Session 3, Presentation 5 from the AWS Sydney Summit

1. Glenn Gore
Building Web-Scale Applications with AWS
Manager Solutions Architects

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
– Failures do happen
• Architect with Security
– Security must happen

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

5. Regions and Storage
Where and What

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

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

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

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

10. Storage Types
Database
• Readily queryable
• Consistency/performance options
SQS
• Logic built-in
• 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
Controller A Controller B Controller C
Controller A Controller B Controller C
Q Q Q
Tight Coupling
Use Amazon SQS as Buffers
Loose Coupling

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

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
Memory-resident session manager
Session database
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
Session State
Service
Not Here
Here
State must reside OUTSIDE
the scope of the elements you
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. AWS Account
Credentials
IAM User
Temporary
Security
Credentials
The IAM Hierarchy of Permissions
Permissions Example
Unrestricted access to all enabled
services and resources
Action: *
Effect: Allow
Resource: *
(implicit)
Access restricted by Group and
User policies
Action: [‘s3:*’, ‘sts:Get*’]
Effect: Allow
Resource: *
Access restricted by generating
identity and further by policies
used to generate token
Action: [ ‘s3:Get*’ ]
Effect: Allow
Resource:
‘arn:aws:s3:::userbucket/*’

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

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

28. Horizontal Scaling – Fully Managed
DynamoDB
• Provisioned throughput NoSQL database
• Fast, predictable performance
• Fully distributed, fault tolerant architecture
• Considerations for non-uniform data
Feature Details
Provisioned
throughput
Dial up or down provisioned read/write
capacity.
Predictable
performance
Average single digit millisecond latencies
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
MapReduce
Integrates with Elastic MapReduce for
complex analytics on large datasets.

29. Petabyte-Scale Data Warehousing
Feature Details
Optimized for
Data
Warehousing
Redshift uses a variety of innovations to
obtain very high query performance on
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
MapReduce
Integrates with ERM via Data Pipeline.

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

31. Building Web-Scale Applications with AWS