1. Cloud Computingfor Banking19 April 2010
Jens Riboe
jens.riboe@ribomation.com

2. Jens RiboeRibomation
Fr diverse kunder
KTH
Ribomation
ERA
London
Goyada
Wily (San Francisco)
VzB
OW
RM
SICS
1990
1995
2000
2005
2010
3. Agenda
What
Why
Who
When
Where
How
Background and terminology
Usage areas
Cloud types
Intro to AWS
Problems
Future
Ask your questions after the speech
4. ElasticComputing
Cloud Computing
Software as a Service
Background and Terminology
5. Between the salespeeks
Howshouldweutilizeour servers between the peekdayssuch as Xmas and Valentines Day? wonderedone of the worldslargestretailingcompany
6. The short and unglamorous answer
Cloud Computing is a new paradigm for deployment of applications
It utilizes virtualization in a massive scale
7. Cloud Computing = V + C + A + P
Virtualization (Xen)
+ DataCenter (Amazon)
+ PublicAccess (SSH/X.509)
+ PricingModel ($0.08/h)
8. Software-as-a-Service (SaaS)
Web accessible service
Fast growing business area
No direct logical coupling to cloud computing
Possible to run a SaaS from a desktop computer, although the performance will be bad
Many large SaaS companies are running their own server farms
The term was coined by Salesforce
9. SaaS vs. Cloud Computing
Consumer
Provider
SaaS
Cloud Computing
10. XaaS vs. Cloud Computing
Cloud Computing
XaaS
SaaS
CaaS
Google Charts
PaaS
RightScale
IaaS
AWS
11. XaaS
There are many variants of Something-as-a-Service
Component-as-a-Service
Software modules/components
Platform-as-a-Service
Deployment and configureation
Infrastructure-as-a-Service
Virtual resources, such as servers, hard drives, storage, data bases, IP addresses
12. Sample SaaS
13. Software cost
Development
Testing
Maintenance
Education
Pays for a lot more features than are used
Licenses
Upgrades
Pay as you go
In-house development
Standard applications
SaaS
14. Business in the cloud
Sales support
Project management
Time sheets
Accounting
. . .
15. Documents in the cloud
Google Apps
Communication
Messages
Email
Calendar
Contacts
Documents
Write
Calc
Present
16. Backup in the cloud
17. Desktop in the cloud
18. Testing in the cloud
Massive traffic
Geographical dispersed
19. Extra server / computing power
Simple/easy deployment
Scalable applications
Large computations
Usage areas
20. (1) Extra server
Project server
Test server
Load generator
. . .
The wear and tear age is here for servers
21. (2) Easy deployment
Point and click deployment
Easy and quick to try out different setups
5 min
22. (3) Scalable applications
Exempel: animoto.com
1
From 10 to 3500 servers in a week
2
3
Users:
Monday: 25K Users
Tuesday:50K Users
Wednesday: 100K Users
Thursday: 250K Users
Platform:
EC2
SQS
S3
RightScale
Ruby on Rails
Source:http://www.slideshare.net/startpad/startpad-countdown-8-amazon-web-services-and-you-470919/36
23. (4) Largecomputations
Transaction analysis
Massive conversations/transformations
Data aggregation
Data warehousing
Source:http://www.slideshare.net/acarlos1000/hadoop-basics-presentation/28
http://open.blogs.nytimes.com/2007/11/01/self-service-prorated-super-computing-fun/
24. Infrastructure cloud
Application cloud
Computation cloud
Cloud types
25. Infrastructure cloud (i-cloud)
As hosting, but in a massive scale
Pay-as-you-go
Rent a server per hour
Virtual server resources
Elastic computing servers
Elastic storage hard drives
Storage services SAN
Queue services job/task queue
Static IP addresses
26. Someactors
Amazon Web Services (AWS)
First, biggest and best
Hosting companies
myCityCloud (Swedish)
Rackspace
GoGrid

27. Run your own private i-cloud
Eucaluptus
Open source version of AWS
API compatible with ECS/EBS/S3
Standard in Ubuntu Server 9.x
Enomaly
The original, run by AWS
28. Application cloud (a-cloud)
Distributed platform for applications
Google App Engine (GAE)
Java/Python, BigTable
Salesforce Force.com
Their own script language, Oracle, enterprise grade
Windows Azure
.NET
29. Computationcloud (c-cloud)
Apache/Yahoo Hadoop
Distributed computation
Distributed file system
Distributed map-reduce
Open-source Java implementation
Inspired by proprietary tools of Google
HDFS (Google File System GFS)
Map-Reduce (Google ditto)
Hive (Google Big Table)
Large clusters
Yahoo has 20000+ Hadoop nodes
30. The human cloud (h-cloud)
Manypeopleworking with many tasks
The mechanical Turk (Automaton Chess Player) [1770-1854], turnedout to be a fraud. It was a human inside.
31. AWS Amazon Web Services
32. EC2 / EBS / S3 / AMI / EIA / SQS
DNS
EC2
SQS
put
get
EBS
SAN
static IP
SDB
HTTP
80
EIA
AMI
S3
HTTP
RDB
MySQL
Security Group
SSH & RDP
22 & 3389
33. EC2 Instance Types
One EC2 Compute Unit (ECU) provides the equivalent CPU capacity
of a 1.0-1.2 GHz 2007 Opteron or 2007 Xeon processor.
34. Operating Systems
Without cost and without support
With cost and with support
Complete own build
Possible to create an AMI basedout of an empty disk file.
35. Global deployment
A region consists of one or more zones
US-East (North Virginia)
US-West (North California)
EU (Ireland)
ASIA (Singapore) - planned
A zone is a logical data center
EU
Regions
US
36. Prices
37. AWS Economy
As you go
USD 0,085/h(EC2 Small)
ReservedInstance
USD 0,03/h + 227/yr
USD 0,03/h + 350/3yr
Spot
Bidding
AWS charges for each started hour
38. Problems
39. When NOT to use the cloud
Just need a fixed number of servers
Cheaper solutions available
Very specific needs
40. Legal restrictions
Certain payment, medical or personal information might not be stored outside EU
The rules never anticipated the cloud
EBS
SQS
AMI
S3
CloudFront
41. The future
42. Affects
Design of new applications
Scalable and fault-tolerant
Testing of these applications
More and better tests in shorter time
Deployment of these applications
Easier, faster and reproducible
43. Changes
IT Operations department
Able to roll out a new config within an hour
Software Development department
Able to assemble a new mash-up within an hour
Test department
Able to run the whole test suit within an hour
Business department
Able to kick-start a new campaign within an hour
44. The Big Switch - Nicholas G Carr
100 years
10 years
45. Conclusions
46. Benefits
Technical
Capacity on demand
Scale Up & Scale Down
Fault Tolerant
Simple Architecture
Economical
No Up-Front Capital Investment
Pay as you go
Start Small & Pay as You Grow
47. At a glance
Usage areas

Extra servers

48. Easy deployment 49. Scalable apps 50. Large computationsCloud types

Infrastructure (i-cloud)

51. Application (a-cloud) 52. Computation (c-cloud) 53. Changes 54. Development 55. Testing 56. Economy 57. Organizations 58. Terms 59. Elastic Computing 60. Cloud Computing 61. Software-as-a-Service 62. X-aaS