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| Title: | 基於Kubernetes 高可用集群的節點失效容錯研究 以HTTP Web服務為驗證案例
The Study of Nodes Fault Tolerance Based on Kubernetes High-availability Clusters：A Pratical Study on HTTP Web Service |
| Authors: | 羅時雨
Luo, Shih-Yu |
| Contributors: | 張宏慶
Jang, Hung-Chin
羅時雨
Luo, Shih-Yu |
| Keywords: | 容錯
節點失效
容器化平台
高可用集群
網絡流量工作負載
Fault Tolerance
Kubernetes
Web Traffic Workload
Container
Autoscaler |
| Date: | 2022 |
| Issue Date: | 2022-03-01 18:21:32 (UTC+8) |
| Abstract: | 近年微服務架構、容器化技術普及、以Docker容器為標準化單位的
軟體封裝，其快速佈署、彈性調整、跨平台運作特性，能讓業界更專注於創新和業務需求、可輕鬆管理底層基礎設施。隨著物聯網、大數據機器學習盛行，得跨主機平行處理大量資料，故當服務發生不可預期中斷時，得維持系統資源可用性與穩定性。
隨著容器數量增長，Docker公司推出容器的管理平台Docker Swarm管理調度跨主機的容器，依據工作負載去調整其運作規模大小，當容器不可預期停止運作時，Docker Swarm叢集會自動產生新的容器，其確保容器服務高可用性。且在同時Google亦推出Kubernetes，故同時比較以Kubernetes 為基礎的 Horizontal Pod Autoscaler，其會依據節點記憶體目標使用率，自動調整服務Pod個数，提升整體資源利用率。Kubernetes簡化應用程式的管理與佈署，但佈署後其集群內效能未被有效去評估與比較，本研究會針對集群內節點資源配置、參數設定，以Vertical-Pod-Autoscaler、Descheduler、Ingress Controller、Scheduling Framework做優化調整。並再與Docker Swarm 架構比較。驗證叢集中節點發生故障失效，優化整體叢集內Web服務Traffic Workload平均反應時間、最長反應時間、連線數成功率、成功次數、失敗次數 數據結果。
In recent years , the popularization of the Microservice architeure,and Docker containers, its rapid deployment ,flexible adjustment,and cross-platform operation characteristics,enable enterprise to focus on innovation and business needs,and easily manage infrastructure.With the coming of Internet of Things and Data Machine Learning,a large amount of data be processed across hosts.Thus,When system’service is suddenly interrupted, the availability of resources can be sustained steadily.The Horizontal Pod Autoscaler based on Kubernetes automatically adjust the number of Pods according to the target memory utilization
of the node , improving the overall resource utilization. Apparently,Kubernetes simplify the management and deployment of pod, but its performance has not been effectively evaluated. The study will focus on the node resource configuration and parameter settings in cluster.Vertical-Pod-Autoscaler, Scheduling Framework, Descheuler, and Ingress Controller makes optimization adjustments.At the same time,compared with the Docker Swarm cluster, When the node fails, the research is implemented to optimize the Web service of the average response time , the longest response time,and the success rate of the number of connection. |
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| Description: | 碩士
國立政治大學
資訊科學系碩士在職專班
107971018 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0107971018 |
| Data Type: | thesis |
| DOI: | 10.6814/NCCU202200253 |
| Appears in Collections: | [資訊科學系碩士在職專班] 學位論文
|
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