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How to Scale Your Next Idea on
AWS: A Love Story
Jinesh Varia
jvaria@amazon.com
Follow me: @jinman
linkedin.com/in/jinman
Story
Story of Scalability
Thursdate.com
ThursDate.com
Magical Elastic Dating Every Thursday

An ephemeral website on On-Demand Cloud Infrastructure

Goes Live: Thursday 4:00 PM
Shuts Down: Thursday 7:00 PM

“Black Friday Effect”
Repeats every Thursday of the Week
www.myjavawebsite.com
Elastic IP

Apache
Tomcat

Amazon EC2
Instance

MySQL

Availability Zone #1

Backups

Amazon S3
Bucket
Pattern #1: Design for failure and nothing will fail
www.myjavawebsite.com
Elastic IP

Apache
Tomcat

Amazon EC2
Instance

MySQL

Availability Zone #1

Backups

Amazon S3
Bucket
www.myjavawebsite.com

Elastic IP

Route53
Hosted Zone

Apache
Logs
Static Data

Tomcat

MySQL

Amazon EC2
Instance

Root

Amazon S3
Bucket

Backups

Data
Snapshots

Amazon EBS Volume
Availability Zone #1
Pattern #2: Edge cache static content
www.myjavawebsite.com

Elastic IP

Route53
Hosted Zone

Apache
Logs
Static Data

Tomcat

MySQL

Amazon EC2
Instance

Root

Amazon S3
Bucket

Backups

Data
Snapshots

Amazon EBS Volume
Availability Zone #1
media.myjavawebsite.com
(Static and Streaming data)

www.myjavawebsite.com
(Dynamic data)

Elastic IP

Route53
Hosted Zone

Amazon
CloudFront
Distribution

Apache
Logs
Static Data

Tomcat

MySQL

Amazon EC2
Instance

Root

Amazon S3
Bucket

Backups

Data
Snapshots

Amazon EBS Volume
Availability Zone #1
media.myjavawebsite.com
(Static and Streaming data)

www.myjavawebsite.com
(Dynamic data)

Elastic IP

Route53
Hosted Zone

Amazon
CloudFront
Distribution

Apache
Logs
Static Data

Tomcat

MySQL

Amazon EC2
Instance

Root

Amazon S3
Bucket

Backups

Data
Snapshots

Amazon EBS Volume
Availability Zone #1
www.myjavawebsite.com
(Dynamic data)

Elastic IP

media.myjavawebsite.com
(Static and Streaming data)

Route53
Hosted Zone

Amazon
CloudFront
Distribution

Apache
Tomcat

Logs
Static Data

Amazon S3
Bucket

Amazon EC2
Instance

MySQL

Amazon RDS DB Instance
Availability Zone #1

Backups
www.myjavawebsite.com

staging.myjavawebsite.com

Elastic IP
183.2.3.1

Tip:
Treat Cloud
Resources as
Fungible
Resources

Dynamic IP
172.3.1.4

App v1.1

App v1.2

Apache

Apache

Tomcat

Tomcat

Production EC2
Instance

Production EC2
Staging EC2
Instance

MySQL

Amazon RDS

Availability Zone #1
www.myjavawebsite.com
(Dynamic data)

Elastic IP

media.myjavawebsite.com
(Static and Streaming data)

Route53
Hosted Zone

Amazon
CloudFront
Distribution

Apache
Tomcat

Logs
Static Data

Amazon S3
Bucket

Amazon EC2
Instance

MySQL
Backups

Amazon RDS DB Instance
Availability Zone #1
Slashdot Effect
Pattern #3: Implement Elasticity
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache
Amazon Machine
Image
Tomcat

Logs
Static Data

Amazon S3
Bucket

Amazon EC2
Instance
Auto Scaling Group

MySQL
Backups

Amazon RDS DB Instance
Availability Zone #1
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache
Amazon Machine
Image

Tomcat

Logs
Static Data

Amazon S3
Bucket

Amazon EC2
Instance
Auto Scaling Group

MySQL
Backups

Amazon RDS DB Instance
Availability Zone #1
media.myjavawebsite.com
(Static and Streaming data)

www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

Amazon
CloudFront
Distribution

Amazon ELB

Apache

Apache

Tomcat

Tomcat

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group : Web Tier

Amazon EC2
Instances
MySQL

Amazon RDS DB Instance
Availability Zone #1

Backups
DB?
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache
Tomcat

Apache
Tomcat

Logs
Static Data

Auto Scaling Group : Web Tier

Amazon RDS DB
Instance

Availability Zone #1

Backups

Amazon S3
Bucket
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache
Amazon DynamoDB
(all Key Value data)

Tomcat

Apache
Tomcat

Logs
Static Data

Auto Scaling Group : Web Tier

Amazon RDS DB
Instance

Availability Zone #1

Backups

Amazon S3
Bucket
Pattern #4: Leverage Multiple Availability Zones
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache
Tomcat

Apache
Tomcat

Logs
Static Data

Auto Scaling Group : Web Tier

Amazon RDS DB
Instance
Availability Zone #1
Backups

Availability Zone #2

RDS Standby
Slave

Amazon S3
Bucket
Pattern #5:
Isolate read and write traffic
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache

Apache

Tomcat

Tomcat

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group : Web Tier

Async
RDS Read
Replicas

Availability Zone #1
Backups

Availability Zone #2

RDS Standby
Slave
Pattern #6: Cache is King; Cache as much as possible
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache

Apache

Tomcat

Tomcat

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group : Web Tier

Async
RDS Read
Replicas

Availability Zone #1
Backups

Availability Zone #2

RDS Standby
Slave
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache

Apache

Tomcat

Tomcat

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group : Web Tier

ElastiCache
Nodes

Async
RDS Read
Availability Zone #1
Replicas
Backups

Availability Zone #2

RDS Standby
Slave
Pattern #7: Leverage application services to increase
your productivity and scale your app
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache

Apache

Tomcat

Tomcat

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group : Web Tier

ElastiCache
Async
RDS Read
Replica

Availability Zone #1
Backups

Availability Zone #2

RDS Standby
Slave
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache
Tomcat

Amazon CloudSearch
(Index all your data)

Apache
Tomcat

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group : Web Tier

Amazon SNS
(notifications)

Amazon CloudWatch
(Monitoring)

ElastiCache
Async

Amazon Simple Email Service
(Send email)

RDS Read
Replica

Availability Zone #1
Backups

Availability Zone #2

RDS Standby
Slave
Tip: Loose coupling for other parts of the application
(For example, Image Processing)
Loose coupling sets you free
Use Amazon SQS as Buffers
Tight Coupling

Controller A

Q

Loose Coupling
using Queues

Controller B

Q
Controller A

Controller C

Q
Controller B

Controller C
CloudFront
Download
Distribution

RRS S3
Bucket to
Serve
content to
CloudFront
S3 Bucket
For Ingest

Instances
User

SQS Queue
Size for Thumbnail

Auto scaling
Group

Instances

SNS Topic

Tip:
Use Queues as
Buffer

SQS Queue
Size Image for
Mobile

SQS Queue
Size Image for Web

Auto scaling
Group

Instances
Auto scaling
Group

S3 Bucket
For originals
CloudFront
Download
Distribution

RRS S3
Bucket to
Serve
content to
CloudFront
S3 Bucket
For Ingest

Instances
User
Auto scaling
Group

Instances

Tip:
Automate by
using
workflows

Auto scaling
Group

SWF

Instances

Instance running
decider

Auto scaling
Group

S3 Bucket
For originals
Pattern #8: Automate Your software development
lifecycle (Continuous Integration + Deployment)
Tip:
Bootstrap your
EC2 Instances

www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon
CloudFront
Distribution

Amazon ELB

Apache
Amazon Machine
Image

Tomcat
Amazon
EC2
Instance

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group

MySQL
Backups

Amazon RDS DB Instance
CloudFormation
Template

Git

Build
Instance

Bootstrap
Scripts

Artifact
Bucket

Continuous Integration

Availability Zone #1
Apache

Your Code
Your Code

Fetch on boot

Fetch on boot

Tomcat
Apache

Struts
Your Code

Struts
Log4J
Spring

Tomcat

Struts

Fetch on boot

Amazon S3

Apache
Struts
Tomcat
Log4J
Hibernate
Spring

Amazon S3

scripts
Chef/puppet

Your Code

Log4J
Spring

Apache
A
p
a
c
h
e

Log4J
A
p
a
c
h
e
T
o
m
c
a
tS
t
r
u
t
s
Y
o
u
r

Spring

Hibernate

Hibernate

C
L
o
d
g
e
4
J
S
p
r
i
n
g
H
i
b
e
r
n
J
a
E
t
E
e
L
i
n
u
x

A
p
a
c
h
e
T
o
m
c
a
tS
t
r
u
t
s
Y
o
u
r
C
L
o
d
g
e
4
J
S
p
r
i
n
g
H
i
b
e
r
n
J
a
E
t
E
e
L
i
n
u
x

T
o
m
c
a
t

Tomcat
A
p
a
c
h
e
T
o
m
c
a
tS
t
r
u
t
s
Y
o
u
r
C
L
o
d
g
e
4
J
S
p
r
i
n
g
H
i
b
e
r
n
J
a
E
t
E
e
L
i
n
u
x

JEE

A
p
a
c
h
e
T
o
m
c
a
tS
t
r
u
t
s
Y
o
u
r
C
L
o
d
g
e
4
J
S
p
r
i
n
g
H
i
b
e
r
n
J
a
E
t
E
e

H
i
b
e
r
n
a
J
t
E
e
E

L
i
n
u
x

Hibernate

A
p
a
c
h
e
T
o
m
c
a
t
H
i
b
e
r
n
a
J
t
E
e
E

L
i
n
u
x

A
p
a
c
h
e
T
o
m
c
a
t
H
i
b
e
r
n
a
J
t
E
e
E

L
i
n
u
x

CHEF
Puppet
JEE

JEE

Linux

JEE

Linux

JEE

L
i
n
u
x

Linux
Linux

JEE
Linux
Java App Stack

Linux

Amazon EC2

Amazon EC2
Java AMI

Java AMI

Inventory of AMIs

Frozen Pizza Model

Golden AMI and
Fetch binaries on boot

Take N Bake Pizza Model

Amazon EC2
JeOS AMI

JeOS AMI and library of recipes
(install scripts)

Made to order Pizza Model
Cloud-Powered Software Development Lifecycle

Dev
All in one instance

Test/QA
2-tier app
with small DB

Staging
2-tier app with
production data

AWS CloudFormation + Chef (or Puppet)

Prod
2-tier app with
production data
Multi-AZ and HA
"80% of time we are wrong what
the customers wants"
Data-driven
A/B Testing

A

B

Control

Treatment
Blue Green Deployments
High Error Rate
Monitoring

Load Balancing

(CloudWatch)

(ELB)

v1.1

v1.1

v1.2

v1.2

v1.1

v1.1

v1.2

v1.2

Web Server Fleet
(Amazon EC2)

Database Fleet
(RDS or DB on EC2)
Auto Scaling

Auto Scaling Group (Min, Max # of instances, Availability Zones .. )
Health Check (Maintain Min # active…)
Launch Configuration (AMIID, Instance type, UserData, Security Groups..)
Scaling Trigger (Metric, Upper Threshold, Lower Threshold, Time interval …)
Types of Scaling (Scale by Schedule, Scale by Policy)
Alarm (Notification Email, SMS, SQS, HTTP)
Availability Zones and Regions
Load Balancing
(ELB)

Auto scaling
v1.1

v1.1

v1.2

v1.2

v1.1

v1.1

v1.2

v1.2

“Auto scaling”
Web Server Fleet
(Amazon EC2)

Database Fleet
(RDS or DB on EC2)

Max instances
Min instances
Scaling Trigger
Custom Metrics
Upper Threshold
Lower Threshold
Increment by
Deploy != Product Launch
Feature = ON
request
Load Balancing
(ELB)

Happy
Path v1.1

New feature
Code Path v1.2

v1.1
v1.1

v1.1
v1.1

v1.2

v1.1
v1.1

v1.1
v1.1

v1.2

Web Server Fleet
(Amazon EC2)

Database Fleet
(RDS or DB on EC2)
Dialing up

A

B

Control

Treatment
Load Balancing
(ELB)

99%

1%

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

Web Server Fleet
(Amazon EC2)

…..

Database Fleet
(RDS or DB on EC2)

A/B Testing
Service
Load Balancing
(ELB)

90%

10%

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

Web Server Fleet
(Amazon EC2)

…..

Database Fleet
(RDS or DB on EC2)

A/B Testing
Service
Load Balancing
(ELB)

70%

30%

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

Web Server Fleet
(Amazon EC2)

…..

Database Fleet
(RDS or DB on EC2)

A/B Testing
Service
Load Balancing
(ELB)

70%

30%

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

Web Server Fleet
(Amazon EC2)

…..

Database Fleet
(RDS or DB on EC2)

A/B Testing
Service

v1.2

High Error Rate
v1.2

Monitoring
(CloudWatch)
Load Balancing
(ELB)

Rollback

90%

10%

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

Web Server Fleet
(Amazon EC2)

…..

Database Fleet
(RDS or DB on EC2)

A/B Testing
Service

Dev, Test
Load Balancing
(ELB)

70%

30%

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

Web Server Fleet
(Amazon EC2)

…..

Database Fleet
(RDS or DB on EC2)

A/B Testing
Service
Load Balancing
(ELB)

50%

50%

A/B Testing
Service

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

Web Server Fleet
(Amazon EC2)

…..

Database Fleet
(RDS or DB on EC2)
Load Balancing
(ELB)

30%

70%

A/B Testing
Service

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

v1.1

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

Web Server Fleet
(Amazon EC2)

…..

Database Fleet
(RDS or DB on EC2)
Load Balancing
(ELB)

5%

95%

A/B Testing
Service

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

v1.2

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

v1.2

v1.1

v1.1

v1.2

v1.2

v1.2

v1.2

v1.2

v1.2

v1.2

v1.2

v1.2

v1.2

v1.2

v1.2

Web Server Fleet
(Amazon EC2)

v1.1

…..

Database Fleet
(RDS or DB on EC2)
Data-driven
HOST LEVEL
METRICS

AGGREGATE
LEVEL
METRICS

LOG ANALYSIS

EXTERNAL
SITE PERFORMANCE
Amazon S3

Via Flume/Fluentd
(Log Aggregator)

Logs from
EC2
Instances

Amazon S3

Task
Node

Amazon Elastic
MapReduce
Code/
Scripts

Mapper
Reducer
HiveQL
Pig Latin
Cascading

Amazon DynamoDB/RDS
Name
Node

Task
Node

Runs multiple
JobFlow Steps

Core
Node

HiveQL
Pig Latin

Query

Tip:
Log analysis
EMR Clusters

Core
Node

HDFS

Amazon Elastic MapReduce
Hadoop Cluster

JDBC/ODBC

BI Apps
Tip:
Pick the right “Big Data Stack” for your data

Client

Ingest
Mobile Client

•Kinesis
•Flume
•Kafka

Store
•S3
•DynamoDB
•RDS

Process
•Hadoop/EMR
•Redshift
•Spark/EMR

Visualize
•Tableau
•Datameer
•D3

(“Thing”)
Sensor

Questions:
Hot data vs. Cold data
Size of data & Speed of data ingest
Adhoc query (reports) vs. frequent queries (dashboard)
Batch vs. Stream
Low latency responses (ms) vs. high latency responses (Hours)
Cost tradeoffs

Insights
Reports
$$
Pattern #9:
Build cost-aware architectures;
Optimize for cost and see savings as early as your next month’s bill
On-demand
Instances
• Pay as you go

• Zero commitment

Reserved
Instances
• One time low
upfront fee +
discounted hourly
costs
• Upto 71% savings
over On-Demand

Spot
Instances
• Requested Bid
Price and Pay as
you go
• Price change
every hour based
on unused EC2
capacity

Dedicated Instances
• Standard and
Reserved
• Multi-Tenant
Single Customer
• Ideal for
compliance and
regulatory
workloads

Billing Options
Mix and Match Instances
12

10

On-Demand
8

6

Light RI

Light RI

Light RI

Light RI

4

2

Heavy Utilization Reserved Instances
0
1

2

3

4

5

6

7

8

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28
Upload large
datasets or log
files directly

Data
Source

Amazon S3
Amazon S3

Task
Node

Amazon Elastic
MapReduce
Code/
Scripts

Mapper
Reducer
HiveQL
Pig Latin
Cascading

Amazon DynamoDB/RDS
Name
Node

Task
Node

Runs multiple
JobFlow Steps

Core
Node

HiveQL
Pig Latin

Query

Adhoc EMR
Clusters
+
Task Nodes
on Spot

Core
Node

HDFS

Amazon Elastic MapReduce
Hadoop Cluster

JDBC/ODBC

BI Apps
ThursDate.com
Magical Elastic Dating Every Thursday

“Not about the past”

Be whatever you want to be:
Doctors
Nerds/Geeks
Philosophers
Mac fans
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon ELB
Amazon
CloudFront
Distribution

Auto Scaling Group
Web Tier

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group
App Tier

Backups

Availability Zone #2
RDS Standby
Slave
Availability Zone #3
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon ELB

Amazon
CloudFront
Distribution

Auto Scaling Group
Web Tier

Auto Scaling Group
Web Tier

Auto Scaling Group
App Tier

Auto Scaling Group
App Tier

Logs
Static Data

RDS Standby
Slave
Availability Zone #1

Availability Zone #2
Availability Zone #3

Amazon S3
Bucket

Backups
Pattern #10: Harden security at every stage
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone

media.myjavawebsite.com
(Static and Streaming data)

Amazon ELB
Amazon
CloudFront
Distribution

Auto Scaling Group
Web Tier

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group
App Tier

Backups

Availability Zone #2
RDS Standby
Slave
Availability Zone #3
www.myjavawebsite.com
(Dynamic data)
Route53
Hosted Zone
#Permit HTTP(S) access to Web Layer from
the Entire Internet
ec2auth Web -p 80,443 -s 0.0.0.0/0

Amazon ELB
Amazon
CloudFront
Distribution

Auto Scaling Group

#Permit Web Layer access to App Layer
ec2auth App -p 8000 –o Web

# Permit App Layer access to DB
ec2auth DB -p 3209 –o App

# Permit admin access SSH to all three layers
# First allow connection from office to Web
tier, and from there to the other layers
ec2auth Web -p 22 -s <for example, network
block of your office>
ec2auth App -p 22 -o Web
ec2auth DB -p 22 -o Web

media.myjavawebsite.com
(Static and Streaming data)

Web Security Group
Web Tier

Logs
Static Data

Amazon S3
Bucket

Auto Scaling Group
App Tier

App Security Group

Backups

Availability Zone #2
DB Security Group

RDS Standby
Slave
Availability Zone #3
Amazon VPC Subnet
Implement security best practices at
every layer









Protect Your AWS Account
Control Internal Access to AWS Resources
Limit External Access to Your AWS Cloud
Protect Data in Transit and at Rest
Secure your data assets
Secure your compute assets (OS, Instance, App)
Backup and easily recover
Keep Track of Your Cloud Resources (Monitoring)

http://bit.ly/aws-security-best-practices-new
Pattern: #11: Go Global Quickly (with single API)
US West Traffic

Web
Web
App
Web
App
App

Web
Web
App
Web
App
App

US East Traffic

Web
Web
App
Web
App
App

Europe Traffic

Web
Web
App
Web
App
App

Web
Web
App
Web
App
App

Web
Web
App
Web
App
App

Asia Traffic

Web
Web
App
Web
App
App

Web
Web
App
Web
App
App

Auto Scaling group : Web
App Tier

Auto Scaling group : Web
App Tier

Auto Scaling group : Web
App Tier

Auto Scaling group : Web
App Tier

RDS
Master

RDS
Master

RDS
Master

RDS
Master

US-West
US-West-1b

RDS
Multi-AZ

US-East
US-East-1b

RDS
Multi-AZ

EU-West
EU-West-1b

Software-based Data Replicator

RDS
Multi-AZ

AP-SOUTHEAST
AP-SOUTHEAST-1b

RDS
Multi-AZ
Pattern #1: Design for failure and nothing will fail
Pattern #2: Edge cache static content
Pattern #3: Implement Elasticity
Pattern #4: Leverage Multiple Availability Zones
Pattern #5: Isolate read and write traffic; Isolate static and dynamic traffic
Pattern #6: Cache as much as possible; Cache is King
Pattern #7: Leverage app services to increase your productivity and scale your app
Pattern #8: Automate Your software development lifecycle
Pattern #9: Optimize for Cost and See Savings as early as your Next Month’s Bill
Pattern #10: Harden security at every stage
Pattern #11: Go global quickly (with single API)
Powerful

Highly scalable, Highly available, Highly

responsive, Fault-tolerant, Cost-effective, globally-deployed

Web application
Andy found “cloud” mate – his soul mate
And he lives happily ever after….
First love is still “the cloud”
Thank you!
Jinesh Varia
jvaria@amazon.com Twitter:@jinman

This slide deck is available at
http://slideshare.net/amazonwebservices
http://aws.amazon.com/whitepapers

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Introduction to Amazon Web Services - How to Scale your Next Idea on AWS : A Love Story - Jinesh Varia (Updated Jan 2014)

Notas do Editor

  1. Single InstanceWeb Application Architecture in 1 AZ
  2. Single InstanceWeb Application Architecture in 1 AZ
  3. Single InstanceWeb Application Architecture in 1 AZ
  4. Single InstanceWeb Application Architecture in 1 AZ
  5. Single InstanceWeb Application Architecture in 1 AZ
  6. Single InstanceWeb Application Architecture in 1 AZ
  7. Single InstanceWeb Application Architecture in 1 AZ
  8. Using Elastic Ips for upgrade process
  9. Single InstanceWeb Application Architecture in 1 AZ
  10. Single InstanceWeb Application Architecture in 1 AZ
  11. Single InstanceWeb Application Architecture in 1 AZ
  12. Single InstanceWeb Application Architecture in 1 AZ
  13. Single InstanceWeb Application Architecture in 1 AZ
  14. Single InstanceWeb Application Architecture in 1 AZ
  15. Single InstanceWeb Application Architecture in 1 AZ
  16. Single InstanceWeb Application Architecture in 1 AZ
  17. Single InstanceWeb Application Architecture in 1 AZ
  18. Single InstanceWeb Application Architecture in 1 AZ
  19. Single InstanceWeb Application Architecture in 1 AZ
  20. Single InstanceWeb Application Architecture in 1 AZ
  21. Single InstanceWeb Application Architecture in 1 AZ
  22. Goal is to get instant feedback from your users and how your application behaves when real load. A/B testing is great. Control and Treatment http://20bits.com/articles/an-introduction-to-ab-testing/Prove success of interface changesProve interest in new features
  23. So how can you do deployments and quickly deploy without any downtime
  24. One simple technique is to do blue green deloyments. Green is your current deployment, you de
  25. BG + Autoscaling = Cost savings + Scaling up
  26. BG + Darklaunches in which you deploy both the versions side by side but customers does not know about it. Two separate code paths but only one activated. The other one is activated by a feature flag. This can be your beta test where you explicitly turn
  27. Goal is to get instant feedback from your users and how your application behaves when real load. A/B testing is great. Control and Treatment http://20bits.com/articles/an-introduction-to-ab-testing/Prove success of interface changesProve interest in new features
  28. What if you have 1000s of nodes. The blue green deployments works well but you may not want to spin up additional 100% capacity. So then you can gradually spin up in small increments of 10% so you only pay for additional 10% of your nodes. Plus you learn more about your customer behavior too.By routing only a small of users to your newly code deployed code base. Start small with 1% - A/B testing is randomizes the traffic and collect feedback on what’s working and what is not working. With a simple configuration change Autoscaling on the other hand scales. You don’t want to send all your traffic to new nodes just yet.Note: you have tested all your application, brought additional capacity before you route real traffic.
  29. Slowly ramp of traffic by simply changing the configuration file in a/b testing and see autoscaling kicking off additional instances as needed. Note here you are not disrupting user behavior because they see only that version that they hit.
  30. Slowly rampup traffic you are know whether the feature is working for your customer and you are learning more about customer.
  31. Pager beeping. Something went wrong. Time to do rollback. Rollbacks are easy…
  32. Change the config file route all the traffic back to your previous hosts….Test what went wrong…fix….deploy new instances using the same process
  33. Start ramping up again…..
  34. You are gradually deploying new software, using the dynamism of the cloud with zero downtime. And that’s cool.
  35. Autoscaling handles all the capacity planning for you.
  36. Batch Processing Architecture using Amazon Elastic MapReduce
  37. puts focus on the date rather than the individual. Users propose fun activities. Other users can send them messages if they like their ideas.
  38. Batch Processing Architecture using Amazon Elastic MapReduce
  39. Single InstanceWeb Application Architecture in 1 AZ
  40. Single InstanceWeb Application Architecture in 1 AZ
  41. Single InstanceWeb Application Architecture in 1 AZ
  42. Single InstanceWeb Application Architecture in 1 AZ
  43. Cloud Computing Rocks