CN106843945B - PaaS-based GIS application deployment method and system - Google Patents
PaaS-based GIS application deployment method and system Download PDFInfo
- Publication number
- CN106843945B CN106843945B CN201710004696.9A CN201710004696A CN106843945B CN 106843945 B CN106843945 B CN 106843945B CN 201710004696 A CN201710004696 A CN 201710004696A CN 106843945 B CN106843945 B CN 106843945B
- Authority
- CN
- China
- Prior art keywords
- gis application
- gis
- application
- paas
- instance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000012360 testing method Methods 0.000 claims abstract description 26
- 238000004519 manufacturing process Methods 0.000 claims description 10
- 238000005516 engineering process Methods 0.000 claims description 5
- 238000002955 isolation Methods 0.000 claims description 5
- 238000011161 development Methods 0.000 abstract description 18
- 238000012423 maintenance Methods 0.000 abstract description 9
- 230000007547 defect Effects 0.000 abstract description 6
- 238000011160 research Methods 0.000 abstract description 4
- 238000012827 research and development Methods 0.000 description 6
- 238000007726 management method Methods 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 238000013468 resource allocation Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 235000014510 cooky Nutrition 0.000 description 1
- 238000001816 cooling Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000005096 rolling process Methods 0.000 description 1
- 239000000523 sample Substances 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F8/00—Arrangements for software engineering
- G06F8/60—Software deployment
Abstract
The invention discloses a GIS application deployment method and a system based on PaaS.A GIS application instance is deployed in a distributed designated container, so that the defect of heavy manual deployment is avoided, the deployment efficiency is high, the deployment success rate is high, all GIS applications can be accessed by a service through an intelligent router, and the use is convenient and flexible; the GIS application shares software and hardware resources, so that the resource utilization rate can be improved, and the cost is reduced; a user of research, development, test, operation and maintenance and business can share GIS application on the cloud platform, so that remote collaborative development and application are possible.
Description
Technical Field
The invention relates to the technical field of GIS application, in particular to a GIS application deployment method and a GIS application deployment system based on PaaS.
Background
PaaS (Platform-as-a-Service), a Platform-as-a-Service, refers to a business model that provides platforms such as a computing environment and a development environment as one type of Service. It is a cloud computing model between IaaS (Infrastructure-as-a-Service) and SaaS (Software-as-a-Service).
The traditional development and deployment of a set of GIS application system is a long process. Firstly, selecting a GIS platform for GIS application development; then testing in a test environment; and finally, when the GIS application system needs to be on-line, processes such as hardware application, purchase, transportation, installation and configuration of software and hardware and the like are required.
The operation and maintenance mode of the traditional GIS application mainly has the following problems:
it is impossible to cope with the rapid and variable service demands. During development and deployment, a plurality of departments such as a research and development department, a testing department, a material department, a financial department, an operation and maintenance department and the like need to cooperate with one another to be successfully completed. This will affect the system release period, making the update of the application unable to adapt to the speed of the change in the service demand.
The resource utilization rate is low, and the maintenance cost is high. In a traditional deployment mode, different GIS application systems cannot share hardware resources, and a test environment and a production environment cannot share the hardware resources. When the business peak comes, the system capacity can be expanded only by purchasing new server resources, but when the business peak comes, many servers are idle, and the utilization rate of the resources is low. Meanwhile, extra expenses in power supply, cooling and the like are brought to enterprises.
And the manual deployment of the system has low efficiency. Existing systems are typically distributed systems, and therefore require repeated installation and configuration of hardware and software resources for each server. This is a heavy task, time and labor consuming, and a large amount of repeated manual configuration work, which is very likely to cause failure of deployment.
The system deployment is difficult. In a traditional development mode, the research and development environment, the test environment and the production environment of a GIS application system are different. The operation and maintenance personnel deploy the system step by step according to the deployment manual written by the research and development personnel, but the deployment manual is possibly invalid due to the difference between the research and development environment and the production environment, and the deployment cannot be performed in the production environment.
The system is difficult to monitor and is difficult to track and position under the production environment. In a distributed environment, when a system has problems, operation and maintenance personnel need to log in different servers respectively to download system logs and then give the system logs to research and development personnel, the research and development personnel search the logs to perform problem location by adopting a manual mode in the face of massive discrete logs, and the operation and maintenance mode is difficult to effectively and accurately locate the position where the system problems occur and the reasons for the system problems.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the PaaS-based GIS application deployment method and system can rapidly deploy GIS applications.
In order to solve the technical problems, the invention adopts the technical scheme that: a GIS application deployment method based on PaaS comprises the following steps:
creating an example of the GIS application, and applying for hardware resources required by the example of the GIS application;
allocating hardware resources for the GIS application example, and starting a specified number of containers;
automatically mirror-deploying instances of the GIS applications at the container;
and registering the address of the started instance of the GIS application into the intelligent router.
The invention also relates to a GIS application deployment system based on PaaS, which comprises:
the creating module is used for creating an example of the GIS application;
the application module is used for applying for hardware resources required by the GIS application instance;
the allocation module is used for allocating hardware resources;
the starting module is used for starting the container;
the deployment module is used for deploying the instance of the GIS application in a mirror image mode;
and the registration module is used for registering the address of the started instance in the intelligent router.
The invention has the beneficial effects that: the GIS application is automatically deployed in the assigned container, so that the defect of heavy manual deployment is overcome, the deployment efficiency is high, the deployment success rate is high, all GIS applications can be accessed by the service through the intelligent router, and the use is convenient and flexible.
Drawings
FIG. 1 is a flow chart of GIS application deployment based on PaaS in the present invention;
fig. 2 is a flowchart of GIS application deployment based on PaaS according to an embodiment of the present invention;
fig. 3 is a block diagram of a GIS application deployment system based on PaaS according to an embodiment of the present invention;
description of reference numerals:
1. a creation module; 2. an application module; 3. a distribution module; 4. a starting module; 5. a deployment module; 6. and registering the module.
Detailed Description
In order to explain technical contents, achieved objects, and effects of the present invention in detail, the following description is made with reference to the accompanying drawings in combination with the embodiments.
The most key concept of the invention is as follows: and the GIS application instance is deployed in the assigned specified container, so that the defect of heavy manual deployment is overcome, the deployment efficiency is high, and the deployment success rate is high.
Referring to fig. 1 to fig. 3, a method for deploying GIS application based on PaaS includes:
creating an example of the GIS application, and applying for hardware resources required by the example of the GIS application;
allocating hardware resources for the GIS application example, and starting a specified number of containers;
automatically mirror-deploying instances of the GIS applications at the container;
and registering the address of the started instance of the GIS application into the intelligent router.
From the above description, the beneficial effects of the present invention are: the GIS application example is deployed in the assigned container, so that the defect of heavy manual deployment is overcome, the deployment efficiency is high, the deployment success rate is high, all GIS applications can be accessed by the service through the intelligent router, and the use is convenient and flexible.
Further, generating and storing a mirror image file of the GIS application.
Further, an image file of the GIS application is obtained, a virtual machine is started by using the image file, and specified resources are distributed, wherein the virtual machine adopts a container isolation technology.
As can be seen from the above description, the virtual machines adopt a container isolation technique, and resources between different virtual machines on the same server are isolated from each other, that is, one virtual machine cannot access resources of another virtual machine, and a crash of one virtual machine does not affect normal operations of the other virtual machines.
Further, whether the instances of the GIS application run normally or not is periodically detected, if not, the instances are closed, and new instances are deployed.
According to the description, the GIS application is periodically detected, and the normal operation of the GIS application can be ensured.
Further, when the performance load of the GIS application is too large, the number of instances of the GIS application is increased.
According to the description, increasing the number of GIS application instances can allocate more resources, and the burden of each GIS application instance is reduced.
Further, when the instance of the GIS application goes down, a new instance is created.
According to the description, the new instance is created when the instance is down, so that the GIS application can be ensured to run continuously and highly available.
Further, when the GIS application is upgraded, a new instance is deployed, and after the new instance is started successfully, the instance before the upgrade is closed.
According to the description, smooth upgrading of GIS application without shutdown can be realized, and normal operation of the GIS application at any time is guaranteed.
Further, a related log of the GIS application is recorded and stored.
According to the description, the related logs of the GIS application are stored, and subsequent calling and query are facilitated.
Further, before creating the instance of the GIS application, the method further includes:
registering the GIS application;
identifying a service interface in the GIS application, and issuing the GIS application in a protocol mode;
testing the issued GIS application;
and auditing the GIS application which passes the test, and releasing the GIS application to a production environment.
As can be seen from the above description, before the GIS application is released to the production environment, the GIS application needs to pass testing and auditing to ensure the reliability of the GIS application.
Furthermore, all GIS applications belonging to the same cloud platform share software and hardware resources on the cloud platform.
According to the description, the GIS application shares software and hardware resources, so that the resource utilization rate can be improved, and the cost is reduced.
Further, the cloud platform comprises a first unregistered GIS application and a second registered GIS application, and the first GIS application can call an interface jar package of the second GIS application.
As can be seen from the above description, GIS applications can be interdependent among themselves.
Furthermore, when the first GIS application is subjected to unit testing, a remote proxy object is created for the second GIS application interface, the instance of the second GIS application is accessed through the remote proxy object, and the result is returned to the first GIS application.
From the above description, when the first GIS application is deployed, the deployment of the second GIS application instance does not affect the test thereof.
Further, when the first GIS application passes the unit test, the first GIS application is registered.
A GIS application deployment system based on PaaS comprises:
the creating module is used for creating an example of the GIS application;
the application module is used for applying for hardware resources required by the GIS application instance;
the allocation module is used for allocating hardware resources;
the starting module is used for starting the container;
the deployment module is used for deploying the instance of the GIS application in a mirror image mode;
and the registration module is used for registering the address of the started instance in the intelligent router.
Examples
Referring to fig. 1 to fig. 3, a first embodiment of the present invention is: as shown in fig. 1 and fig. 2, a method and a system for deploying GIS application based on PaaS include the following contents:
in this embodiment, when deploying GIS applications, the deployment is mainly implemented by a central repository, a resource management center, a cloud platform, a development framework, and a remote agent framework. The central warehouse is mainly used for managing GIS application, and comprises site management, application management, developer management, tenant management and the like; the resource management center is mainly used for monitoring software and hardware resources and providing GIS application instance management, server monitoring, log query, application performance analysis and the like; the cloud platform is mainly used for providing software and hardware resources for GIS application, providing dynamic allocation of resources, resource isolation, intelligent routing, fault transfer, log collection and analysis, hardware resource monitoring and the like; the development framework/remote agent framework mainly provides technical support for GIS application, the development framework mainly provides functions of non-invasive programming, multi-protocol release service, parameter verification, automatic registration and pre-release of service, parameter configuration components, log components and the like, and the remote agent framework provides functions of automatic generation of agents, remote communication, local load balancing, safe calling and the like.
Firstly, registering a GIS application; in this embodiment, after the development of the GIS application is completed by the development framework, the GIS application is registered in the central repository, and the GIS application is composed of a plurality of GIS services, and the GIS services mainly include interface and logic implementation.
Identifying a service interface in the GIS application, and issuing the GIS application in a protocol mode; when the GIS application is started, the development framework automatically identifies the service interfaces of the GIS application and releases the services by protocols such as json, amf, avro and the like. And then testing the issued GIS application, mainly performing function test on the GIS application.
The GIS applications belonging to the same cloud platform share software and hardware resources on the cloud platform, so that the GIS applications can be interdependent, the cloud platform is supposed to comprise a first unregistered GIS application and a second registered GIS application, the first GIS application can call an interface jar packet of the second GIS application, when the first GIS application is started for unit test, a remote proxy object is created for the second GIS application interface by a remote proxy framework, when the first GIS application calls the interface of the second GIS application, the remote proxy object accesses the instance of the second GIS application deployed on the cloud platform and sends a return result to the first GIS application, the first GIS application can be locally subjected to unit test without concerning deployment of the second GIS application. The first GIS application passes the unit test and registers in the central repository, and then performs the above-described release and testing.
Creating an example of the GIS application, and applying for hardware resources required by the example of the GIS application; after the verification, the GIS application program is released to the production environment, and then the GIS application is required to be deployed, firstly, an example is created for the GIS application, and hardware resources required by the example of the GIS application, such as CPU core number, memory number, example number and the like, are applied.
Allocating hardware resources for the GIS application example, and starting a specified number of containers; the cloud platform allocates enough hardware resources for the GIS application instances according to a resource scheduling algorithm, and starts a specified number of containers by using a virtualization technology. In this embodiment, the cloud platform allocates resources for the GIS application on the cloud platform by using a drf (dominant Resource farm) algorithm according to the Resource usage on the cloud platform. The DRF algorithm is a max-min fair algorithm for different resource types. Such an algorithm would maximize the minimum allocation received by GIS applications on the cloud platform. Therefore, different GIS applications can be deployed on each server, and server resources are fully utilized. The GIS cloud platform also supports other various resource allocation strategies. For example, a unique allocation policy, each server has and can only deploy one GIS application; the cloud platform can allocate the GIS application to servers with a common attribute value, for example, the GIS application needs special servers as support, and then special tag attributes can be marked for the servers, so that the GIS application can be deployed to the special servers when being deployed; according to the grouping strategy, the cloud platform can distribute the GIS applications to servers of different groups so as to achieve a high availability target, for example, the servers on the same rack are used as a group, so that the GIS cloud platform deploys the GIS applications to different racks respectively, power failure of one rack is guaranteed, and normal operation of the GIS applications cannot be influenced. The cloud platform provides unified scheduling of resources, and can better solve the problems that server resources are in shortage in the liquid level peak period and are wasted at other times. For example, when a business peak comes, resources of the test environment and some of the resources of some non-important business applications can be released and allocated to the key business applications; and releasing the resources from the key business application after the business peak period.
And automatically mirroring and deploying the instance of the GIS application in the container, and then registering the address of the started instance of the GIS application in the intelligent router. In this embodiment, the cloud platform registers the started instance of the GIS application in the intelligent router, and the service user can access the GIS application running on the cloud platform through the intelligent router. The intelligent router distributes the request to correct GIS application examples according to the request URL of the service user, and the intelligent router can implement a load balancing strategy among the GIS application examples according to the strategy designated by the GIS application, wherein the load balancing strategy comprises the following steps: polling policy, iphash policy, cookie policy, and the like.
In this embodiment, the GIS application deployment package is uploaded to the cloud platform, and the cloud platform automatically generates an image file of the GIS application using the image template file, stores the image file in an image repository, and registers the image file in the cloud platform database.
The server can pull the image file of the GIS application from the image warehouse, start the virtual machine by using the image file, and allocate the designated resources. In this embodiment, the virtual machines adopt a container isolation technology, and resources between different virtual machines on the same server are isolated from each other, that is, one of the virtual machines cannot access resources in the other virtual machine, and the normal operation of the other virtual machine is not affected by the crash of the one virtual machine.
And periodically detecting whether the instance of the GIS application runs normally, if not, closing the instance, and deploying a new instance. In this embodiment, the cloud platform periodically detects whether the deployed instances of the GIS application are operating normally by using a probe technology, and allocates resources to the new instances again after the new instances are deployed.
And when the performance load of the GIS application is overlarge, increasing the number of instances of the GIS application. After the new instance is added, the cloud platform allocates new resources to the new instance according to the resource allocation policy.
When the GIS application instance is down, a new instance is created, and the GIS application can be ensured to run continuously with high availability.
When the GIS application is upgraded, a new instance is deployed, and after the new instance is started successfully, the instance before the upgrade is closed. When the GIS application is upgraded, the cloud platform can smoothly upgrade the GIS application without stopping, when the version of the GIS application is switched, the cloud platform deploys new examples for the GIS application of a new version, and when the examples are successfully deployed, the cloud platform can close the application examples of the old version of the GIS application one by one.
And recording and storing a related log of the GIS application. The cloud platform also records and stores mass logs related to the GIS application, the operation framework provides a log component when the GIS application is operated, the operation framework intercepts a service request when a service published on the GIS application is called by the service, a requested RequestId (service request ID) parameter is read, if the RequestId is empty, the operation framework generates the RequestId, and a request calling context is created by using the RequestId.
When the operation frame initializes the request call context by using the container name, the application version number and the application instance name, the request call context is stored in a thread variable to generate a ServiceId (service call ID), a service call context is created by using the ServiceId, then the first service call context in the stack is read out from the stack of the service call context of the service request context, the referreserviceid of the current service call context (ServiceId of the service call calling the current service) is set by using the ServiceId of the service call context, and the context of the current service call is pressed into the stack of the service call context of the service request context
When the operation frame uses the service group, the service method and the service starting time to initialize the current service call context, firstly, the service logic code is called, the first service call request context is popped from the stack of the service call context requesting the service context, and the service ending time of the service call context is set.
In this embodiment, the running framework writes the contents of the service request context and the service invocation context into the system log by using the log component, and the log contents include: log time, container name, application version number, application instance name, belonging system, log level, log type, request id (requestid), current service call id (serviceid), service call id (referreserviceid) calling current service, service group, service method, service start time, service end time, error code and information, etc. Wherein the log type is a performance log, the log component writes the log into a log collector, and then the log collector sends the log to a distributed storage system.
When a client queries the log, the client acquires a log cursor by using the query application real-time log, and then circularly uses the cursor to roll and query the application log. In this embodiment, the format of the cursor is: RSA (< queryTime > | < taskId > | < timeout > | < pageSize > | < logTime > | < logId >) queryTime represents the time to query the real-time application log, accurate to milliseconds; taskId is the container name (task id of marathon) timeout is the cursor timeout, if queryTime + timeout < current time, the cursor is invalid; pageSize indicates the maximum number of logs returned; logTime represents the time of the last log, accurate to milliseconds; logId represents the id of the last log.
When a real-time log interface is inquired and applied, the queryTime and logTime are set as the current server time, and logId is null; when a real-time log interface is applied to rolling query, using queryTime and timeout to judge whether the cursor is overtime, and if the cursor is overtime, returning an overtime error; if logId is empty, inquiring logs larger than or equal to logTime, inquiring the number of the logs to be pageSize, and then executing the step 5; if the logId is not null, inquiring logs larger than or equal to logTime, wherein the number of the inquired logs is 2 × pageSzie; and searching whether the log contains logId, if not, returning the log of the number of previous pageSize bars, and if so, returning the log of the number of pageSize bars after the logId.
If a new cursor is to be generated, the queryTime is set as the current time of the server, logTime is the time of the last log, and logId is the id of the last log.
The request call chain analysis method comprises the following steps: acquiring a RequestId of a service request; inquiring all performance logs of the RequestId, and storing the logs in a Map object by taking the ServiceId as a key; circulating all logs of the Map, and reading the referreserviceId of the logs; if the referrence serviceId is null, the serviceId of the log is stored in a FirstId variable, if the referrence serviceId is not null, the referrence serviceId is used for finding a corresponding call log in a Map object, and then the log is added into the call list serviceIds of the call log object; acquiring a call log object by using the FirstId, traversing the ServiceIds call list depth-first traversal call log, and generating an xml file; and the client analyzes the calling relation of the service displayed by the xml file in a tree form.
In the embodiment, users for research, development, test, operation and maintenance and business can share the GIS application on the cloud platform, so that the remote collaborative development and application are possible; moreover, research, development, test and production are in the same cloud platform environment, the deployment difficulty of the GIS application is reduced, the deployment success rate is improved, the defect of heavy manual deployment is overcome, and the flexible and rapid deployment of the GIS application is realized.
As shown in fig. 3, corresponding to the GIS application deployment method, the present embodiment further relates to a GIS application deployment system based on PaaS, including:
the GIS application creating module 1 is used for creating GIS application examples, wherein one GIS application can create a plurality of examples which can be selected according to requirements;
the application module 2 is used for applying for hardware resources required by GIS application instances, and each instance needs enough resource space;
the distribution module 3 is used for distributing hardware resources, in the embodiment, the cloud platform uniformly schedules and distributes resources required by the GIS application;
the starting module 4 is used for starting the containers, and the number of the started containers is carried out according to the specified number;
the deployment module 5 is used for deploying the GIS application instance in a mirror image mode;
and the registration module 6 is used for registering the address of the started instance in the intelligent router.
In summary, the method and the system for deploying the GIS application based on PaaS provided by the invention have the advantages that the GIS application instance is deployed in the assigned container, the defect of heavy manual deployment is avoided, the deployment efficiency is high, the deployment success rate is high, all GIS applications can be accessed by the service through the intelligent router, and the use is convenient and flexible; the GIS application shares software and hardware resources, so that the resource utilization rate can be improved, and the cost is reduced; a user of research, development, test, operation and maintenance and business can share GIS application on the cloud platform, so that remote collaborative development and application are possible.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all equivalent changes made by using the contents of the present specification and the drawings, or applied directly or indirectly to the related technical fields, are included in the scope of the present invention.
Claims (14)
1. A GIS application deployment method based on PaaS is characterized by comprising the following steps:
creating an example of the GIS application, and applying for hardware resources required by the example of the GIS application;
allocating hardware resources for the GIS application example, and starting a specified number of containers;
automatically mirror-deploying instances of the GIS applications at the container;
and registering the address of the started instance of the GIS application into the intelligent router.
2. The PaaS-based GIS application deployment method according to claim 1, wherein an image file of the GIS application is generated and saved.
3. The PaaS-based GIS application deployment method according to claim 2, wherein an image file of the GIS application is acquired, a virtual machine is started by using the image file, and assigned resources are allocated, and the virtual machine employs a container isolation technology.
4. The PaaS-based GIS application deployment method according to claim 3, wherein whether an instance of the GIS application is running normally is periodically detected, and if not, the instance is closed and a new instance is deployed.
5. The PaaS-based GIS application deployment method according to any of claims 1-4, characterized in that when the performance load of the GIS application is too large, the number of instances of the GIS application is increased.
6. The PaaS-based GIS application deployment method according to any of claims 1-4, characterized in that when an instance of a GIS application goes down, a new instance is created.
7. The PaaS-based GIS application deployment method according to any of claims 1-4, wherein when a GIS application is upgraded, a new instance is deployed, and after the new instance is successfully started, the instance before the upgrade is closed.
8. The PaaS-based GIS application deployment method according to claim 7, wherein a GIS application related log is recorded and saved.
9. The PaaS-based GIS application deployment method of claim 8, further comprising, prior to creating the instance of the GIS application:
registering the GIS application;
identifying a service interface in the GIS application, and issuing the GIS application in a protocol mode;
testing the issued GIS application;
and auditing the GIS application which passes the test, and releasing the GIS application to a production environment.
10. The PaaS-based GIS application deployment method according to claim 8 or 9, wherein all GIS applications belonging to the same cloud platform share software and hardware resources on the cloud platform.
11. The PaaS-based GIS application deployment method of claim 10, wherein the cloud platform comprises an unregistered first GIS application and a registered second GIS application, and wherein the first GIS application can invoke an interface jar package of the second GIS application.
12. The PaaS-based GIS application deployment method of claim 11, wherein when performing a unit test on a first GIS application, a remote proxy object is created for a second GIS application interface, an instance of a second GIS application is accessed through the remote proxy object, and a result is returned to the first GIS application.
13. The PaaS-based GIS application deployment method of claim 12, wherein the first GIS application is registered after the first GIS application passes a unit test.
14. A GIS application deployment system based on PaaS is characterized by comprising:
the creating module is used for creating an example of the GIS application;
the application module is used for applying for hardware resources required by the GIS application instance;
the allocation module is used for allocating hardware resources;
the starting module is used for starting the container;
the deployment module is used for deploying the instance of the GIS application in a mirror image mode;
and the registration module is used for registering the address of the started instance in the intelligent router.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710004696.9A CN106843945B (en) | 2017-01-04 | 2017-01-04 | PaaS-based GIS application deployment method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710004696.9A CN106843945B (en) | 2017-01-04 | 2017-01-04 | PaaS-based GIS application deployment method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106843945A CN106843945A (en) | 2017-06-13 |
| CN106843945B true CN106843945B (en) | 2020-12-01 |
Family
ID=59118606
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710004696.9A Active CN106843945B (en) | 2017-01-04 | 2017-01-04 | PaaS-based GIS application deployment method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106843945B (en) |
Families Citing this family (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107766050B (en) * | 2017-10-31 | 2021-12-07 | 新华三云计算技术有限公司 | Heterogeneous application deployment method and device |
| CN107766569A (en) * | 2017-11-10 | 2018-03-06 | 泰瑞数创科技(北京)有限公司 | GIS management methods and system based on cloud platform |
| CN108319482B (en) * | 2018-02-11 | 2021-07-06 | 北京恒华伟业科技股份有限公司 | JavaWeb module management method and device |
| CN112205015B (en) * | 2018-05-29 | 2023-09-05 | 上海诺基亚贝尔股份有限公司 | Method, apparatus and computer readable medium for policy distribution |
| CN109445802B (en) * | 2018-09-25 | 2022-08-26 | 众安信息技术服务有限公司 | Privatized Paas platform based on container and method for publishing application thereof |
| CN109725920B (en) * | 2018-12-29 | 2022-05-06 | 咪咕文化科技有限公司 | Service instance updating method and device and storage medium |
| CN112084040B (en) * | 2020-09-28 | 2021-07-20 | 上海道客网络科技有限公司 | Container resource planning system and method based on application mirror image data identification |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101803328A (en) * | 2007-09-13 | 2010-08-11 | 空中客车运作股份公司 | The ACARS router that is used for long-range aviation electronics application program |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105867955A (en) * | 2015-09-18 | 2016-08-17 | 乐视云计算有限公司 | Deployment system and deployment method of application program |
| CN105468362B (en) * | 2015-11-17 | 2019-03-08 | 广州杰赛科技股份有限公司 | Using dispositions method and cloud computing system |
| CN106020930B (en) * | 2016-05-13 | 2019-07-23 | 深圳市中润四方信息技术有限公司 | A kind of application management method and system based on application container |
| CN106202429A (en) * | 2016-07-13 | 2016-12-07 | 武大吉奥信息技术有限公司 | GIS cloud service based on mixing container with virtualized host provides method and device |
-
2017
- 2017-01-04 CN CN201710004696.9A patent/CN106843945B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101803328A (en) * | 2007-09-13 | 2010-08-11 | 空中客车运作股份公司 | The ACARS router that is used for long-range aviation electronics application program |
Non-Patent Citations (1)
| Title |
|---|
| "基于开源PaaS技术的互联网业务平台自动部署方案";何震苇等;《电信科学》;20151031(第10期);第2015259-1至2015259-8页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106843945A (en) | 2017-06-13 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106843945B (en) | PaaS-based GIS application deployment method and system | |
| CN110290189B (en) | Container cluster management method, device and system | |
| CN111966305B (en) | Persistent volume allocation method and device, computer equipment and storage medium | |
| CN108845884B (en) | Physical resource allocation method, device, computer equipment and storage medium | |
| US9851989B2 (en) | Methods and apparatus to manage virtual machines | |
| JP6658882B2 (en) | Control device, VNF placement destination selection method and program | |
| CN104503845B (en) | A kind of task distribution method and system | |
| US8099494B2 (en) | Tuning and optimizing distributed systems with declarative models | |
| CN107451147B (en) | Method and device for dynamically switching kafka clusters | |
| US9535754B1 (en) | Dynamic provisioning of computing resources | |
| CN102880503A (en) | Data analysis system and data analysis method | |
| US9542226B2 (en) | Operating programs on a computer cluster | |
| US9959157B1 (en) | Computing instance migration | |
| CN101340368B (en) | Web service distributed management system and method based on WSDM | |
| Di Sanzo et al. | A flexible framework for accurate simulation of cloud in-memory data stores | |
| US20200310828A1 (en) | Method, function manager and arrangement for handling function calls | |
| CN109347661B (en) | Instantiation method and device of consumer VNF | |
| CN109347716B (en) | Instantiation method and device of consumer VNF | |
| CN110971439A (en) | Policy decision method and device, system, storage medium, policy decision unit and cluster | |
| CN114489985A (en) | Data processing method, device and storage medium | |
| CN110119308B (en) | System for managing large-scale container applications | |
| US20220206836A1 (en) | Method and Apparatus for Processing Virtual Machine Migration, Method and Apparatus for Generating Virtual Machine Migration Strategy, Device and Storage Medium | |
| US11656944B1 (en) | Code function checkpoint and restore | |
| CN109150599A (en) | A kind of O&M monitoring system based on cloud framework | |
| CN102790788B (en) | Grid resource management system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |