Cloud server performance data collection method and device based on python

Abstract

The invention discloses a cloud server performance data collection method and device based on python. According to the sustainably integrated full-automation performance data collection of the cloud server of each node of a cloud provider, the improvement of the performance stability of the cloud service is tested, and performance data at certain time can be automatically obtained and generated; and the visual manifestation of a test result can improve readability, and the execution iteration efficiency of test data in the future is improved. During node testing, a full-automation form and sustainable integration can be implemented, direct manual intervention is not needed, and after data is collected, the collected data is sent to an appointed person and stored locally to serve as the iteration of next data collection. The performance data collection time of cloud service is shortened. The execution iteration efficiency of test data in the future is improved, and the performance indexof the server does not need to be obtained by manual interference in special time periods, such as at night, on weekends and the like.

Description

technical field [0001] The present disclosure relates to the field of data collection, in particular to a python-based cloud server performance data collection method and device. Background technique [0002] At present, the cloud service market occupies an important position in the Internet field, and its hosts are deployed in many regions, and the current trend is still expanding. During the period when a new node goes online, we need to test the node, check the performance indicators of the node, collect the performance data of the stable operation of the cloud host, and do the impact of future node maintenance and function addition on the host performance. The performance metrics data collected, these tests are undoubtedly boring. [0003] At present, there are generally two types of cloud service node tests. The first type is to manually test repetitive work, enter the test host cpu, memory, disk I / O, bandwidth, etc., execute the command and view the results, and summa...

AI Technical Summary

Problems solved by technology

The problems of the first solution are that the repetitive work of manual testing is boring, unnecessary time is wasted, and the number of test items is too large, the time required for testing is longer, and it is difficult to meet the requirements for testing at special time points, such as early morning at night, During the weekend break; the problem with the second solution is that the shell automatically runs the script and automatically obtains the result data. You can only manually look at each step of the operation. Although it frees your hands, it cannot realize data visualization and full automation.

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