The document discusses the state of global infrastructure performance and the challenges of delivering optimal performance to global web audiences. It summarizes that: 1) Content delivery networks (CDNs) were created to help address global performance challenges, but no single provider can deliver optimal coverage worldwide due to the immense scale and complexity of the internet. 2) A diversified portfolio using multiple cloud providers and CDNs is necessary to maximize global performance. 3) Real-time performance data from a global network is needed to intelligently route traffic to the best-performing locations for each user.

1. The State of Global Infrastructure Performance
Marty Kagan
marty@cedexis.com

2. ORIGINS

3. Web audiences are increasingly global

4. But global performance remains challenging

5. In 2002, the Solution was Content Delivery Networks

6. But the Internet is Immense and Complex
Countries
230
Networks
28k+

7. And Even the Largest Providers Cover Only a Small %
Akamai Technologies: The $6.6B Market Leader in CDN

8. Rackspace Hosting
Mean Response Times 26 August 2012

9. Akamai CDN
Mean Response Times 26 August 2012

10. Edgecast CDN
Mean Response Times 26 August 2012

11. Level3 CDN
Mean Response Times 26 August 2012

12. CloudFront CDN
Mean Response Times 26 August 2012

13. Fastweb CDN
Mean Response Times 26 August 2012

14. The Solution:
Maximizing global performance
requires a diversified portfolio
! Multi-Cloud is the only way to deliver
optimal performance to global users.

15. Variation by Network
Fastest Average Response Time, 26 August 2012

16. Variation by Network
Fastest Average Response Time, 26 August 2012

17. Variation by Network
Fastest Average Response Time, 26 August 2012

18. Variation over Time

19. How does one capture the end-user experience?

20. What We Need is a Community
RADAR
Assess performance of
every cloud provider
and content delivery
network on the planet
ACTIONABLE
INTELLIGENCE

21. Seed the Market

22. Seed the Market

23. Seed the Market

24. Build a Community

25. Radar Community Edition

26. Radar: Javascript – Execution

27. Detailed reporting

28. Operating at Scale
Mission critical software as a service platform running on 150 servers
deployed in 48 datacenters in 26 cities in 16 countries on 5 continents
Measurements
1B (Day)
Decisions
13B (Month)
Public Clouds
87
Private Platforms
350+

29. WHAT HAVE WE LEARNED

30. Amazon EC2 Europe
Median Response Times 26 August 2012

31. Amazon EC2 South America
Mean Response Times 26 August 2012

32. Amazon EC2 Asia Pacific (Singapore)
Mean Response Times 26 August 2012

33. Windows Azure West US
Mean Response Times 26 August 2012

34. Windows Azure West Europe
Mean Response Times 26 August 2012

35. Windows Azure East Asia
Mean Response Times 26 August 2012

36. Internap AgileCLOUD Texas
Mean Response Times 26 August 2012

37. Internap AgileCLOUD Amsterdam
Mean Response Times 26 August 2012

38. Internap AgileCLOUD Singapore
Mean Response Times 26 August 2012

39. Variation by Network

40. Variation by Network

41. Variation by Network

42. Variation by Network

43. How does one drive traffic across a hybrid-cloud?

44. What We Need is a Way to Make Data Actionable
RADAR OPENMIX
Assess performance of Instantly match local
every cloud provider user demand with the
and content delivery best performing
network on the planet provider at a given
moment in time
ACTIONABLE ADAPTIVE
INTELLIGENCE AUTOMATION

45. How Openmix Works

46. Software Defined Request Routing

47. No Rules Engine
4

48. Means Unprecedented Flexibility
4

49. Simple DNS Integration
CNAME
- hosting.lemonde.fr
CNAME - hosting2.lemonde.fr
- lemonde.vo.llnwd.net
Lemonde.fr 2-01-271d-0002 - lemonde.Amazon.net
.cdx.cedexis.net - medias.lemonde.fr.edgesuite.ne
- medias.lepost.fr.c.footprint.net
- orig-10001.lemonde.cotcdn.net

50. Hosted on 3 Redundant Anycast Networks
Network I Network II Network III
• Amsterdam • Frankfurt • Amsterdam
• Atlanta • Hong Kong • Ashburn
• Chicago • London • Atlanta
• Dallas • Los Angeles • Brussels
• Frankfurt • Madrid • Chicago
• Hong Kong • Miami • Dallas
• London • Milan • Frankfurt
• Los Angeles • New York • London
• New York • Paris • Los Angeles
• Paris • San Jose • Miami
• San Jose • Seoul • New York
• Seattle • Singapore • Phoenix
• Singapore • Stockholm • San Jose
• Sydney • Tokyo • Sao Paulo
• Tokyo • Toronto • Seattle
• Washington DC • Washington DC • Toronto

51. Technical Benefits
Average Page Load Times for Hotel Reservation System
20.0
18.0
16.0
14.0
12.0
Seconds
10.0
8.0
6.0
APDEX threshold
4.8 seconds
4.0
2.0
-
China USA Brazil Thailand Australia France Canada Germany
Single-Source 18.6 9.0 8.0 7.7 6.6 4.7 4.7 3.9
Multi-Source 6.8 4.2 4.8 3.5 4.1 3.2 2.8 2.9

52. NEXT STEPS

53. Our Mission
Automated management
of global computing
resources and traffic
routing based on real-time
intelligence and ad hoc
logic.

54. Cedexis Today

55. Cedexis Tomorrow

56. What We Want
To make the web faster
for every user on the
planet.