AWS provides a platform that is ideally suited for deploying highly available and reliable systems that can scale with a minimal amount of human interaction.  This talk describes a set of architectural patterns that support highly available services that are also scalable, low cost, low latency and allow for agile  development practices.   We walk through the various architectural decisions taken for each tier and explain our choices for appropriate AWS services and building blocks to ensure the security, scale, availability and reliability of the application.

1. Building Web-Scale Applications with AWS
Dan Cuddeford and Matthew Trescot
Enterprise Solutions Architect and Solutions Architect

2. I am Barack Obama, Ask me anything
Reddit Needed to Scale for a special guest
• 2,987,307 pageviews on the day of the IAmA
• President Obama’s user page received 428,004
pageviews on the day of the IAMA
• Added 60 dedicated instance to handle the increased
load
• At peek transfering 48 MB/s to the internet

3. While You Scale
• Architect for Failure • Architect with Security
– Failures do happen – Security must happen

4. Why Is Scale Important?
AWS
Actual demand
Actual demand
Customer
Dissatisfaction
Self
Hosting
Waste
Predicted Demand
Rigid Elastic

5. Regions and Storage
Where and What

6. Regions
US-WEST (Oregon)
EU-WEST (Ireland)
AWS GovCloud (US)
ASIA PAC (Tokyo)
US-EAST (Virginia)
ASIA PAC (Sydney)
US-WEST (N. California)
SOUTH AMERICA (Sao Paulo)
ASIA PAC
(Singapore)

7. Availability Zones
US-WEST (Oregon))
EU-WEST (Ireland)
AWS GovCloud (US)
ASIA PAC (Tokyo)
US-EAST (Virginia)
ASIA PAC (Sydney)
US-WEST (N. California)
SOUTH AMERICA (Sao Paulo)
ASIA PAC
(Singapore)

8. Storage Types
Ephemeral Storage Elastic Block Storage
• (Almost) every instance has them • 1GB to 1TB
• Fast • Snapshot-able
• Cheap • You choose the IOPS
• Volatile • Good for random IO

9. Storage Types
S3 Glacier
• (Almost) infinitely durable • (Almost) infinitely durable
• Infinitely scalable • Infinitely scalable
• CloudFront integration • Cheapest

10. Storage Types
Database SQS
• Readily queryable • Logic built-in
• Consistency/performance options • Infinitely scalable
• Good for small blobs and write/read
once

11. Application Scaling
Wide and Proud

12. Loose coupling sets you free!
• The looser they're coupled, the bigger they scale
– Independent components
– Design everything as a black box
– Decouple interactions
– Load-balance clusters
Use Amazon SQS as Buffers
Tight Coupling Controller A Controller B Controller C
Q Q Q
Loose Coupling
Controller A Controller B Controller C

13. Allows for Parallel Processing and Failure
• Fan out
• Use varied instance types
• Use varied billing models

14. Allows for Parallel Processing and Failure

15. Lets you Auto Scale
Trigger auto-
scaling policy
as-create-auto-scaling-group MyGroup
--launch-configuration MyConfig
--availability-zones eu-west-1a
--min-size 4
--max-size 200
Auto Scaling
Automatic resizing of compute clusters based on demand
Feature Details
Control Define minimum and maximum instance pool
sizes and when scaling and cool down occurs.
Integrated to Amazon Use metrics gathered by CloudWatch to drive
CloudWatch scaling.
Instance types Run Auto Scaling for On-Demand and Spot
Instances. Compatible with VPC.

16. …and Spread the Load
Elastic Load Balancing
• Create highly scalable applications
• Distribute load across EC2 instances
in multiple availability zones
Feature Details
Available Load balance across instances in multiple
Availability Zones
Health checks Automatically checks health of instances and
takes them in or out of service
Session stickiness Route requests to the same instance
Secure sockets layer Supports SSL offload from web and application
servers with flexible cipher support
Monitoring Publishes metrics to CloudWatch

17. But usually some state has to reside somewhere
Cookies in browser
Session database
Memory-resident session manager
Framework-provided session handler

18. So this store of state needs to be…
Performant
Scalable
Reliable

19. Where should session state reside?
Trigger auto-
scaling policy
Not Here
Here Session State State must reside OUTSIDE
the scope of the elements you
Service wish to scale

20. And what do I build it on?
The state service itself must
be well architected

21. IAM Temporary Security Credentials
• Use Cases
 Identity Federation to AWS APIs
 Mobile and browser-based applications
 Consumer applications with unlimited users
• Scales to millions of users
– No need to create an IAM identity for every user

22. The IAM Hierarchy of Permissions
Permissions Example
Unrestricted access to all enabled Action: *
AWS Account services and resources Effect: Allow
Credentials Resource: *
(implicit)
Access restricted by Group and Action: [‘s3:*’, ‘sts:Get*’]
Effect: Allow
IAM User User policies Resource: *
Temporary Access restricted by generating Action: [ ‘s3:Get*’ ]
Security Effect: Allow
identity and further by policies Resource:
Credentials used to generate token ‘arn:aws:s3:::userbucket/*’

23. AWS Application Management Solutions
Higher-level Services Do it yourself
Elastic Beanstalk OpsWorks CloudFormation EC2
Convenience Control

24. Data Tier Scaling
The bane of the Architect’s existence

25. Vertical Scaling
“We’re gonna need a bigger box”
• Simplest approach
• Can now leverage PIOPs
• High I/O instances
• Easy to change instance sizes
• Will hit an endpoint eventually
hi1.4xlarge
m2.4xlarge
m1.small

26. Master/Slave Horizontal Scaling
• Reasonably simple to adapt to
• Can now leverage PIOPs
• Easy to change instances sizes
• Will hit an endpoint eventually

27. • More complex at the application layer
Sharded Horizontal Scaling • ORM support can help
• No practical limit on scalability
• Operation complexity/sophistication
• Shard by function or key space
D A
• RDBMS or NoSQL
Hash Ring
C B

28. Horizontal Scaling – Fully Managed
DynamoDB Feature Details
• Provisioned throughput NoSQL database Provisioned Dial up or down provisioned read/write
• Fast, predictable performance throughput capacity.
• Fully distributed, fault tolerant architecture Predictable Average single digit millisecond latencies
• Considerations for non-uniform data performance from SSD-backed infrastructure.
Strong consistency Be sure you are reading the most up to
date values.
Fault tolerant Data replicated across Availability Zones.
Monitoring Integrated to CloudWatch.
Secure Integrates with AWS Identity and Access
Management (IAM).
Elastic Integrates with Elastic MapReduce for
MapReduce complex analytics on large datasets.

29. Petabyte-Scale Data Warehousing
Feature Details
Optimized for Redshift uses a variety of innovations to
Data obtain very high query performance on
Warehousing datasets ranging in size from hundreds
of gigabytes to a petabyte or more.
Scalable Easily scale the number of nodes in your
data warehouse up or down as your
performance or capacity needs change
Fault tolerant Data replicated across Availability
Zones.
Monitoring Integrated to CloudWatch.
Secure Encrypt data in transit and at rest. Can
also be run in VPC to isolate your data
warehouse cluster.
S3 intergration Loads data in parallel to each node from
S3.
Elastic Integrates with ERM via Data Pipeline.
MapReduce

30. Summary
• Use these techniques (and many, many others) situationally
• Awareness of the options is the first step to good design
• Scaling is the ability to move the bottlenecks around to the
least expensive part of the architecture
• AWS makes this easier – so your application is not a victim of
its own success