1、,传统网络数据分析的智能化升级 Intelligent Upgrading of Traditional Network Traffic Analysis,AIOps在企业数据中心的探索Exploration of AIPOS in Enterprise Data Center,AIOps三阶段,Algorithmic IT Operations,Artificial Intelligence for IT Operations,Autonomous IT Operations,AIOps第一驱动力,第二驱动力：IT架构,Monolithic Architecture,Traditional
2、SOA,Microservices,自动化分析 - 主动、高效性能管理解决方案,业务运行态势感知，可视,基线分析,趋势预测,RCA分析,主动业务梳理,业务关联分析,全路径分析,多参数组合阈值警报,多段智能警报 定制报表,面向业务性能的时序数据库 - CSPMDB 应用协议解析，应用层交易日志 130多种网络层到应用交易层性能指标（秒精度） CSPAE 科来流量分析处理引擎 数据源 - 全网络数据包 Flow,数据,分析结果,警报,Data Source of AIOps,Network,OS,Application,Client,Business,Machine Learning for AI
3、Ops,Supervised Learning,Unsupervised Learning,Machine Learning from Ali,Visualization to Operations,Operations to Autonomous Operations,How to start AIOps,Network,OS,Application,Client,Business,Security,NPMD,Syslog,APM,Mobile SDK,NPMD,Which is the best Beginning,AIOps,技术成熟度,实施周期,资金成本,团队能力,安全,Why is NPM the Best Beginning,用户 or 前端,Firewall,ADC,ADC,WEB,APP,ADC,CORE,Cola RAS,Cola UPM,技术成熟度,资金成本,实施周期,生产安全,团队能力,GARTNER Magic Quadrant （2018）,Situational Awareness Business,Situational Awareness Branchs,Situational Awareness Application,Situational Awareness - Network,Situational Awareness - Event,
