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Ceph distributed storage monitoring and tuning management method for big data platform

A distributed storage and big data platform technology, which is applied in the field of Ceph distributed storage monitoring and tuning management, can solve the problems of high technical threshold, difficult statistics and analysis data, high operation and maintenance costs, etc., so as to improve the efficiency of operation and maintenance management and unify Operation and maintenance management, the effect of lowering the technical threshold

Inactive Publication Date: 2019-02-01
北京京航计算通讯研究所
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The operation and maintenance of the Ceph cluster after deployment is a major difficulty in its promotion and application, because its management and maintenance need to be realized through a large number of complex command lines. Time-consuming special training can be mastered, the technical threshold is high, and the operation and maintenance cost is high
At the same time, the cluster running status monitoring command officially provided by Ceph will generate a large amount of status data, and technicians in the professional field need to spend a lot of time reading to analyze the running status of the cluster, lacking intuitive status information display, and lack of historical data. It is difficult to form statistical analysis data, and it is even more difficult to integrate with the existing big data platform of the user unit, and it is impossible to realize unified monitoring and management of the business
[0003] The above two aspects have restricted the promotion and application of the Ceph distributed storage system in the production environment

Method used

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  • Ceph distributed storage monitoring and tuning management method for big data platform
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  • Ceph distributed storage monitoring and tuning management method for big data platform

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0065] Example of Monitoring and Alarming

[0066] Such as figure 2 As shown, this embodiment proposes the monitoring and alarming workflow of the Ceph distributed storage monitoring and tuning management system of the present invention:

[0067] Step 1: Select monitoring and management nodes for system deployment. The deployed system will be able to capture Ceph cluster operating data and status information;

[0068] Step 2: The configuration information and status information of the cluster are stored in the operation monitoring management database;

[0069] Step 3: The monitoring and management module calculates and analyzes the data in the database to obtain the running status of the Ceph cluster, and provides it to the unified data mining module and data display module in the big data platform to provide users with unified data analysis and High-quality data display;

[0070] Step 4: The status alarm module is responsible for further matching calculation on the data ...

Embodiment 2

[0073] Example of Performance Tuning

[0074] Such as image 3 As shown, the present embodiment proposes the performance tuning workflow of the Ceph distributed storage monitoring and tuning management system for the present invention:

[0075] Step 1: Select monitoring and management nodes for system deployment. The deployed system will be able to capture Ceph cluster operating data and status information;

[0076] Step 2: The configuration information and status information of the cluster are stored in the monitoring management database; the monitoring management module calculates and analyzes the data in the database to generate operation monitoring management data;

[0077] Step 3: The performance tuning module calculates and analyzes the operation monitoring and management data comprehensively, obtains the optimal configuration scheme of the current cluster on specific parameters such as the number of PGs, generates an tuning template, and submits it to the configuratio...

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Abstract

The invention belongs to the field of cloud storage technology, in particular to a Ceph distributed storage monitoring and tuning management method oriented to a large data platform, which focuses onsolving the problems of complex monitoring and management operation of the Ceph distributed storage system and difficult mining of decision data resources. The method is implemented based on a monitoring and tuning management system. The system comprises a running monitoring management database, a monitoring management module, a status alarm module, an alarm status rule preset module, a performance tuning module and a configuration management module. The invention can realize the high efficiency, low cost and unified operation and maintenance management of the Ceph distributed storage system,remarkably improve the operation and maintenance management efficiency of the system, effectively reduce the technical threshold of the deployment and application of the Ceph distributed storage system in the production environment, and is favorable for the large-scale popularization and application of the system.

Description

technical field [0001] The invention belongs to the technical field of cloud storage, and specifically relates to a Ceph distributed storage monitoring and tuning management method for a big data platform, which focuses on solving the problems of complicated monitoring and management operations of the Ceph distributed storage system and difficult mining of decision-making data resources. Background technique [0002] Ceph is a widely used distributed storage system, which has the characteristics of high scalability, high reliability, high performance, and multiple copies. The operation and maintenance of the Ceph cluster after deployment is a major difficulty in its promotion and application, because its management and maintenance need to be realized through a large number of complex command lines. Time-consuming specialized training can be mastered, the technical threshold is high, and the operation and maintenance costs are high. At the same time, the cluster running stat...

Claims

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Application Information

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IPC IPC(8): G06F9/50H04L12/24H04L12/26H04L29/08
CPCG06F9/5083H04L41/06H04L41/0823H04L41/0893H04L43/16H04L67/1097
Inventor 张彤李姝张永静郑春一李世成周羽朱盼盼高晓琼左晓辉司敬
Owner 北京京航计算通讯研究所
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