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最大化 EC2 性能:实例优化实战指南 [重复].pdf

上传人: 明**** 编号:1013650 2025-12-21 25页 434.47KB

1、 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Geoff BlakePrincipal EngineerAnnapurna LabsToby BuckleySr Specialist SA,EC2AWSMaximizing EC2 Perfo

2、rmance:A Hands-on Guide to Instance Optimization CMP333-R 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Topics Performance engineering intro APerf intro Groovy with Aspects Mongo DB instance tuning Call to action 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved

3、.2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Performance engineering introduction 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Performance engineeringFinding opportunity in the system 2025

4、,Amazon Web Services,Inc.or its affiliates.All rights reserved.Challenges of performance engineering-Abstractions leak-Everything has cost-Bottlenecks may hide others-Search space explosion 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Ideal Performance Engineering modelMeasureU

5、nderstandTuneDefine“Performance engineering is never done,you just stop”2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Reality of performance engineeringMeasureUnderstandTuneDefineMeasureMeasureMeasureUnderstandUnderstandUnderstandTuneTune 2025,Amazon Web Services,Inc.or its affi

6、liates.All rights reserved.Reality of performance engineeringstraceUnderstandTuneDefineiostateBPFasprofUnderstandUnderstandUnderstandTuneTune 2025,Amazon Web Services,Inc.or its affiliates.All rights reserved.Wide-then-deep performance debugging-Intuition can be mis-leading-Depth first search is ine

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根据《Maximizing EC2 Performance: A Hands-on Guide to Instance Optimization》的内容,以下是全文关键点的概括: 1. **性能工程概述**:性能工程是一个持续的过程,包括测量、理解和调整,以优化系统性能。 2. **性能工程模型**:理想模型包括测量、理解、调整三个阶段,强调持续优化。 3. **性能调试策略**:采用“广度优先-深度优先”的调试方法,优先考虑机会,避免直观误导。 4. **APerf工具**:APerf是一个用于理解EC2上应用性能的工具,可测量数百个系统级指标,使用简单,开销低。 5. **CPU工作原理**:介绍了CPU的工作流程,包括获取指令、执行数学运算和预测下一步指令。 6. **MongoDB性能分析**:通过ycsb工具分析MongoDB性能,考虑了缓存、内存、存储等成本。 7. **性能优化建议**:强调性能优化需要找到系统中的机会,并从多个信号源和调整候选中进行深入分析。
"EC2性能优化秘籍" "MongoDB调优全攻略" "AWS APerf工具大揭秘"
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