CN115037615A - Self-adaptive application capacity expansion method based on cloud platform - Google Patents
Self-adaptive application capacity expansion method based on cloud platform Download PDFInfo
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- 230000008602 contraction Effects 0.000 claims abstract description 8
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- 230000003044 adaptive effect Effects 0.000 claims description 11
- 238000012423 maintenance Methods 0.000 abstract description 7
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- H—ELECTRICITY
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0803—Configuration setting
- H04L41/0813—Configuration setting characterised by the conditions triggering a change of settings
- H04L41/0816—Configuration setting characterised by the conditions triggering a change of settings the condition being an adaptation, e.g. in response to network events
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
- H04L43/0817—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability by checking functioning
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L63/00—Network architectures or network communication protocols for network security
- H04L63/08—Network architectures or network communication protocols for network security for authentication of entities
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Abstract
The invention discloses a self-adaptive application capacity expansion method based on a cloud platform, which comprises the following steps: the target application receives a service request; monitoring a first application index of a target application in the ACK cluster to judge whether the first application index meets the expansion and contraction capacity condition; and performing application copy expansion or contraction on the target application when the expansion and contraction conditions are met. The self-adaptive application capacity expansion method based on the cloud platform can automatically sense the state of the target application, automatically expand and contract the service through the application index, does not need human intervention, and does not need operation and maintenance personnel to worry about the problems of insufficient resources and resource waste. And the application is not required to be modified, the operation and maintenance cost is reduced, and the flexibility is improved.
Description
Technical Field
The invention relates to the technical field of application capacity expansion, in particular to a self-adaptive application capacity expansion method based on a cloud platform.
Background
With the development of the cloud market, at present, more and more services are migrated from the IDC machine room to the cloud, and how to handle more requests at the lowest cost becomes an urgent need for development and operation and maintenance personnel. For example, some large activities need to be guaranteed, the previous method is to prepare a large number of servers to start up and deploy services before the activities, wait for tasks to be processed, and prepare machines, which takes a lot of time for operation and maintenance personnel and causes high cost.
Disclosure of Invention
The invention provides a self-adaptive application capacity expansion method based on a cloud platform, which solves the technical problems and specifically adopts the following technical scheme:
a self-adaptive application expansion method based on a cloud platform comprises the following steps:
the target application receives a service request;
monitoring a first application index of a target application in the ACK cluster to judge whether the first application index meets the expansion and contraction capacity condition;
and performing application copy expansion or capacity reduction on the target application when the capacity expansion condition is met.
Further, if the first application index is greater than or equal to a preset capacity value, whether the number of application copies of the target application in the ACK cluster is smaller than a maximum preset number is judged;
if the number of the application copies of the target application in the ACK cluster is smaller than the maximum preset number, carrying out application copy capacity expansion on the target application in the ACK cluster;
and if the number of the application copies of the target application in the ACK cluster is equal to the maximum preset number, carrying out application copy capacity expansion on the target application in the SAE cluster.
Further, if the first application index is less than or equal to a preset capacity reduction value, judging whether the number of application copies of the target application in the ACK cluster is equal to a first minimum preset number;
if the number of the application copies of the target application in the ACK cluster is equal to the minimum preset number, no adjustment is made;
and if the number of the application copies of the target application in the ACK cluster is larger than the minimum preset number, performing application copy capacity reduction on the target application in the ACK cluster.
Further, if the first application index is smaller than the preset expansion value but greater than or equal to the prepared expansion value for the preset time, the application copy expansion is also performed on the target application, and the prepared expansion value is smaller than the preset expansion value.
Further, if the number of application copies of the target application in the ACK cluster is equal to the maximum preset number, authenticating the target application;
and if the target application has SAE capacity expansion permission, carrying out application copy capacity expansion on the target application in the SAE cluster.
Further, monitoring a second application index of the target application in the SAE cluster to judge whether the second application index meets the expansion and contraction capacity condition;
and if the second application index is larger than or equal to the preset capacity expansion value, carrying out application copy capacity expansion on the target application in the SAE cluster.
Further, if the second application index is less than or equal to the preset capacity reduction value, whether the number of the application copies of the target application in the SAE cluster is greater than a second minimum preset number is judged;
if the number of the application copies of the target application in the SAE cluster is larger than a second minimum preset number, performing application copy capacity reduction on the target application in the SAE cluster;
and if the number of the application copies of the target application in the SAE cluster is equal to the second minimum preset number, performing application copy capacity reduction on the target application in the ACK cluster.
Further, if the second application index is smaller than the preset expansion value but greater than or equal to the prepared expansion value for the preset time, the application copy expansion is also performed on the target application, and the prepared expansion value is smaller than the preset expansion value.
Further, the ratio of the preliminary expansion value to the preset expansion value is in a range of 1 or less and 0.9 or more.
Further, the first application index and/or the second application index is one of a CPU usage rate, a memory usage rate, and a custom index.
The self-adaptive application capacity expansion method based on the cloud platform has the advantages that the state of the target application can be automatically sensed, the service can be automatically expanded and contracted through the application indexes, manual intervention is not needed, and operation and maintenance personnel do not need to worry about insufficient resources and resource waste.
The self-adaptive application capacity expansion method based on the cloud platform has the advantages that any modification on the application is not needed, the operation and maintenance cost is reduced, and the flexibility is improved.
The self-adaptive application capacity expansion method based on the cloud platform has the advantages of short capacity expansion time, large capacity expansion capacity and low production cost.
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Fig. 1 is a schematic diagram of an adaptive application expansion method based on a cloud platform according to the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and the embodiments.
As shown in fig. 1, a cloud platform-based adaptive application extension method includes the following steps:
s1: the target application receives the service request.
S2: and monitoring a first application index of the target application in the ACK cluster to judge whether the first application index meets the expansion and contraction capacity condition.
S3: and performing application copy expansion or capacity reduction on the target application when the capacity expansion condition is met.
The self-adaptive application capacity expansion method based on the cloud platform can automatically sense the application state, automatically expand and contract the service through the application indexes, does not need human intervention, and operation and maintenance personnel do not need to worry about the problems of insufficient resources and resource waste. The following specifically describes specific steps of performing application copy expansion or reduction on the target application when the expansion and reduction conditions are met.
Specifically, if the first application index is greater than or equal to the preset tolerance value, it is determined whether the number of application copies of the target application in the ACK cluster is less than the maximum preset number. And if the number of the application copies of the target application in the ACK cluster is smaller than the maximum preset number, carrying out application copy capacity expansion on the target application in the ACK cluster. And if the number of the application copies of the target application in the ACK cluster is equal to the maximum preset number, carrying out application copy capacity expansion on the target application in the SAE cluster. And monitoring a second application index of the target application in the SAE cluster to judge whether the second application index meets the capacity expansion and reduction condition, and if the second application index is greater than or equal to a preset capacity expansion value, performing application copy capacity expansion on the target application in the SAE cluster. In the present application, the preset tolerance value is 80%. It is understood that the first application indicator and the second application indicator may be one of a CPU usage rate, a memory usage rate, and a custom indicator. In the present application, the first application index and the second application index are both CPU utilization rates.
For example, assume that the CPU utilization of the application copy of the target application of the original ACK cluster is:
copy 1CPU utilization: 50 percent of
Copy 2CPU utilization: 50 percent of
Copy 3CPU usage: 50 percent of
The average utilization rate of the three copies is 50 percent
When the application receives a large number of requests, the three-copy CPU changes to:
copy 1CPU utilization: 80 percent of
Copy 2CPU utilization: 90 percent
Copy 3CPU usage: 80 percent of
The average utilization rate of the three copies is 83.3 percent
At this time, if the average utilization rate of the three copies is greater than 80% of the preset capacity expansion value, one copy is expanded.
Preferably, if the number of the application copies of the target application in the ACK cluster is equal to the maximum preset number, the target application is authenticated first, and if the target application has an SAE capacity expansion permission, the application copy capacity expansion is performed on the target application in the SAE cluster.
Further, if the first application index is less than or equal to the preset capacity reduction value, whether the number of application copies of the target application in the ACK cluster is equal to a first minimum preset number is judged. If the number of application copies of the target application in the ACK cluster is equal to the minimum preset number, no adjustment is made. And if the number of the application copies of the target application in the ACK cluster is larger than the minimum preset number, performing application copy capacity reduction on the target application in the ACK cluster. In the present application, the predetermined shrinkage value is 40%, and the first minimum predetermined number is 1.
As a preferred embodiment, if the first application indicator is less than the preset expansion value but greater than or equal to the prepared expansion value for the preset time, the application copy expansion is also performed on the target application, and the prepared expansion value is less than the preset expansion value.
It will be appreciated that in some instances the first application level does not reach 80%, but is close to 80% for a long time. In this case, the capacity can be expanded, and the processing efficiency of the application can be improved. The ratio of the preliminary expansion value to the preset expansion value is less than or equal to 1 and greater than or equal to 0.9. In the present application, the preliminary capacity value is set to 75%.
As a preferred embodiment, if the second application indicator is less than or equal to the preset scaling value, it is determined whether the number of application copies of the target application in the SAE cluster is greater than a second minimum preset number. And if the number of the application copies of the target application in the SAE cluster is larger than the second minimum preset number, performing application copy capacity reduction on the target application in the SAE cluster. And if the number of the application copies of the target application in the SAE cluster is equal to the second minimum preset number, performing application copy capacity reduction on the target application in the ACK cluster. In the present application, the second minimum preset number is set to 1.
Similarly, if the second application index is smaller than the preset expansion value but greater than or equal to the prepared expansion value for the preset time, the application copy expansion is also performed on the target application, and the prepared expansion value is smaller than the preset expansion value.
It will be appreciated that in some instances the second utility criterion has not reached 80%, but has been approaching 80% for a long time. In this case, the capacity can be expanded, and the processing efficiency of the application can be improved. The preliminary capacitance value setting method is described above.
When an application receives a request, if the current application cannot process so many requests, an HPA program in a cluster monitors a program resource index through Prometheus, when the index reaches a capacity expansion threshold value, the current copy is expanded in an ACK cluster, if the maximum copy allowed by the capacity expansion is still unable to process the request, the HPA program is linked with an SAE cluster, a cluster interface is called, the number of copies with the same service in the SAE cluster is expanded after authentication, SAE has no resource limitation, large-scale capacity expansion can be carried out, and after the request processing is completed, the copies in SAE and ACK are sequentially reduced. The cluster automatically senses the application state, improves the service stability and reduces the cloud resource cost. Specifically, accessing one application is front-end load balancing SLB through DNS domain name resolution to SAE and ACK. When the business application receives the request, the HPA program in the ACK cluster monitors the application index in Prometous constantly, and judges whether the current application needs capacity expansion according to the capacity expansion index. And if the index reaches the expansion threshold value, expanding the application copy in the current ACK cluster. If the application copies are expanded, the expansion indexes are recovered to be normal, and the expansion is not carried out any more, so that the number of the current application copies is maintained. And if the service requests are reduced, carrying out capacity reduction on the service services in the current ACK cluster. If the application copy is expanded, when the expansion index is still higher than the expansion threshold and the current cluster copy is expanded to the maximum copy allowing expansion, the SAE service interface is called to continue expansion until the expanded copy can support the current application processing. After the application process is finished, the service index changes, firstly the HPA in SAE reduces the copy according to the index, and secondly the HPA in ACK reduces the copy according to the index.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It should be understood by those skilled in the art that the above embodiments do not limit the present invention in any way, and all technical solutions obtained by using equivalent alternatives or equivalent variations fall within the scope of the present invention.
Claims (10)
1. A self-adaptive application expansion method based on a cloud platform is characterized by comprising the following steps:
the target application receives a service request;
monitoring a first application index of a target application in the ACK cluster to judge whether the first application index meets the expansion and contraction capacity condition;
and performing application copy expansion or capacity reduction on the target application when the capacity expansion condition is met.
2. The cloud platform-based adaptive application capacity expansion method according to claim 1,
if the first application index is larger than or equal to the preset expansion value, judging whether the number of application copies of the target application in the ACK cluster is smaller than the maximum preset number or not;
if the number of the application copies of the target application in the ACK cluster is smaller than the maximum preset number, carrying out application copy capacity expansion on the target application in the ACK cluster;
and if the number of the application copies of the target application in the ACK cluster is equal to the maximum preset number, carrying out application copy capacity expansion on the target application in the SAE cluster.
3. The cloud platform-based adaptive application expansion method according to claim 2,
if the first application index is smaller than or equal to the preset capacity reduction value, judging whether the number of application copies of the target application in the ACK cluster is equal to a first minimum preset number or not;
if the number of the application copies of the target application in the ACK cluster is equal to the minimum preset number, no adjustment is made;
and if the number of the application copies of the target application in the ACK cluster is larger than the minimum preset number, performing application copy capacity reduction on the target application in the ACK cluster.
4. The cloud platform-based adaptive application capacity expansion method according to claim 2,
if the first application index is smaller than the preset expansion value but is greater than or equal to the prepared expansion value for the preset time, the application copy expansion is also carried out on the target application, and the prepared expansion value is smaller than the preset expansion value.
5. The cloud platform-based adaptive application capacity expansion method according to claim 2,
if the number of the application copies of the target application in the ACK cluster is equal to the maximum preset number, authenticating the target application;
and if the target application has SAE capacity expansion permission, performing application copy capacity expansion on the target application in the SAE cluster.
6. The cloud platform-based adaptive application capacity expansion method according to claim 2,
monitoring a second application index of the target application in the SAE cluster to judge whether the second application index meets the expansion and contraction capacity condition;
and if the second application index is larger than or equal to the preset capacity expansion value, carrying out application copy capacity expansion on the target application in the SAE cluster.
7. The cloud platform-based adaptive application capacity expansion method according to claim 6,
if the second application index is less than or equal to the preset capacity reduction value, judging whether the number of the application copies of the target application in the SAE cluster is greater than a second minimum preset number;
if the number of the application copies of the target application in the SAE cluster is larger than a second minimum preset number, performing application copy capacity reduction on the target application in the SAE cluster;
and if the number of the application copies of the target application in the SAE cluster is equal to the second minimum preset number, performing application copy capacity reduction on the target application in the ACK cluster.
8. The cloud platform-based adaptive application capacity expansion method according to claim 7,
and if the second application index is smaller than the preset expansion value but is greater than or equal to the prepared expansion value for the preset time, performing application copy expansion on the target application, wherein the prepared expansion value is smaller than the preset expansion value.
9. The cloud platform-based adaptive application capacity expansion method according to any one of claims 4 or 8,
the ratio of the preliminary expansion value to the preset expansion value is less than or equal to 1 and greater than or equal to 0.9.
10. The cloud platform-based adaptive application expansion method according to any one of claims 1 to 8,
the first application index and/or the second application index is one of a CPU utilization rate, a memory utilization rate and a user-defined index.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109446032A (en) * | 2018-12-19 | 2019-03-08 | 福建新大陆软件工程有限公司 | The method and system of the scalable appearance of Kubernetes copy |
| CN113395178A (en) * | 2021-06-11 | 2021-09-14 | 聚好看科技股份有限公司 | Method and device for elastic expansion and contraction of container cloud |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109446032A (en) * | 2018-12-19 | 2019-03-08 | 福建新大陆软件工程有限公司 | The method and system of the scalable appearance of Kubernetes copy |
| CN113395178A (en) * | 2021-06-11 | 2021-09-14 | 聚好看科技股份有限公司 | Method and device for elastic expansion and contraction of container cloud |
Non-Patent Citations (1)
| Title |
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| 阿里云云原生: "比心云平台基于阿里云容器服务 ACK 的弹性架构实践", 《CSDN》, pages 1 - 12 * |
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