1. Building Great
Companies
on the Cloud
Roman Stanek
Founder, CEO Good Data

2. Promise
This presentation
contains no “every
cloud has silver lining”
joke
:-|

3. Who am I
Roman - quot;Stanquot; at
Starbuck's
Technologist
Entrepreneur (NetBeans,
Systinet)
Blogger (roman.stanek.org)
Czech

6. What is happening to
computing today is a
revolution, the biggest
upheaval since the
invention of the PC
in the 1970s.
Nicholas Carr

7. quot;It's stupidity.
It's worse than
stupidity: it's a
marketing
hype campaign
Richard Stallman
Founder, Free Software
Foundation

8. But we all
struggle with the
cloud definition...

9. Most of all the
graphics artists...

14. Definition:
Clouds are hardware-based services
offering compute, network and
storage capacity where:
Hardware management is highly
abstracted from the buyer
Buyers incur infrastructure costs as
variable OPEX
Infrastructure capacity is highly
elastic (up or down)
McKinsey & Company

16. No, you
cannot
install
cloud on
your
notebook.

17. Security & control

18. By a 5‐to‐1 ratio,
companies trust internal
IT systems over cloud‐
based technologies due to
fear about security
threats and loss of control
of data and systems.
Avanade Inc.

19. They are right...
Streamload: On June 15,
2007 system
administrator's script
accidentally misidentified
and deleted quot;good dataquot;
along with the quot;dead dataquot; of
some 3.5 million former
user accounts and files.

20. Or are they?
LAX Los Angeles 1,200
MIA Miami 1,000
JFK New York 900
ORD Chicago 825
EWR Newark 750
0 300 600 900 1200
10 U.S. airports with the highest weekly frequency of laptop loss
Airport Insecurity: The Case of Missing & Lost Laptops, Ponemon Institute LLC

21. This get scary...
Did not protect sensitive
65%
information contained on laptop
57%
Worry about losing their laptop
Laptop contains
53%
confidential company information
42%
Data on laptop is not backed up
0 0.175 0.35 0.525 0.7
Airport Insecurity: The Case of Missing & Lost Laptops, Ponemon Institute LLC

22. Most likely causes of data
breach?
Negligent insiders 75%
Outsourced data 42%
Malicious insiders 26%
Social engineering 2%
Hackers 1%
0 0.2 0.4 0.6 0.8
2008 Study on the Uncertainty of Data Breach Detection,Ponemon Institute LLC

23. IT environment where data
breaches occur
Off-network devices 58%
Networks 50%
Mainframes 41%
Paper files 39%
Backups 18%
0 0.15 0.3 0.45 0.6
2008 Study on the Uncertainty of Data Breach Detection,Ponemon Institute LLC

24. Ability to detect the loss or
theft of confidential
information
31%
25%
18%
16%
10%
Somehow
Very confident Confident confident Not confident Unsure
2008 Study on the Uncertainty of Data Breach Detection,Ponemon Institute LLC

25. Amazon Security/
SLAs
Multiple redundant sites
SAS70
Amazon EC2 SLA - 99.95%
4 hrs, 22 min/year
Amazon S3 SLA - 99.9%

27. Control: Plenty of startups
solving this problem already

28. Cloud or No Cloud?
For SMBs, data is safer
in the cloud
Secure, auditable, fully
compliant
Pick your cloud provider
carefully

29. Technology

31. Acronyms don’t
matter:
Caches, bloom filters, bitmap
indexes, column stores,
distributed key/value stores
and document databases

32. MapReduce law:
If It Can Be Done in
Parallel, It Will Be

33. ACID -> BASE
Traditional approaches don’t
scale
BASE - basically available, soft
state, eventually consistent:
BigTable, SimpleDB,
Cassandra, Dynamo

34. GoodData: Innovate
vs. leverage?
Processing Power
Cloud makes ROLAP approach possible
Elastic Scale
IT builds for peak load, we don’t have to
Multi-Tenancy
Single instance across 1000s of customers
Stateless
Massive load balancing (shared nothing)

35. TechCrunch Effect

36. Public cloud classes
AWS MS Azure Google AE
Predefined
CPU x86 .Net
framework
EBS, S3, SQL, Azure
Storage SimpleDB store
BigTable
Network Declarative Automatic Fixed

37. Cloud APIs
True SOA
Loosely coupled - REST, Atom
Encapsulate cloud services:
Control APIs
Data APIs
Application Functionality APIs

38. Open Cloud
Manifesto
Prevent vendor lock-in
“or”
Limit innovation

39. Cloud economics

40. If you want to
change the
game, change
the economics
of how the
game is
played
Alan M. Webber

41. Startups in the cloud
Infrastructure labor savings
No CAPEX: Less equity goes to VCs
Unpredictable demand (up and down)

42. Succeed (or fail)
faster
$500k to start technology company
Big bets aren't as big anymore
Easier for startups to adapt to shifts
Level playing field for startups

43. IT vs. Clouds
Losing their monopoly on the
infrastructure
It’s all about economics

44. 1 email
message
$0.0001

45. Fixed pricing
Most widely used pricing
No supply/demand
Simple, predictable
AWS, Google App Engine:
CPU, Storage, network traffic

46. Variable pricing
Reserved instance price (AWS):
“I have 10 instances running 24x7”
Spot price/future price:
“I want 1,000 instances at the end of
the quarter”
Off-peak pricing:
“Run my MapReduce app 10 hours
every day”

47. Cloud providers
Economies of scale
Utilization and efficiency
SLAs
Question: Long-term viability?

49. Private clouds
Violate #2 of our cloud definition:
Buyers incur infrastructure costs
as CAPEX
Virtualization on top of traditional
enterprise IT stack
Encapsulation of IT infrastructure
Scale?

50. Economies of scale
Technology Medium-sized DC Very Large DC Ratio
$95 per Mbit/sec/ $13 per Mbit/sec/
Network 7.1
month month
$2.20 per GByte / $0.40 per GByte /
Storage 5.7
month month
140 Servers / >1000 Servers /
Administration 7.1
Administrator Administrator
HAMILTON, J. Internet-Scale Service Efficiency. In Large-Scale Distributed Systems and Middleware (LADIS) Workshop (September 2008)

51. 5 Public clouds
+
500 Private clouds
505 Clouds in 2015

52. Business impact

53. Winners
Google, Amazon.com
Cisco
SaaS vendors

54. Losers
Big server vendors
(HP, Sun, Dell)
Monolithic app providers
Microsoft

55. Real winners
Innovation
SMBs, Startups
The little guy wins

56. Good Data: On Demand
Business Intelligence
Cloud + Web 2.0
metaphors
Flickr for Data
Simplicity &
Collaboration

57. Company status
30 employees
Development in
Prague
Sales & marketing in
San Francisco
Funded by industry
luminaries
www.gooddata.com

58. Thank you!