Realization method of elastic scheduling of virtual resources combined with monitoring data of application performance indicators

A technology for monitoring data and application performance, applied in the information field, can solve problems such as waste of server hardware resources, complicated server hardware expansion, and inconvenient server expansion, and achieve the effects of convenient operation and maintenance, reduced workload, and labor cost savings

Active Publication Date: 2018-06-08
SICHUAN ZHONGDIAN AOSTAR INFORMATION TECHNOLOGIES CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] 1. Waste of hardware: an information system may need several servers at the peak of user access, but when the user access is at a low point, the server's cpu, memory and other resources are idle, which leads to server hardware waste of resources
[0008] 2. It is inconvenient to expand the server capacity: the general information system will make a certain plan for the server resources before the implementation, but with the promotion of the information system, when there are more and more visiting users, the expansion of the server hardware is relatively complicated, if the plan is not clear, there will be lead to greater waste of hardware resources
[0009] 3. The inability to flexibly calculate user access will lead to downtime risks: the number of user visits is not static. If the number of user visits to an information system increases due to some unexpected events, there is a certain degree of system downtime due to insufficient hardware resources. The risk of machine failure, although planning and disaster recovery have been basically done during the implementation of the project, this situation is still unavoidable under the current conditions

Method used

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  • Realization method of elastic scheduling of virtual resources combined with monitoring data of application performance indicators
  • Realization method of elastic scheduling of virtual resources combined with monitoring data of application performance indicators
  • Realization method of elastic scheduling of virtual resources combined with monitoring data of application performance indicators

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Embodiment 1

[0075] The present invention is mainly based on the combination of cloud computing technology and its theory with the IMS (Integrated Information Operation and Maintenance Supervision System) system, and realizes the functions of real-time monitoring and flexible expansion scheduling of the information system.

[0076] Elastic expansion: The concept of elastic expansion was first proposed by Amazon in the United States. In the present invention, it is mainly aimed at a dynamic expansion of the hardware of the business application itself (mainly referring to virtual machines, disk space, etc. in this invention). During the operation of business applications, the number of virtual machine instances supporting business applications can be dynamically increased or decreased. The business system can automatically start more instances when the load is high, and automatically stop some instances when the load is low. Elastic expansion realizes the real on-demand allocation of resourc...

Embodiment 2

[0100] This embodiment is further optimized on the basis of the foregoing embodiments. Further, in order to better realize the present invention, said step 2-3-1) includes the following specific steps:

[0101] 2-3-1-1) Query the number of running virtual machines configured by the rule;

[0102] 2-3-1-2) Query the virtual machines in the elastic pool in ascending order of startup and shutdown;

[0103] 2-3-1-3) virtual machines are classified into a stop list and a run list;

[0104] 2-3-1-4) Compare the actual number of planned runs with the number of planned runs configured by the rule. When the number of running virtual machines configured by the rule is less than the actual number of running virtual machines, take out the difference between the actual number and the rule configuration in reverse order from the running list. The number of virtual machines obtained by the difference between them will be placed in the list to be stopped; when the number of running virtual m...

Embodiment 3

[0107] This embodiment is further optimized on the basis of any of the above embodiments. Further, in order to better realize the present invention, the step 2-3-2) includes the following specific steps:

[0108] 2-3-2-1) Query the number of running virtual machines configured by the rule;

[0109] 2-3-2-2) Query the virtual machines in the elastic pool;

[0110]2-3-2-3) Classify the virtual machine into a stop list and a run list;

[0111] 2-3-2-4) Compare the actual number of planned runs with the number of planned runs configured by the rule. When the number of running virtual machines configured by the rule is less than the actual number of running virtual machines, take out the difference between the actual number and the rule configuration in reverse order from the running list. When selecting a virtual machine, select the virtual machine in the data center first and put it in the list to be stopped; when the number of virtual machines configured by the rule is the same...

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Abstract

The invention discloses a virtual resource elastic scheduling implementation method combined with application performance index monitoring data, including the following steps: 1) scheduling according to time and / or scheduling according to business system indicators needs to configure elastic pool scheduling rules; 2) based on elastic pool scheduling rules Scheduling; 2-1) Declaring the virtual machine queue to be started and stopping the queue; 2-2) Querying the available elastic pool; 2-3) Cycle processing; 2-4) Judging the scheduling rule, when it is a time-based scheduling rule, Execute 2‑4‑1) time scheduling submethod; when scheduling rules for business system indicators, execute 2‑4‑2) business system index scheduling submethod; 2‑5) start all virtual machines in the queue to be started; 2‑ 6) Stop all the virtual machines in the queue to be stopped; 2‑7) End of scheduling, solve the disadvantages of hardware resource waste in the existing technology, adopt flexible scheduling rules, reduce the waste of hardware resources by the business system, and effectively reduce costs .

Description

technical field [0001] The invention relates to the field of information technology, specifically, a virtual resource flexible scheduling implementation method combined with application performance index monitoring data. Background technique [0002] Cloud resource management system: The cloud resource management system can centrally manage computing resources, storage resources, and network resources in cloud computing resource pools in multiple provinces and cities. The management platform adopts a first-level deployment, and resource operation and scheduling are all carried out locally in the resource pools of provinces and cities. The overall deployment architecture of the cloud resource management system is as follows: figure 1 The resource management platform and the resource pool of the provincial company are set as shown. The database server of the resource management platform and the application server of the resource management platform are set in the resource mana...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L12/24H04L12/861H04L29/08
Inventor 黄荣辉朱海萍贺斌周永静杨洋余痴牟俊王绘宇赵海峰
Owner SICHUAN ZHONGDIAN AOSTAR INFORMATION TECHNOLOGIES CO LTD
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