This presentation discusses architectural patterns for building applications in the cloud. It begins with an overview of Windows Azure and how the cloud environment differs from traditional infrastructure in being uniform, automated, designed for failure and scale. The presentation emphasizes rethinking applications for the cloud by designing for failure and scale through techniques like caching, autoscaling, asynchronous processing and distributing content and data across multiple data centers. The goal is to build resilient applications that can scale easily to demand spikes without single points of failure.

1. APRIL 17, 2012 | SLIDE 1

2. Architectural Patterns for the Cloud
Maarten Balliauw
@maartenballiauw
APRIL 17, 2012 | SLIDE 2

3. Who am I?
 Maarten Balliauw
 Antwerp, Belgium
 www.realdolmen.com
 Focus on web
 ASP.NET MVC, Windows Azure, SignalR, ...
 MVP Windows Azure & ASPInsider
 http://blog.maartenballiauw.be
 @maartenballiauw
 Author: Pro NuGet - http://amzn.to/pronuget
APRIL 17, 2012 | SLIDE 4

4. Agenda
 Quick recap: Windows Azure
 What’s different in the cloud?
 Rethinking apps
 Conclusion
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5. Quick recap
Windows Azure
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6. Windows Azure is a cloud platform
 On-demand
 Self-service
 Pay per use
 Highly automated
APRIL 17, 2012 | SLIDE 7

7. Windows Azure Components
Compute Storage SQL Azure Service Bus Connect
BI Marketplace CDN Caching ACS
Application Services Storage Services Foundation Services
APRIL 17, 2012 | SLIDE 8

8. What’s different
in the cloud?
APRIL 17, 2012 | SLIDE 9

9. Differences with your infrastructure
 Uniform
 Automated
 Designed for failure
 Designed for scale
 It’s not in your datacenter
APRIL 17, 2012 | SLIDE 10

10. Uniform
 Every machine +/- the same
 No specialized hardware
 No specialized OS*
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11. Demo
Customizing the Windows Azure virtual machine
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12. Automated
 Makes decisions on provisioning &
updating
 Monitors health
 The platform knows what’s best
 Not necessarily for your app…
APRIL 17, 2012 | SLIDE 13

13. Designed for failure
UD 1
UD 2
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14. Designed for scale
 Scale out
 Stateless
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15. It’s not in your datacenter
 Integration
 Authentication
APRIL 17, 2012 | SLIDE 16

16. Rethinking apps
What do I have to think about?
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17. Scenario: Newspaper website
 National & International
 Sudden spikes in usage
 Dynamic content
 Static content
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18. Current architecture
 Will work on the cloud!
 Will fail on the cloud!
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19. Design for failure
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20. Assume everything will fail
 Automated service maintenance
 Compute node crash
 Storage throttling
 SQL Azure throttling
 Connectivity
 Your code
APRIL 17, 2012 | SLIDE 21

21. Retry everything
SQL Azure Error 40501
The service is currently busy. Retry the
request after 10 seconds.
Retry against anything that might be external
SQL Azure, Windows Azure Storage, Service Bus, …
http://windowsazurecat.com/2011/02/transient-fault-
handling-framework/
APRIL 17, 2012 | SLIDE 22

22. The entire datacenter fails!
 Run in 2+ datacenters
 Keep data synchronized
 All data
 or limit scope
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23. Refactoring the architecture
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24. Windows Azure Data Centers
100ms
50ms
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25. Windows Azure Traffic Manager
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26. Windows Azure Traffic Manager
 Strategies
 Round-robin
 Fail-over
 Performance (geo)
 Solves datacenter outage
APRIL 17, 2012 | SLIDE 27

27. Are we there yet?
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28. Solutions to a SPOF being down
 Set a monitoring endpoint for TM
 Take the entire datacenter out of the loop
 Take the SPOF out of the story
 Degrade gracefully
APRIL 17, 2012 | SLIDE 29

29. Refactoring our architecture
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30. Design for scale
*and failure
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31. Belgians are not used to snow
What will happen to our
architecture?
APRIL 17, 2012 | SLIDE 32

32. Here’s what will happen…
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33. Solution: scale out!
 Add more VM’s!
 Autoscaling (WASABi)
 Windows Azure Autoscaling Application Block
 Enterprise Library
 http://entlib.codeplex.com/wikipage?title=WASABiBet
aReleaseNotes&referringTitle=EntLib5Azure
APRIL 17, 2012 | SLIDE 34

34. Solution: scale out!
 Add more VM’s!
 Autoscaling (as-a-Service)
 www.opstera.com
APRIL 17, 2012 | SLIDE 35

35. Here’s what will happen…
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36. SQL Azure
 Monitored by the platform
 The platform does not like high DB traffic
 Throttling & retries
APRIL 17, 2012 | SLIDE 37

37. Caching
 Most of our users are doing reads
 Cache content near where it’s needed
 Windows Azure Caching
 Blob Storage
APRIL 17, 2012 | SLIDE 38

38. Refactoring our architecture
APRIL 17, 2012 | SLIDE 39

39. Caching
 How do you populate it?
 When do you populate it?
 When do you invalidate it?
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40. Work asynchrounously
 Read from cache
 Present? Use cache
 Not present? Ask to cache it & read from
DB
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41. Refactoring our architecture
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42. A typical web request…
 1 request is dynamic
 493 requests are static*
 Get that static content out of your servers!
 Cache content near where it’s needed
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43. Windows Azure CDN
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44. Refactoring our architecture
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45. Conclusion
APRIL 17, 2012 | SLIDE 46

46. Key takeaways
 Cloud is different
 Design for failure
 Design for scale
 Work asynchronously
 Cache close to where it’s needed
 Also think price vs. Allowed outage
APRIL 17, 2012 | SLIDE 47

47. One more… Learn from others!
 Amazon - http://slidesha.re/AlaHIG
 Trello - http://bit.ly/xO5G9e
 YouPorn - http://bit.ly/yUSanQ
 StackOverflow - http://bit.ly/xkLvH9
 InstaGram - http://bit.ly/xbWuzx
 … (highscalability.com)
APRIL 17, 2012 | SLIDE 48

48. http://blog.maartenballiauw.be
@maartenballiauw
http://amzn.to/pronuget
or Install-Package ProNuGet
THANK YOU!
APRIL 17, 2012 | SLIDE 49