1. AWS CLOUD SCHOOL
London - Thursday 12th April, 2012

2. Hello.

3. Thank you.

5. Storage
Tools &
Compute
Support
Databases

6. Consumer Seller
business business

7. Decades of experience
Operations, management and scale

8. Programmatic access

9. Unexpected innovation

10. Blinding flash of the
obvious

12. 6 years young
Amazon S3 launched on March 14th, 2006

13. Objects in S3
Billions of objects
905 B
1000.000
750.000
500.000
250.000
0
Q4 2006 Q4 2007 Q4 2008 Q4 2009 Q4 2010 Q4 2011 Q1 2012
650k+ peak transactions per second

18. Utility computing
Available. On-demand. Flexible.

19. Let’s go!

20. Launch a
high availability
web app
Reliable. Scalable. On-demand. From anywhere.
10 minutes.

21. cloudbyexample.net

22. What just happened?

23. AP LICAT
P ION ARCH ECTU
IT RE

24. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Application servers
Data store

25. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Application servers
Data store
Amazon DynamoDB

26. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Amazon EC2 Application servers
Data store
Amazon DynamoDB

27. AP LICAT
P ION ARCH ECTU
IT RE
Elastic Load
Balancer Load balancer
Amazon EC2 Application servers
Data store
Amazon DynamoDB

28. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Application servers
Data store

29. Cloud architecture
best practice

30. “Everything fails,
all the time”

31. Design for failure

32. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Decoupled Application servers
Data store

33. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Stateless Application servers
Data store

34. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Redundancy Application servers
Data store

35. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Redundancy Application servers
Data store

36. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Availability zone
Application servers
redundancy
Data store

37. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Horizontal scale Application servers
Data store

38. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Horizontal scale Application servers
Data store

39. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Horizontal scale Application servers
Data store

40. Design for elasticity
Scale out. Scale in.

41. Usage
Midnight 7am 9am Noon 3pm 5pm Midnight
Time of day

42. Usage
January December
Time of year

43. Usage
January December
Time of year

44. Usage
60%
January December
Time of year

45. Design for cost
Pricing options.

46. Economies of scale

47. 19 price drops
Committed to passing savings to customers

48. Utilisation

49. Achieving economies of scale
100%
Time

50. Achieving economies of scale
100%
Reserved capacity

51. Achieving economies of scale
100%
On-demand
Reserved capacity

52. Achieving economies of scale
100%
On-demand
Reserved capacity

53. Spot market
Choose your own price for compute

54. Fine grained
time/cost benefit

55. 30,472 cores
$1,279 per hour

56. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Application servers
Data store

57. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Application servers
CloudFormation
template
Data store

58. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Application servers
CloudFormation
template
Data store

59. AWS CloudFormation
Automated provisioning tool. Template based.

60. Atomic and idempotent
Also: free!

61. CloudFormation template
CloudFormation service

62. CloudFormation template
CloudFormation service
EC2 instances Load balancer

63. EC2 instance sizes
Range of compute, storage and memory
Metered by Elastic Compute Unit

64. Standard High memory High CPU
m1 m2 c1

65. 1 instance for 100 hours
=
100 instances for 1 hour
You choose where to balance cost against time.

66. Placement groups
Cluster compute
10 gig E, non blocking network

67. 42nd
240 TFLOPS. World’s fastest ethernet supercomputer.

68. GPU
2 x NVIDIA Tesla. 400 cores each.
Molecular modeling. Hedging. Transcoding and rendering.

69. CloudFormation template
CloudFormation service
EC2 instances Load balancer

70. CloudFormation template
CloudFormation service
EC2 instances Load balancer S3 bucket

71. 99.999999999%
durability

72. CloudFormation template
CloudFormation service
EC2 instances Load balancer S3 bucket

73. CloudFormation template
CloudFormation service
EC2 instances Load balancer S3 bucket Users and
groups

74. CloudFormation template
CloudFormation service
EC2 instances Load balancer S3 bucket Users and Autoscaling
groups

75. CloudFormation template
CloudFormation service
EC2 instances Load balancer S3 bucket Users and Autoscaling
groups
Security groups Port access Write access Scaling parameters

76. Identity and Access
Management

77. API level restrictions
Restricted by default

78. Account

79. Billing
Account credentials Account
MFA

80. Account
DBA Developer Sys admin Finance
Roles

81. Account
DBA Developer Sys admin Finance
Roles
Sally
Robert
Users
Chris

82. Security credentials
Multifactor authentication
Management console access
Data read/write access
API level access

83. Account
DBA Developer Sys admin Finance
Roles
Sally
Robert
Users
Chris

84. Restricted credentials
Access specific S3 bucket, DynamoDB and
CloudFormation

85. A note on security...

86. Shared responsibility

87. Service Organisation
Controls 1 ISO 27001
Shared responsibility
FISMA PCI DSS
Moderate Level 1

89. Data stays local

90. aws.amazon.com/security

91. Autoscaling

92. Automatic scaling
Availability zone and load balancer aware.

93. Metrics
CPU, network, IO, custom

94. Metrics
CPU, network, IO, custom
CloudWatch alarms
Set operational thresholds: IOPS, page load time

95. Metrics
CPU, network, IO, custom
CloudWatch alarms
Set operational thresholds: IOPS, page load time
Trigger autoscaling policy
Adjust autoscaling groups within bounds
Register with load balancer

96. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Application servers
Data store
Amazon DynamoDB

97. Any database on Amazon EC2
MySQL, DB2, Oracle, PostgreSQL...

98. Relational Database Service
Managed MySQL and Oracle databases

99. Rapid High
provisioning availability
Scalable Scalable
storage compute
Relational Database Service
Managed MySQL and Oracle databases

101. High performance databases
Increase throughput
Increase availability
Reduce latency

102. High performance databases
Read replicas
Push-button
scaling Increase throughput
ElastiCache
Increase availability
Reduce latency

103. High performance databases
Increase throughput
Multi-AZ Increase availability
Reduce latency

104. High performance databases
Increase throughput
Increase availability
Reduce latency ElastiCache

105. Problem
Performance decreases at scale

106. Performance
Predictable, consistent
Scale

107. Performance
Predictable, consistent
Degraded performance
with scale
Scale

108. Performance
Predictable, consistent
Degraded performance
with scale
Scale

109. = more problems

110. Data caching
Provisioning!
Data sharding
= more problems
Cluster management
Fault management

111. Undifferentiated
heavy lifting

112. DynamoDB

113. Fully managed
NoSQL database
service

114. Extremely fast
performance

115. Consistently fast
performance

116. Low latency
Single digit millisecond

117. SSD backed
Low latency
Single digit millisecond
< 5 ms reads < 10 ms writes

118. Seamless scalability
No table size limits. Unlimited storage.
Live repartitioning. Zero admin.

119. Durable and available
Consistent, disk-only writes

120. Predictable performance
Provisioned throughput

121. Reserve required IOPS
Per table. Set at creation. Scale via API.

122. Scale at any time
No downtime

123. Data model
Flexible. Schema-less.

124. Simple key/value pairs
title => “Introduction to DynamoDB”
date => “20120320”

125. Associative array,
or Hash
[ title => “Introduction to DynamoDB”,
date => “20120320” ]

126. Attributes
[ title => “Introduction to DynamoDB”,
date => “20120320” ]

127. [ title => “Disaster Recovery with AWS”,
date => “20120320”,
format => “online seminar”,
presenter => “Jeff Barr” ]
Attributes
[ title => “Introduction to DynamoDB”,
date => “20120320” ]

128. [ title => “Disaster Recovery with AWS”,
date => “20120320”,
format => “webinar”,
presenter => “Jeff Barr” ]
Items
[ title => “Introduction to DynamoDB”,
date => “20120320” ]

129. [ title => “Disaster Recovery with AWS”,
date => “20120328”,
format => “webinar”,
presenter => “Jeff Barr” ]
Table
[ title => “Introduction to DynamoDB”,
date => “20120320” ]

130. Table

131. Item
“UserID” = “1”
“Date” =
“20100915”
“Title” = “flower”
“Tags” = “flower”,
“jasmine”, “white”

132. “UserID” = “1” “UserID” =”2” “UserID” =”3”
“Date” = “Date” = “Date” =
“20100915” “20100916” “20100917”
“Title” = “flower” “Title” = “ferrari” “Title” = “coffee”
“Tags” = “flower”, “Tags” = “car”, “Tags” = “drink”,
“jasmine”, “white” “italian” “delicious”

133. “ImageID” = “1” Primary or hash key
“Date” = “20100915”
“Title” = “flower”
“Tags” = “flower”,
“jasmine”, “white”

134. “ImageID” = “1” Primary or hash key
“Date” = “20100915” Composite or range key
“Title” = “flower”
“Tags” = “flower”,
“jasmine”, “white”

135. “ImageID” = “1” Primary or hash key
“Date” = “20100915” Composite or range key
“Title” = “flower”
“Tags” = “flower”, Sets of strings
“jasmine”, “white”
or numbers

136. Best practice
Well balanced, fine grained hash keys.
Customer, order, item, etc. rather than store_id.

137. Simple API
Only 12 operations.

138. Consistency
Writes are always consistent.
Implicit, item-level transactions.

139. Durability
Writes occur to disk, not memory.
Writes are acknowledged once they have been
made in two physical data centres.

140. Availability
Region specific (not AZ)
Continuously replicated across multiple AZs

141. Zero admin
Single API call deployment and scaling.

143. AP LICAT
P ION ARCH ECTU
IT RE
Load balancer
Application servers
Data store

144. High availability
Decouple. Horizontal scale. Availability zones.

145. Automate
Rapid, error free provisioning.

146. DynamoDB
No administration NoSQL.

147. What’s next?

148. Analytics with Elastic
MapReduce
Built for data. Designed for humans.

149. create external table items_db
(id string, likes bigint, views bigint)
stored by
'org.apache.hadoop.hive.dynamodb.DynamoDBStorageHandler'
tblproperties
("dynamodb.table.name" = "items",
"dynamodb.column.mapping" = "id:id,likes:likes,views:views");
select id, likes, views from items_db
order by views desc;

150. Simple Workflow
Managed workflows

151. Create thumbnail Update
Top 100
New share
Upload image Duplicate detection

152. Amazon CloudSearch
Managed search. Provide documents. Search.
Up and running in an hour.

153. Create search domain
Upload documents
Search Document Format (SDF)
XML or JSON
Search!

154. Sophisticated
applications

155. Reliable
applications

156. Innovative
applications

157. Undifferentiated
heavy lifting

158. Productivity

162. Left image Right image
Warp Warp
Stereo match
3D map
Tiling

164. Thank you!

165. Q&A
matthew@amazon.com

166. Tutorials
Self-directed. Choose your track.

168. Hands-on sessions

169. Break out sessions

170. AWS staff

171. cloudbyexample.net