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撥雲見日 – Cloud Computing at Yahoo!
雅虎雲端運算的策略
• Optimizing for Yahoo! global platforms
• Data processing and serving environments
• Faster product development and innovation
• Reduce costs for infrastructure
• Open Source
• Multi-year effort
Target Scale for Yahoo! Cloud
• Massive user base and engagement-500M+ unique users per month-Hundreds of petabytes of storage -Hundreds of billions of objects-Hundreds of thousands of requests/sec
• Global-Tens of globally distributed data centers-Serving each region at low latencies
• Challenges-Rapidly extracting value from voluminous data-Highly variable usage patterns-Downtime must be avoided: very expensive
Ads Optimization
Improving Consumer Experience
Content Optimization
Search Index
Image/Video Storage &Delivery
AttachmentStorage
Load Balancing
RSS Feeds
Site thumbnails
Yahoo! Cloud Services
Common Approaches to QA, Production Engineering,Performance Engineering, Datacenter Management, and Optimization
ID & Account Management
Shared Infrastructure
Provisioning & Virtualization
Simple API’s
Operational Storage
Structured, unstructured
Batch Storage & Processing
Large scale distributed processing
Edge Content Services
Caching, Proxies
Online Serving
Web, Data
Security and Authentication
Metering, Billing
Monitoring & QoS
Yahoo! Cloud Services
ROI & InnovationUsers
Applications
Platform Services
Cloud Services
Physical Layer
IaaS
PaaS
SaaS
雲端人才培訓計劃
• Hadoop & MapReduce 訓練課程-Hadoop 入門-MapReduce Programming-Pig 入門
• Yahoo! Technology-YUI, Continuous Integration, Scrum Development Process
• 實習-在 Yahoo Hadoop Cluster 上熟悉 MapReduce 的設計邏輯-培養在雲端環境上專案開發的技巧
• 經過密集的訓練課程及線上專案的實習後,加入雅虎產品平台的開發工作。
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