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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/61593

    Title: 雲端服務下自動化部署及監控系統之管理架構;Automatic Monitoring and Deployment of Cloud Services
    Authors: 陸俊廷;Lu,Chun-Ting
    Contributors: 資訊工程學系
    Keywords: 雲端服務;Hadoop;自動化部署;監控;Puppet;cloud services;Hadoop;automatic deployment;monitoring;Puppet
    Date: 2013-08-27
    Issue Date: 2013-10-08 15:23:13 (UTC+8)
    Publisher: 國立中央大學
    Abstract: Hadoop為常見Platform as a Service中常見的雲端工具,並為終端使用者提供運算平台。在大部分情況下,安裝Hadoop集群需要在大量的計算主機安裝不同的軟體資源。傳統的軟體安裝方式,管理者需要在不同的主機下重覆相同的安裝步驟,對於管理者而言是相當沒效率及花費時間的。除此之外,分散於這些主機上的不同軟體其更新的需求也不盡相同。近幾年來,許多部署的工具即為解決此類問題而推出,其一名為Puppet,其不但可解決軟體部署問題同時亦可應用在Hadoop的安裝上。它使用了伺服器驅動的方式部署軟體在不同的計算主機上,換句話說,Puppet主機定期接收到客戶端的部署報告並從其中資訊判斷是否有軟體資源需要更新。儘管其解決了關於軟體部署的複雜性及問題,但仍面臨到關於擴充性的問題,當客戶端規模龐大時,大量的訊息回傳,伺服器的處理效率將會成為服務效率中的瓶頸。為了解決此項問題,我們提出了一自動化的部署工具,它基於Puppet部署Hadoop集群並採取了客戶端驅動的方式避免了上述問題。在部署過程中,我們提出的部署工具首先在伺服器端發送不同的部署條件,接著客戶端定期從伺服器端接收到的訊息判斷何種軟體需要安裝或軟體是否需要更新。當此部署工具與一般部署工具針對在Hadoop的安裝上比較,我們可以發現在大規模的集群下使用此部署工具效率較為優秀,其部署彈性也是較其他工具優秀。
    Hadoop is a common cloud tool to build a cloud platform that can be accessed by end-users. In most cases, installation of a Hadoop platform requires installation of different software packages on tens to thousands of computing machines. With a traditional software deployment strategy, the administrators need to repeat similar installation procedures on different computing machines, which is inefficient and time-consuming. In addition, different software components that are distributed among the computing hosts may need to be upgraded. Recently, a popular software deployment tool called Puppet is developed to solve the problem of software deployment, and can apply to Hadoop installation. It uses a server-driven model to install and update various software packages on many computing machines. That is, the Puppet deployment server periodically receives reports from the deployment clients (targets), and computes what software packages are required by what deployment clients. Although it simplifies the problem of software deployment, it still suffers the scalability problem --- the server becomes an obvious performance bottleneck when the number of deployment clients is large. To overcome the problem, we have developed an automatic, client-driven deployment tool for Hadoop based on Puppet. At first, the proposed deployment tool dispatch different installation rules from the deployment server to the client (target) machines. Then, the client periodically checks the server for what versions of software packages are required, and installs software packages if necessary. When compared with similar deployment tools for Hadoop, the proposed deployment tool works better when the number of deployment clients is relatively large.
    Appears in Collections:[資訊工程研究所] 博碩士論文

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