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。

Questions?