Microsoft Cloud Computing

Microsoft Cloud Computing
David Chou
Architect, Microsoft
blogs.msdn.com/dachou

2010+
Cloud
2000s
SOA
1990s
Web
1980s
Client-Server
1970s
Mainframe
Fifth Paradigm Shift in Computing

Microsoft in the Cloud
(6 years)
4B emails/day
(7 years)
5B conf
min/yr
(15 years)
450M+
active users
(11 years)
2B queries/mth
(11 years)
320M+ active
users
(12 years)
Largest non-
ICP/IP cloud service
x100M users
(13 years)
550M
users/mth
(15 years)
450M+
active users

Bing – “Auto Pilot” Architecture
Data Repositories
Web & Structured Data Indices
Query Analysis & Processing
Front-End UX
Internet

Generalized Cloud Application Model
Always Available
Service-Oriented
Model-Driven
Scale-Out
Staged Production
Self-Service
Failure Resilient
Federated
Multi-Tenant
Elastic

The Microsoft Cloud
Chicago Data Centre
Purpose-built data centre to accommodate containers at large scale
Cost $500 million, 100,000 square foot facility (10 football fields)
40 foot shipping containers can house as many as 2,500 servers
Density of 10 times amount of compute in equivalent space in traditional data centre
Can deliver an average PUE of 1.22
Power Usage Effectiveness benchmark from The Green Grid™ consortium on energy efficiency

The Microsoft Cloud
Chicago Data Centre

The Microsoft Cloud
~100 Globally Distributed Data Centers
Quincy, WA
Chicago, IL
San Antonio, TX
Dublin, Ireland
Generation 4 DCs

The Microsoft Cloud
Platform-as-a-Service

Scalability & Availability
Consistency & Control
On-premise
Public Cloud
Real-Time Performance
Redundancy & Resiliency
Global Reach
Security & Privacy
Customizability
Ease of Provisioning
Abstract Resources
Physical Resources
A Hybrid World
Homogeneity
Heterogeneity

Application
Marketplace
Information Marketplace
Personal Data Repository
Application Services
Workflow Hosting
Distributed Cache
Services Hosting
Frameworks
Claims-Based Identity
Federated Identities
Secure Token Service
Declarative Policies
Security
Composite Applications
On-Premise Bridging
Service Bus
Connectivity
Transact-SQL
Data Synchronization
Relational Database
ADO.NET, ODBC, PHP
Data
C / C++
Compute
Win32
VHD
Unstructured Data
Blobs
Message Queues
Distributed Filesystem
Content Distribution
Storage
Windows Azure Platform

“Dublin”
“Velocity”
Frameworks
“Geneva”
Security
Access Control
Project “Sydney”
Connectivity
Service Bus
SQL Azure Data Sync
Data
Compute
Table Storage Service
Blob Storage Service
Queue Service
Xdrive
CDN
Storage
Windows Azure Platform

Kelley Blue Book
About
kbb.com, established 1995
14M UU/month
Multiple physical data centers
Technical implementation
Client – Silverlight, DeepZoom, WPF
Web – IIS 7, ASP.NET MVC
Server – SQL Server 2005/2008, Windows Server 2003/2008
Tools – Visual Studio 2008, .NET Framework 3.5
63,000 lines of .NET code
2.5 GB SQL Server DB w/ 125 tables, 15 indexed views, 117 stored procs, etc
Solution
Cloud-based overflow capacity
Windows Azure Web Role
SQL Azure database
Benefits
~$100,000 savings / year in hosting costs alone
Retire failover data center (27 Web servers & 9 SQL Servers)
<1% code changes needed for application compatibility
6 weeks down to 6 minutes to add server capacity

Application Models
Web Hosting
Massive scale infrastructure
Burst & overflow capacity
Temporary, ad-hoc sites
Application Hosting
Hybrid applications
Composite applications
Automated agents / jobs
Media Hosting & Processing
CGI rendering
Content transcoding
Media streaming
Distributed Storage
External backup and storage
High Performance Computing
Parallel & distributed processing
Massive modeling & simulation
Advanced analytics
Information Sharing
Reference data
Common data repositories
Knowledge discovery & mgmt
Collaborative Processes
Multi-enterprise integration
B2B& e-commerce
Supply chain management
Health & life sciences
Domain-specific services

Internet-Scale Application Architecture
Design
Horizontal scaling
Service-oriented composition
Eventual consistency
Fault tolerant (expect failures)
Security
Claims-based authentication & access control
Federated identity
Data encryption & key mgmt.
Management
Policy-driven automation
Aware of application lifecycles
Handle dynamic data schema and configuration changes
Data & Content
De-normalization
Logical partitioning
Distributed in-memory cache
Diverse data storage options (persistent & transient, relational & unstructured, text & binary, read & write, etc.)
Processes
Loosely coupled components
Parallel & distributed processing
Asynchronous distributed communication
Idempotent (handle duplicity)
Isolation (separation of concerns)

Platform of Choice
SERVICES
SERVERS
Applications
Developer Tools
Programming Model
Relational Database
Operating System
Systems Management

Platform of Choice

3 Key Take-aways
Platform-as-a-service fabric cloud
Hybridon-premisesoftware and cloudservices platform
Consistentprogramming modeland tools

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Microsoft Cloud Computing

by David Chou on Nov 21, 2009

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