center.
Step three: service resource scheduling
After the three steps of configuration are completed, the intelligent scheduling of the resources can be realized through the cloud service management platform. As shown in fig. 1, taking a developer of the department 3 applies for a Mysql database as an example, the cloud platform realizes optimal matching of resources and optimal utilization of the resources through virtual resource pool level scheduling, VDC level scheduling, available partition level scheduling and IaaS level scheduling.
Step four: application running support
In the cloud service management platform, application online management capability is provided, classification storage of different application packages is realized through newly built application programs, each application program can store multiple versions, the application packages are uploaded to the cloud platform object storage for multiple copies to be stored, and the safety and stability of package media storage are ensured. Providing functions of uploading, downloading, editing, deleting, transferring image of program package, accessing application, etc. needs to support uploading war, zip, jar program package in common format, and supports uploading full package and incremental package so as to facilitate incremental update of application by user.
And meanwhile, a unified application instance management interface is provided for a developer, full life cycle management such as application creation, deletion, starting, stopping, restarting and upgrading is realized, in addition, the application list can intuitively display the running state of the application, and a quick application access entry is provided for a user. When creating the application, the user can select different deployment modes according to the type of the application medium, including virtual machine deployment, application engine deployment and containerization deployment.
Based on a virtual machine deployment mode, uploading and starting an application program package of a developer to the virtual machine are achieved through an automatic shell script, and an application access function is provided. This deployment is suitable for single function or traditional monolithic applications.
Based on the application engine deployment mode, a developer applies for the distributed application engine service provided by the cloud service management platform, the platform calls the underlying basic resource, the distributed application engine service is automatically deployed, and the high concurrency requirement of an application system in a certain time period can be met by providing the characteristics of load balancing, session maintenance, session sharing and the like.
Based on the containerized deployment approach, the mainstream kustmize and Chart package program support is required, and through a template warehouse, the application templates based on the Kubernetes Helm standard are managed. The rapid deployment of the templates is efficiently realized, and the lightweight and high elasticity of containerized application are realized.
The foregoing description is only illustrative of the preferred embodiments of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.
Claims (8)
1. A polymorphic application cloud loading method based on an industry heterogeneous cloud environment is characterized in that,
comprising the following steps:
step one: accessing a virtualized environment;
step two: resource intelligent scheduling configuration;
step three: scheduling service resources;
step four: an application running support;
the management and the scheduling of the cloud platform to the underlying IaaS resources are realized, and the connection between the cloud platform and the IaaS environment is opened from the following four dimensions
(1) The north interface of the IaaS is scheduled to realize data synchronization, mirror synchronization and full life cycle management of the virtual machine of the bottom resource pool;
(2) Receiving various asynchronous operation and management instructions issued by a cloud platform by installing a deployment Agent on a virtual machine, and realizing issuing, automatic deployment and full life cycle management of cloud middleware and a database in the virtual machine;
(3) Through the IaaS layer north interface and the Agent, the on-line monitoring of the virtual machine and the cloud service component is realized;
(4) By setting monitoring and alarming indexes in the cloud platform, the health conditions of the virtual machine and the cloud service assembly are calculated and evaluated.
2. The method of claim 1, wherein the step of determining the position of the substrate comprises,
to realize intelligent scheduling of resources, firstly, labeling processing of the resources is required, classification labels are used for achieving the functions of identification and classification, and labeling is carried out on available subareas according to the characteristics of the resources through a cloud service management platform, so that grouping and classification of resource objects are realized.
3. The method of claim 2, wherein the step of determining the position of the substrate comprises,
after the interface and the labeling configuration of the bottom layer resources are completed, the resource demands of the business departments for calculation, storage and network are collected by taking the departments as units, and the cloud platform resources are distributed layer by layer through the virtual resource pool and the virtual resource center.
4. The method of claim 1, wherein the step of determining the position of the substrate comprises,
after the three steps of configuration are completed, the intelligent scheduling of the resources can be realized through the cloud service management platform.
5. The method of claim 1, wherein the step of determining the position of the substrate comprises,
the cloud service management platform provides application online management capability, classification storage of different application program packages is achieved through newly built application programs, each application program can store more than one version, and the application program packages are uploaded to more than one copy in the cloud platform object storage for storage.
6. The method of claim 5, wherein the step of determining the position of the probe is performed,
the system also provides the functions of uploading, downloading, editing, deleting, transferring the program package into mirror image and accessing the application, and supports uploading war, zip, jar format program packages, and supporting uploading full-volume packages and increment packages, thereby facilitating the increment updating of the application by users.
7. The method of claim 6, wherein the step of providing the first layer comprises,
providing a unified application instance management interface, realizing full life cycle management of application creation, deletion, starting, stopping, restarting and upgrading, and in addition, the application list visually shows the running state of the application and provides a quick application access entry;
when creating the application, the user can select different deployment modes according to the type of the application medium, including virtual machine deployment, application engine deployment and containerization deployment.
8. The method of claim 7, wherein the step of determining the position of the probe is performed,
based on a virtual machine deployment mode, uploading and starting an application program package of a developer to the virtual machine through an automatic shell script, and providing an application access function;
based on an application engine deployment mode, a developer applies for a distributed application engine service provided by a cloud service management platform, the platform calls underlying basic resources, the distributed application engine service is automatically deployed, and the high concurrency requirement of an application system in a period of time can be met by providing the characteristics of load balancing, session maintenance and session sharing;
based on the containerized deployment approach, support for kustmize and Chart packages is required for managing application templates based on the Kubernetes Helm standard through a template repository.
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20150324182A1 (en) * | 2014-05-09 | 2015-11-12 | International Business Machines Corporation | Automated deployment of a private modular cloud-computing environment |
CN113703791A (en) * | 2021-08-14 | 2021-11-26 | 济南浪潮数据技术有限公司 | Software deployment method, system, storage medium and equipment |
CN113867937A (en) * | 2021-08-29 | 2021-12-31 | 浪潮软件科技有限公司 | Resource scheduling method and device for cloud computing platform and storage medium |
CN113900769A (en) * | 2021-09-24 | 2022-01-07 | 浪潮软件科技有限公司 | Virtual machine monitoring method based on heterogeneous cloud computing environment |
CN114090174A (en) * | 2021-11-15 | 2022-02-25 | 交控科技股份有限公司 | City rail edge cloud integration equipment based on super integration |
CN115499310A (en) * | 2022-08-26 | 2022-12-20 | 浪潮软件科技有限公司 | Business application cloud method and system based on cloud computing platform container service |
-
2023
- 2023-07-18 CN CN202310876024.2A patent/CN116594740A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20150324182A1 (en) * | 2014-05-09 | 2015-11-12 | International Business Machines Corporation | Automated deployment of a private modular cloud-computing environment |
CN113703791A (en) * | 2021-08-14 | 2021-11-26 | 济南浪潮数据技术有限公司 | Software deployment method, system, storage medium and equipment |
CN113867937A (en) * | 2021-08-29 | 2021-12-31 | 浪潮软件科技有限公司 | Resource scheduling method and device for cloud computing platform and storage medium |
CN113900769A (en) * | 2021-09-24 | 2022-01-07 | 浪潮软件科技有限公司 | Virtual machine monitoring method based on heterogeneous cloud computing environment |
CN114090174A (en) * | 2021-11-15 | 2022-02-25 | 交控科技股份有限公司 | City rail edge cloud integration equipment based on super integration |
CN115499310A (en) * | 2022-08-26 | 2022-12-20 | 浪潮软件科技有限公司 | Business application cloud method and system based on cloud computing platform container service |
Non-Patent Citations (3)
Title |
---|
姜秀丽: "《基于Kubernetes的应用容器云实战》", 30 September 2021, 机械工业出版社, pages: 8 - 9 * |
范平平;: "云应用引擎技术的研究与策略", 科技视界, no. 28 * |
青岛英谷教育科技股份有限公司: "《云计算与大数据理论》", 31 August 2017, 西安电子科技大学出版社, pages: 67 - 68 * |
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