This document provides an agenda and overview for a technical workshop on Amazon Web Services (AWS). The workshop will include an AWS technical review, a discussion on cloud-powered continuous integration, and a Q&A session. Core principles that will be discussed include that everything fails all the time and that users only pay for AWS resources when they are turned on. The technical review section will cover Amazon EC2 instances, Amazon Machine Images (AMIs), importing virtual machines to EC2, instance storage types, AWS regions and availability zones. Other topics include auto scaling, load balancing, monitoring with CloudWatch, and media storage and distribution with S3. The workshop will include demonstrations of data storage options like RDS, DynamoDB and E

2. TECH WORKSHOP
Johannes Borch – Solutions Architect
Author: Carlos Conde – Solutions Architect

3. #1 AWS Technical Review
#2 Cloud-Powered CI
#4 Q&A Session

4. Core Principles

5. « Everything fails
all the time »
Werner Vogels – CTO of Amazon

6. When you turn off your cloud
resources, you actually stop
paying for them

7. Technical Review

9. Amazon EC2
On-demand instances with admin access

15. Amazon Machine
Images
Pre-configured server Image

16. YOUR CODE
3rd PARTY
LIBRARIES
CORE
SERVICES
OPERATING
SYSTEM
AMI

17. YOUR CODE YOUR CODE
3rd PARTY 3rd PARTY
LIBRARIES LIBRARIES
CORE CORE
SERVICES SERVICES
OPERATING OPERATING
SYSTEM SYSTEM
AMI AMI

18. YOUR CODE YOUR CODE YOUR CODE
3rd PARTY 3rd PARTY 3rd PARTY
LIBRARIES LIBRARIES LIBRARIES
CORE CORE CORE
SERVICES SERVICES SERVICES
OPERATING OPERATING OPERATING
SYSTEM SYSTEM SYSTEM
AMI AMI AMI

19. VM Import
Easily import virtual machine images from your existing
environment to Amazon EC2 instances
• VMware ESX VMDK images
• Citrix Xen VHD images
• Microsoft Hyper-V VHD images for Microsoft Windows
Server 2003 (R2) and 2008 (R1 & R2)

21. Instance-Store
vs.
EBS-Store

22. 32bits
64bits

24. US East Region (N. VA) EU West Region (IRE) Japan Region (Tokyo)
Availability Availability Availability Availability
Zone A Zone B Zone A Zone B Availability Availability
Zone A Zone B
Availability Availability
Availability
Zone C Zone D
Zone C
US West 1 Region (N. CA) APAC Region (Singapore) US West 2 Region (Oregon)
Availability Availability Availability Availability Availability Availability
Zone A Zone B Zone A Zone B Zone A Zone B

36. Amazon Route 53
On-demand DNS service
+
Elastic IP
Dynamic IP addresses for EC2 instances

39. Horizontal Scaling

40. Amazon CloudWatch
Monitoring for AWS resources

42. Auto Scaling
Automatically scale up/down EC2 capacity

44. Elastic Load Balancing
Distributes incoming traffic to EC2 instances

46. 6 am

47. 10 am

48. 10 am

49. 10 am

50. 7 pm

51. 7 pm

52. 7 pm

53. without elasticity you can't accelerate

54. High Availability

59. Media Storage &
Distribution

60. Amazon S3
Simple Storage Service

62. 1b Tb

63. 99.999999999%
durability

64. Amazon S3 Growth
Total Number of Objects Stored in Amazon S3 566
Billion
262 Billion
102 Billion
40 Billion
2.9 Billion 14 Billion

69. Tip: MFA Delete

70. Amazon CloudFront
Flexible content delivery network

71. US West 1 US West 2 US East Europe West Asia Pacific Asia Pacific
(N. California) (Oregon) (N. Virginia) (Dublin) (Singapore) (Tokyo)
AWS Regions
AWS Edge Locations (CloudFront & Route 53)

79. DEMO

80. Data Storage

81. Data Storage
Relational Databases

82. Amazon RDS
Relational Database Service

88. Backups

90. [[ console screenshot ]]
RDS automated backups

92. [[ console screenshot ]]
RDS DB snapshots

94. Restore

96. [[ console screenshot ]]
RDS DB snapshots

99. [[ console screenshot ]]
RDS snapshot restore

102. RDS Read-Replicas
For read-heavy applications

105. RDS Multi-AZ
Secondary replica in another Availability Zone

111. RDBMS on EC2
Special use cases

115. [[ console screenshot ]]
restore EBS from snapshot

119. Amazon ElastiCache
Memcached compatible in-memory cache

127. Data Storage
"NoSQL" Databases

128. Amazon SimpleDB
NoSQL database, key-value model

129. Domain
ID Category Name Color Size Make Model Year
item01 Clothes Shirt Siamese small,
medium,
large
item02 Clothes Sweater Blue, large 2006,
Yellow, 2007
Pink
item03 Car parts Emissions O2 Audi S4 2000,
sensor 2001,
2002

130. Item
ID Category Name Color Size Make Model Year
item01 Clothes Shirt Siamese small,
medium,
large
item02 Clothes Sweater Blue, large 2006,
Yellow, 2007
Pink
item03 Car parts Emissions O2 Audi S4 2000,
sensor 2001,
2002

131. Attributes
ID Category Name Color Size Make Model Year
item01 Clothes Shirt Siamese small,
medium,
large
item02 Clothes Sweater Blue, large 2006,
Yellow, 2007
Pink
item03 Car parts Emissions O2 Audi S4 2000,
sensor 2001,
2002

132. Values
ID Category Name Color Size Make Model Year
item01 Clothes Shirt Siamese small,
medium,
large
item02 Clothes Sweater Blue, large 2006,
Yellow, 2007
Pink
item03 Car parts Emissions O2 Audi S4 2000,
sensor 2001,
2002

133. Amazon DynamoDB
Fully managed NoSQL database

136. Low Latency
ADMIN
Massive and Seamless
Scalability
Durable and Available
Predictable Performance
Zero Administration

137. Average reads<5ms, writes<10ms

140. DEMO

141. Best Practices

142. Design for Failure
• Elastic IP addresses
• Multiple Azs
• Snapshot EBS volumes

143. Multiple AWS accounts
• Production
• Development

144. AWS IAM
Identity and Access Management

145. 145
Identity & Access Management (IAM)
IAM offers greater security, flexibility,
and control when using AWS, including:
• Integration with your corporate directory
• Create and manage user groups
• Assign Permissions to Users and Groups
• Manage Passwords

146. Use multi-factor
authentication
for admins

149. Loose Coupling
Adopt SOA principles

150. Create Independent components
Design everything as a Black Box
Think in terms of services
Load-balance clusters
Amazon SQS as Buffers
Tight Coupling Controller A Controller B Controller C
Q Q Q
Loose Coupling
using Queues Controller A Controller B Controller C

151. Amazon SQS
Simple Queue Service

152. Use notifications
You need to know when something's wrong

153. Amazon CloudWatch
Monitoring for AWS resources
+
Amazon SNS
Simple Notification Service

155. Tip – Instance Optimizer
Free Memory
Free CPU PUT 2 weeks
Free HDD
At 1-min
intervals Amazon CloudWatch
Alarm
Instance
Custom Metrics
“You could save a bunch of money by switching
to a small instance, Click on CloudFormation Script to
Save”

156. Implement Elasticity
… In all your components

157. Automate
AWS is a programmable datacenter

159. App Vending
Machine
Pre-configured
IT security-blessed
auto-scalable
auto-backup
multi-AZ
full-control
one-click deployable
enterprise apps

160. APIs / CLI
Script your IT infrastructure

163. Java, Ruby, Python, PHP, .Net
…
res = ec2.runInstances new RunInstancesRequest([
imageId: "ami-00754474",
keyName: "aws-sa-ww-key",
instanceType: "m1.small",
securityGroups: ["httpssh"],
minCount: 1,
maxCount: 1,
userData: "AWSWeb.war".bytes.encodeBase64().toString()
])
…

164. CLI
PROMPT> ec2-run-instances ami-b232d0db -n 3 --availability-zone us-east-1a

165. HTTP
https://ec2.amazonaws.com/?Action=RunInstances
&ImageId=ami-60a54009
&MaxCount=3
&MinCount=1
&Placement.AvailabilityZone=us-east-1b
&Monitoring.Enabled=true
&AUTHPARAMS

166. AWS CloudFormation
Template-based provisioning service

174. Test & Prototype
On-demand, pay as you go testing and
prototyping

176. Data-based decision
making
Drive your development by user's feedback

178. "Hadoop is a reliable storage and data analysis system"
HDFS MapReduce

179. MapReduce

185. (map ‘( ))
( )
(reduce ‘( ))

186. Each input to a map is a list of <key, value> pairs
(<a, > , <o, > , <p, > , …)
Each output of a map is a list of <key, value> pairs
(<a’, >, <o’, >, <p’, >, …)
Each input to a reduce is a <key, value-list>
(<a’, >, …)
Reduced into a list of values

190. Deploying a Hadoop cluster is hard
http://eddie.niese.net/20090313/dont-pity-incompetence/

191. Amazon Elastic
MapReduce
Hadoop + The AWS Cloud

194. Data Warehouse
(Batch Processing)
Data Warehouse Data Warehouse
(Steady State) (Steady State)
Shrink to
Expand to 9 instances
25 instances

195. Reducing Costs with Spot Instances
Scenario #1 Scenario #2
Job Flow
Job Flow
Duration:
Duration:
7 Hours
14 Hours
Cost : #2: Cost with Spot
4 instances *14 hrs * $0.50 = $28 4 instances *7 hrs * $0.50 = $13 +
5 instances * 7 hrs * $0.25 = $8.75
Total = $21.75
Time Savings: 50% Cost Savings: ~22%

196. AWS is a set of infrastructure building blocks

197. Amazon Web Services is all about
FLEXIBILITY

198. « Want to increase innovation?
Lower the cost of failure »
Joi Ito

199. AWS lowers the cost of
innovation
Testing a new idea is cheap

200. Resources

201. Architecture Center
aws.amazon.com/architecture

203. Articles & Tutorials
aws.amazon.com/articles

205. Videos & Webinars
aws.amazon.com/resources/webinars

207. FREE TIER!
aws.amazon.com/free

209. Plat_forms web development contest
Ulrich Stärk, Freie Universität Berlin – Plat_forms web development contest:
Der Wettbewerb wird am 03. und 04.04.2012 in den Räumen des Henry-Ford-
Baus der Freien Universität Berlin stattfinden;
der 02.04. wird als Anreise- und Aufbautag genutzt: https://www.plat-
forms.org/
Plat_Forms ist ein Experiment um die Eigenschaften verschiedener
Webentwicklungsplattformen (Java, .NET, PHP, Ruby, Perl, usw.)
wissenschaftlich zu untersuchen, bei dem Teams professioneller
Softwareentwickler gegeneinander antreten

210. Q &A

211. THANK YOU
aws.amazon.com