CN105700877A - Application deployment method and apparatus - Google Patents
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Abstract
The present application provides an application deployment method and apparatus. The method comprises: receiving an application deployment request for a target application, wherein the application deployment request comprises an application configuration file, and the application configuration file contains application deployment information of the target application at a cloud platform; parsing the application configuration file, so as to obtain the application deployment information; and according to the application deployment information, deploying the target application at the cloud platform. The method and apparatus provided by the present application significantly improve efficiency of application deployment.
Description
Technical Field
The present application relates to network technologies, and in particular, to a method and an apparatus for deploying an application.
Background
With the development of cloud computing technology, applications developed by developers can be deployed to a cloud platform, and the cloud platform provides resources such as instances, memories, processors and the like for the running of the applications. For example, a developer may develop a Web application for implementing an instant messaging service and upload the application package to the cloud platform. In the related art, after the application program is uploaded to the cloud platform, deployment personnel still need to perform deployment work of some applications, for example, the deployment personnel may configure an elastic resource scaling strategy for the application on the cloud platform, so that resource occupation of the application is adjusted in time along with changes of application load, and resource utilization rate of the cloud platform is improved. However, this manual configuration of application deployment by deployment personnel makes application deployment inefficient.
Disclosure of Invention
In view of this, the present application provides an application deployment method and apparatus, so as to improve application deployment efficiency.
Specifically, the method is realized through the following technical scheme:
in a first aspect, an application deployment method is provided, including:
receiving an application deployment request for a target application, the application deployment request comprising: the application configuration file comprises application deployment information of the target application on the cloud platform;
analyzing the application configuration file to obtain the application deployment information;
and deploying the target application on a cloud platform according to the application deployment information.
In a second aspect, an application deployment apparatus is provided, including:
a request receiving module, configured to receive an application deployment request for a target application, where the application deployment request includes: the application configuration file comprises application deployment information of the target application on the cloud platform;
the configuration analysis module is used for analyzing the application configuration file to obtain the application deployment information;
and the deployment control module is used for deploying the target application on the cloud platform according to the application deployment information.
According to the application deployment method and device, the cloud platform analyzes the application deployment information according to the application configuration file, and deploys the application according to the application deployment information, so that compared with a manual configuration mode of deployment personnel, the application deployment efficiency is remarkably improved.
Drawings
FIG. 1 is a schematic diagram of a cloud platform shown in an exemplary embodiment of the present application;
FIG. 2 is a flow chart illustrating a method for application deployment in accordance with an exemplary embodiment of the present application;
fig. 3 is a block diagram of an application deployment device according to an exemplary embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The cloud platform can provide services for applications developed by developers, and the developers only need to develop an application program for bearing certain business and upload the application program to the cloud platform. The cloud platform includes various rich resources, such as a processor, a memory, and the like, and the application can be deployed on the cloud platform, and the cloud platform allocates the running resources for the application. Deployment of the application on the cloud platform can include: for example, resources such as a processor and a memory are allocated to an application, and a resource elastic scaling policy of the application is configured, for example, when the application is in a high access amount, the load is large, the resources of the application may be expanded at this time, and when the access amount of the application is low, some application resources may be recycled.
In order to solve the problem of low application deployment efficiency caused by manual configuration of deployment personnel when an application is deployed on a cloud platform in the related art, the embodiment of the application provides an application deployment method, and the deployment of the application can be automatically executed by the cloud platform, so that the application deployment efficiency on the cloud platform is improved. Referring to fig. 1, fig. 1 illustrates a cloud platform, in which an application deployment apparatus 11 for executing the application deployment method of the present application may be disposed, and further includes a platform resource 12 (e.g., a memory, a processor, etc.), and of course, the cloud platform may also include other components, which are not described in detail. In this example, the application deployment device 11 may receive the application deployment request, and request to deploy a certain application on the cloud platform, and then the application deployment device 11 may execute the application deployment method of the present application to implement deployment of the application.
Fig. 2 illustrates a flow of an application deployment method according to an embodiment of the present application, which may include:
in step 201, an application deployment request for a target application is received, where the application deployment request includes: and the application configuration file comprises application deployment information of the target application on the cloud platform.
For example, in this example, an application requested to be deployed on the cloud platform may be referred to as a "target application," and when a developer completes development of the target application, the target application may be uploaded to the cloud platform, and at this time, the cloud platform may be considered to receive an application deployment request for the target application.
The application configuration file included in the application deployment request may mainly include some information required for deploying the target application on the cloud platform, which may be referred to as application deployment information. In this example, the content of the application deployment information is not limited as long as the application deployment-related information is provided. For example, the application deployment information may include resource requirement information of the target application, for example, the required memory size is x1, and the required disk size is x 2; for another example, the application deployment information may further include resource elastic scaling policy information of the target application, for example, when the CPU occupancy rate of the application is higher than 30%, two application instances are added, or when the CPU occupancy rate is lower than 10%, two application instances are decreased. Other examples are not described in detail.
For example, in this step, the application configuration file may be packaged together with the application package and uploaded to the cloud platform. For example, a developer usually knows application scenarios and service characteristics of a target application relatively, and can clearly know what resource elastic scaling strategy the target application needs to set or what resources required by the application, taking a college entrance score query application as an example, as the developer, it can be clear that the access volume of the application is possibly large in months 7 and 8, so that the resource elastic scaling strategy corresponding to the months can be set, and the application resources are expanded when the application load is large. Therefore, the application configuration file may be created by a developer when developing the target application, or may be created by other personnel at an appropriate time, and the application configuration file is uploaded to the cloud platform together with the application package, and optionally, the application configuration file and the application package may also be uploaded separately.
In step 202, the application configuration file is parsed to obtain application deployment information.
In this step, after receiving the application configuration file, the application deployment device of the cloud platform parses the application configuration file to obtain the application deployment information contained therein. For example, taking the application deployment information contained in the application configuration file as the resource flexible scaling policy information of the target application as an example, the content of the resource flexible scaling policy information can be obtained through parsing, for example, when the CPU occupancy rate of the application is higher than 30%, two application instances are added.
In step 203, the target application is deployed on the cloud platform according to the application deployment information.
For example, after obtaining the application deployment information in the application configuration file, the application deployment apparatus may deploy the application on the cloud platform according to the information. For example, if it is known that the target application resource requirement included in the application deployment information in the application configuration file is: the required memory size is x1, and when the disk size to be occupied is x2, resources can be allocated to the target application accordingly, for example, the cloud platform allocates a memory size of x1 and a disk size of x2 to the target application.
According to the application deployment method, the cloud platform analyzes the application deployment information according to the application configuration file, and the application is deployed according to the application deployment information, so that the application deployment efficiency is remarkably improved compared with a manual configuration mode of deployment personnel.
The following takes a resource elastic scaling strategy for deploying a target application to a cloud platform as an example to describe format settings of an application configuration file in the embodiment of the present application: the flexible resource expansion is a way to improve the resource utilization rate of the cloud platform, for example, when a certain high load threshold is reached, the resources of the application can be expanded, including increasing the number of application instances, memory, CPU (central processing unit), disk occupation, and the like; and when a certain low-load threshold value is reached, the resources of the application can be recycled, and the number of application examples, the memory, the CPU, the disk occupation and the like can be reduced. As for the high load threshold, the low load threshold, etc., can be determined according to the service characteristics and the scenario of the application.
In this example, when the application deployment information is resource elastic scaling policy information, for example, the following parameters may be included: the system comprises a flexible measurement parameter, an elastic action threshold value and an elastic action amplitude limit value corresponding to the flexible measurement parameter, strategy time information and the like. The method comprises the following specific steps:
wherein, the expansion measurement parameter is as follows: can be used to decide whether to extend or reclaim the resources of the application according to the parameters. The method can comprise the following steps: file descriptor number, thread/process number, application access request number, network bandwidth usage, processor utilization, memory utilization, and the like. In the application configuration file, which scaling measurement parameters are set can be determined according to the actual situation of the service carried by the application.
For example, when the number of application access requests is larger, or the memory utilization rate is larger, it indicates that the load of the current application is larger, and the resource can be expanded for the application; or when the number of application access requests is smaller, indicating that the application resource can be reclaimed. Therefore, the cloud platform can monitor the states of the parameters in real time according to the telescopic measurement parameters, grasp the resource use condition of the application accordingly, and adjust the allocation of the application resources.
Elastic action threshold corresponding to the stretch metric parameter: the scaling parameter is used as a reference for expanding or recycling the resource, but when the resource is changed, a threshold corresponding to the scaling parameter needs to be set. For example, when the scaling metric parameter is memory utilization, if it is set that an application instance is extended when the memory utilization is higher than 30%, then the 30% is a threshold corresponding to the memory utilization, that is, when the threshold is reached, the extension or the reclamation is performed.
In this example, the aforementioned expansion resource or recovery resource may be referred to as a resilient action, and the aforementioned threshold may be referred to as a resilient action threshold, for example, when a certain resilient action threshold is exceeded, a resilient action may be performed to expand or recover. In a specific implementation, for each scaling parameter, the set elastic action threshold may include an expansion threshold and a recovery threshold, and the resource expansion is performed when the expansion threshold is exceeded, and the resource recovery is performed when the recovery threshold is fallen below.
Elastic action amplitude limit value corresponding to the telescopic measurement parameter: the above-mentioned elastic action threshold value may be used to define under what conditions the elastic action is to be performed, and the elastic action amplitude limit value herein may be used to define the conditions that need to be met when performing the elastic action, such as an upper expansion limit when expanding resources, a lower recovery limit when recovering resources, or a step value for a single expansion or recovery.
Illustratively, when the elasticity is used to expand the number of instances of the application, the upper limit of the expanded instances, i.e., the maximum number of instances, may be set to be 10, and the lower limit of the reduced instances, i.e., the minimum number of instances, may be set to be 2; and it can also be set that only one application instance can be added per expansion, i.e. the step value of a single expansion is 1. The upper limit, the lower limit, the expansion step value, and the like can be set for the elastic operation at the same time.
Policy time information: through the above-mentioned stretch metric parameter, the elastic action threshold value and the amplitude limit value, it can be known that when a certain stretch metric parameter reaches what elastic action threshold value, the elastic action is started to be executed, and the elastic action can be executed according to the amplitude limit value, and the policy time information here can be used for defining when to execute the above-mentioned setting. For example, it is not necessary to perform the elastic action according to the scaling metric parameter on the application profile on any day, and the elastic scaling policy may only need to be performed at some specific time according to the service characteristics of the application.
The policy time information can be set in the form of year, month, day, hour, minute, second, week, etc., and in the application configuration file, the above time information can be represented by specific numerical values, or any time can be represented by a word; the time can also be configured in a time period and a time point mode, for example, 1-2 can represent No. 1 and No. 2. When various types of time configuration items such as year, month, day of week and the like are included in the policy time information, the time configuration items can be divided by separators, such as "use", "divide".
The above-mentioned scaling parameter, the elastic action threshold and the elastic action amplitude limit corresponding to the scaling parameter, and the policy time information are just some lists, and the content included in the application configuration file is not limited to these, and may also include other information.
For the resource elastic scaling policy information listed above, the application configuration file with multiple formats can be implemented, and the format of the application configuration file can be xml, json or yaml.
Taking a Json format configuration file as an example, the configuration of the resource elastic expansion policy information is described as follows: for example, in the application configuration file in the Json format, "file descriptor fd, process thread, request req, processor utilization cpu, and memory occupancy mem" may be set as the scaling metric parameters to determine the execution of the elastic action, and the execution of the elastic action may be determined according to any one of the parameters, for example, the elastic action may be executed when a condition of a certain parameter is satisfied.
For each stretch metric parameter, an elastic action threshold corresponding to the stretch metric parameter is also set. For example, "min _ fd" represents the minimum number of file descriptors, and the value of min _ fd can be set to 20, that is, when the number of file descriptors is lower than 20, the reclamation of the application instance is performed; "max _ fd" represents the maximum number of file descriptors, and the value of max _ fd can be set to 500, i.e., when the number of file descriptors is greater than 500, the expansion of the application instance is performed. Similarly, "min _ thread" may be set to 10, which represents that the application instance is recycled when the number of processes is less than 10, and "max _ thread" may be set to 20, which represents that the application instance is expanded when the number of processes is greater than 20. The required number of elastic action threshold "min _ req" equal to 1000, "max _ req" equal to 5000 can also be set in the same way; setting the CPU elastic action threshold value 'min _ CPU' equal to 10 and 'max _ CPU' equal to 20; the elastic action threshold value of the memory occupancy rate is also set to be 50, and the value of the 'max _ mem' is set to be 80.
In addition, the spring action in this example is an extended instance, and a spring action amplitude limit is also set, for example, "min _ instance" represents a minimum number of instances, and may be set to 2, that is, the minimum number of instances to be reduced cannot be less than 2, "max _ instance" represents a maximum number of instances, and may be set to 4, that is, the maximum number of instances to be extended cannot be more than 4. "step _ instance" represents a step value when an instance is extended or recovered, and for example, if the value of "step _ instance" is set to 1, this indicates that an instance is extended one at a time.
Policy time information can be set in the application configuration file, and the time information can include a plurality of time factors such as year, month, day, hour, minute, and the like. For example, "day" may be set, where "1" indicates that the resource elastic scaling policy is executed at 1 st hour of each month, and the policy may also be executed at 13 th hour of 1 st hour. "year": and "day": mean that the year and date are not limited, but that month is set to execute the strategy in 7-8, i.e., in months 7 and 8 of each year.
In configuring the above-mentioned application configuration file in the Json format, two rules, that is, rule1 and rule2, may be configured, where rule1 indicates that the policy in rule1 is executed at 13 th hour every month on day 1 every year, for example, when the CPU utilization is lower than 10%, the resources of the application are reclaimed. While rule2 indicates that the policy in rule1 is executed at 13 th hour on day 2 of each month every year, the policy is the same, i.e. rule1 and rule2 may be the same except for the time information for executing the policy, and other information such as the stretch metric parameter and its elastic action threshold, elastic action limit, etc.
If the application configuration file is configured in xml format, Yaml format, the content of the configuration file is the same as that of the Json format configuration file in the above example, and may be different only in format.
Using java application of a college entrance examination score query as an example, the application deployment method of the embodiment of the present application is briefly described as follows: the service characteristics and the application scenes of the applications are inquired according to the college entrance examination scores, the application is characterized in that the inquiry amount is very large in 7-8 months per year, and in order to meet the access requirements in the period, developers can distribute the application programs and simultaneously configure the resource elastic expansion strategy information of the applications.
The application deployment information in the application configuration file of the application may include the following: taking the Jason-formatted application configuration file as an example, for example, the application may use cpu and memory mem as the scaling measurement parameter, and use the increase or decrease of the number of instances as the expansion action. And, it also sets up the elastic action threshold value and includes: the cpu threshold is: 10 ~ 30, e.g., "min _ cpu" equals 10, "max _ cpu" equals 30; setting the threshold value of the memory as follows: 50-80, e.g., "min _ mem" equals 50, "max _ mem" equals 80; and the elastic action amplitude limit comprises: the number of the examples ranges from 2 to 10, for example, "min _ instance" is equal to 2, "max _ instance" is equal to 10, that is, the extended examples can not exceed 10 at most, and the reduced examples can not be lower than 2 at least; and the step value is 1, e.g., "step _ instance" equals 1, meaning to increment or decrement one instance at a time. In addition, policy time information may also be set,
the application program package of the college entrance examination score query and the application configuration file can be published together by the developer, and the application program package and the application configuration file can be packaged and uploaded to the cloud platform. After receiving the application configuration file, the application deployment device of the cloud platform may analyze the configuration file to obtain the resource elastic expansion policy information. The cloud platform can deploy the college entrance examination score query application according to the resource elastic expansion strategy information, and set the elastic expansion strategy of the application.
After the configuration of the elastic scaling strategy is completed, the cloud platform can monitor the cpu and the memory of the application in real time according to the strategy in 7 months and 8 months of each year, and determine the number of instances according to the threshold of the cpu and the memory. When the occupancy rate of the cpu is higher than 30%, the instances are expanded one at a time by a stepping value of 1; instances are reduced when the occupancy of the cpu is below 10%, one at a time. The monitoring strategy of the memory is similar to that of the cpu, except that the monitoring threshold is changed from 10-30% to 50-80%.
According to the application deployment method, the cloud platform analyzes the application deployment information according to the application configuration file, and the application is deployed according to the application deployment information, so that the application deployment efficiency is remarkably improved compared with a manual configuration mode of deployment personnel. In addition, different target applications may set different elastic scaling strategies according to their respective characteristics.
Fig. 3 illustrates a structure of an application deployment apparatus, where the apparatus may be applied to a cloud platform, and implementation processes of functions and actions of each module in the apparatus are specifically described in implementation processes of corresponding steps in the foregoing method, and are not described herein again. As shown in fig. 3, the application deployment apparatus may include: a request receiving module 31, a configuration analyzing module 32 and a deployment control module 33; wherein,
a request receiving module 31, configured to receive an application deployment request for a target application, where the application deployment request includes: the application configuration file comprises application deployment information of the target application on the cloud platform;
a configuration analysis module 32, configured to analyze the application configuration file to obtain the application deployment information;
and the deployment control module 33 is configured to deploy the target application on the cloud platform according to the application deployment information.
Further, the application deployment information includes: the resource demand information of the target application on the cloud platform; and the deployment control module 33 is configured to allocate resources to the target application on the cloud platform according to the resource demand information.
Further, the application deployment information includes: resource elastic scaling strategy information of the target application; and the deployment control module 33 is configured to configure an elastic scaling policy for the target application on the cloud platform according to the resource elastic scaling policy information.
Further, the resource elastic scaling policy information includes: the system comprises a telescopic measurement parameter, an elastic action threshold value and an elastic action amplitude limit value corresponding to the telescopic measurement parameter, and strategy time information. For example, the format of the application configuration file includes: xml, json or yaml.
The application deployment device of the example can enable the cloud platform to analyze the application deployment information according to the application configuration file, and deploy the application accordingly, so that the application deployment efficiency is remarkably improved compared with a manual configuration mode of deployment personnel. In addition, different target applications may set different elastic scaling strategies according to their respective characteristics.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the scope of protection of the present application.
Claims (10)
1. An application deployment method, comprising:
receiving an application deployment request for a target application, the application deployment request comprising: the application configuration file comprises application deployment information of the target application on the cloud platform;
analyzing the application configuration file to obtain the application deployment information;
and deploying the target application on a cloud platform according to the application deployment information.
2. The method of claim 1, wherein the application deployment information comprises: the resource demand information of the target application on the cloud platform;
the deploying the target application on the cloud platform according to the application deployment information comprises: and distributing resources for the target application on a cloud platform according to the resource demand information.
3. The method of claim 1, wherein the application deployment information comprises: resource elastic scaling strategy information of the target application;
the deploying the target application on the cloud platform according to the application deployment information comprises: and configuring an elastic expansion strategy for the target application on the cloud platform according to the resource elastic expansion strategy information.
4. The method of claim 3, wherein the resource elastic scaling policy information comprises: the system comprises a telescopic measurement parameter, an elastic action threshold value and an elastic action amplitude limit value corresponding to the telescopic measurement parameter, and strategy time information.
5. The method of claim 1, wherein the format of the application configuration file comprises: xml, json or yaml.
6. An application deployment apparatus, comprising:
a request receiving module, configured to receive an application deployment request for a target application, where the application deployment request includes: the application configuration file comprises application deployment information of the target application on the cloud platform;
the configuration analysis module is used for analyzing the application configuration file to obtain the application deployment information;
and the deployment control module is used for deploying the target application on the cloud platform according to the application deployment information.
7. The apparatus of claim 6, wherein the application deployment information comprises: the resource demand information of the target application on the cloud platform;
and the deployment control module is used for allocating resources for the target application on the cloud platform according to the resource demand information.
8. The apparatus of claim 6, wherein the application deployment information comprises: resource elastic scaling strategy information of the target application;
and the deployment control module is used for configuring an elastic stretching strategy for the target application on the cloud platform according to the resource elastic stretching strategy information.
9. The apparatus of claim 8, wherein the resource elastic scaling policy information comprises: the system comprises a telescopic measurement parameter, an elastic action threshold value and an elastic action amplitude limit value corresponding to the telescopic measurement parameter, and strategy time information.
10. The apparatus of claim 6, wherein the format of the application configuration file comprises: xml, json or yaml.
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| CN112973129B (en) * | 2021-03-12 | 2024-04-05 | 厦门雅基软件有限公司 | Game deployment method, game deployment device, electronic equipment and computer readable storage medium |
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