This is the presentation from the session at Codebase on June 17. Building Scalable Web Applications on AWS. Including content on why you might chose to use AWS for scalable web applications, a rule Book for buidling scalable web application on AWS, common patterns for web applications and where to go next to learn more about AWS.

1. Scalable Web Applications on AWS
Ian Massingham - Technical Evangelist
17 June 2014

2. A popular use-case for AWS services
Applications with growing, variable or cyclical demand fit AWS well
Exercise elasticity and automation to real advantage
AWS services allow you to accelerate application development
Scalable Web Applications

3. Why use AWS for scalable web applictions?
Rule Book for scalable web application on AWS
Common patterns for web applications
Where to go next to learn more
Agenda

4. Why AWS for scalable
web applications?

5. What your users want…
High & consistent
performance
Lots of new
features all of the
time
Always on,
accessible
anywhere
Personalized and
rich applications

6. • reddit is a San Francisco, CA company that
provides reddit.com, a social news and
entertainment website where users can
submit and rank ideas, images, and links
• reddit originally operated reddit.com on
physical servers, but after the number of
users quadrupled in 18 months, the
company realized it couldn’t scale with an
on-premises environment
• By migrating to AWS, reddit can scale to
manage 4 billion page views per month and
run its website with only 20 employees
With AWS, reddit scales its social news site to handle 4 billion page
views per month with only 20 employees
Find out more here : aws.amazon.com/de/solutions/case-studies/reddit/

7. • One of the world's leading online travel
companies, providing leisure and business
travel to customers worldwide
• Expedia needed a global infrastructure to
support its commitment to create a great
experience for customers worldwide
• Using AWS, Expedia created a global
infrastructure for its critical applications while
reducing network latency to under 50
milliseconds and enabling a 230% CPU
consumption efficiency for data processing
Expedia Uses AWS to Run Critical, High Volume Applications on
a Global Infrastructure
Find out more here : aws.amazon.com/solutions/case-studies/expedia/

8. Not excess capacity!
Startups on AWS
Find out more at : aws.amazon.com/solutions/case-studies

9. Rule Book for Scalable Web
Applications on AWS

10. Rule 2: Service requests as fast as possible
Rule 1: Service all web requests
Rule 3: Handle requests at any scale
Rule 4: Simplify architecture with services
Rule 5: Automate operational management
Rule 6: Leverage unique cloud properties

11. DNS Application Data
Rule 1: Service all web requests

12. DNS Application DataRequest
Rule 1: Service all web requests

13. DNS Application DataRequest
Rule 1: Service all web requests

14. DNS Application DataRequest
…then this is
irrelevant
Clients can’t
resolve you?
Rule 1: Service all web requests

15. DNS Application DataRequest
“100%
Available”
SLA
Rule 1: Service all web requests
Route53
Feature Details
Global Supported from AWS global edge locations for fast and reliable
domain name resolution
Scalable Automatically scales based upon query volumes
Latency based
routing
Supports resolution of endpoints based upon latency, enabling
multi-region application delivery
Integrated Integrates with other AWS services allowing Route 53 to front load
balancers, S3 and EC2
Secure Integrates with IAM giving fine grained control over DNS record
access
http://aws.amazon.com/route53/sla

16. DNS Application DataRequest
Rule 1: Service all web requests
Route53

17. Region
DNS Application DataRequest
Rule 1: Service all web requests
Elastic
Load
Balancer Region
Availability Zone
Availability Zone
Availability Zone
Availability Zone
Route53
Elastic load balancing
Multi-availability zone
Multi-region

18. Region
Rule 1: Service all web requests
DNS Application DataRequest
Elastic
Load
Balancer Region
Availability Zone
Availability Zone
Availability Zone
Availability Zone
Route53

19. Region
Rule 1: Service all web requests
DNS Application DataRequest
Elastic
Load
Balancer
Route53
Region
Availability Zone
Availability Zone
Availability Zone
Availability Zone
Multi-AZ RDS
(Master-
slave)
Inter-region
replication
Read-replicas

20. Rule 2: Service requests as fast as possible
Rule 1: Service all web requests
Rule 3: Handle requests at any scale
Rule 4: Simplify architecture with services
Rule 5: Automate operational management
Rule 6: Leverage unique cloud properties

21. Rule 2: Service requests as fast as possible

22. Rule 2: Service requests as fast as possible
a) Choose the fastest route
Region
A
Route53
Region
B
Request

23. Rule 2: Service requests as fast as possible
a) Choose the fastest route
Region
A
Route53
Region
B
16ms 92ms
Request

24. Rule 2: Service requests as fast as possible
a) Choose the fastest route
Region
A
Route53
Region
B
16ms 92ms
Request

25. Rule 2: Service requests as fast as possible
Region
A
Route53
Region
B
16ms
Request
Region A DNS entry
a) Choose the fastest route

26. Rule 2: Service requests as fast as possible
a) Choose the fastest route
b) Offload your application servers
London
Paris
NY
Served from S3
/images/*
3
Served from EC2
*.php
2
Single CNAME
www.mysite.com
1
CloudFront
World-wide content distribution network
Easily distribute content to end users with
low latency, high data transfer speeds, and
no commitments.

27. Without CloudFront
EC2 webservers/app servers loaded by user
requests
Rule 2: Service requests as fast as possible
a) Choose the fastest route
b) Offload your application servers

28. With CloudFront
Load of user requests pushed into
CloudFront, EC2 cluster can scale
down
Offload
Scale
Down
Rule 2: Service requests as fast as possible
a) Choose the fastest route
b) Offload your application servers

29. Rule 2: Service requests as fast as possible
ResponseTime
ServerLoad
ResponseTime
Server
Load
ResponseTime
Server
Load
No CDN CDN for
Static
Content
CDN for
Static &
Dynamic
Content
Offload
Scale
Down
a) Choose the fastest route
b) Offload your application servers

30. Rule 2: Service requests as fast as possible
a) Choose the fastest route
b) Offload your application servers
c) Cache it if you can
ElastiCache
Memcached compatible caching
layer
Serve frequently requested &
slow changing data from scalable
cache clusters
Reduce load on database and
other servers

31. Rule 2: Service requests as fast as possible
a) Choose the fastest route
b) Offload your application servers
c) Cache it if you can
d) Single digit latencies where it matters
Scale
DatabaseQueryPerformance
Desired consistency, predictability

32. Rule 2: Service requests as fast as possible
a) Choose the fastest route
b) Offload your application servers
c) Cache it if you can
d) Single digit latencies where it matters
Scale
DatabaseQueryPerformance
Desired consistency, predictability
Actual
degraded
performance
with scale

33. Rule 2: Service requests as fast as possible
a) Choose the fastest route
b) Offload your application servers
c) Cache it if you can
d) Single digit latencies where it matters
Scale
DatabaseQueryPerformance
Desired consistency, predictability
Actual
degraded
performance
with scale
Management problems
Data sharding
Data caching
Provisioning
Cluster management
Fault management

34. Rule 2: Service requests as fast as possible
a) Choose the fastest route
b) Offload your application servers
c) Cache it if you can
d) Single digit latencies where it matters
Scale
DatabaseQueryPerformance
Dynamo DB Query Performance
Relational
Database
Query
Performance
DynamoDB
Low latency
Large scale
Zero admin
Predictable performance

35. Rule 2: Service requests as fast as possible
a) Choose the fastest route
b) Offload your application servers
c) Cache it if you can
d) Single digit latencies where it matters
Scale
DatabaseQueryPerformance
Dynamo DB Query Performance DynamoDB
Low latency
Large scale
Zero admin
Predictable performance
Average single-digit milliseconds server side
latencies
Runs on solid state drives, and is built to
maintain consistent, fast latencies at any scale

36. Rule 2: Service requests as fast as possible
Rule 1: Service all web requests
Rule 3: Handle requests at any scale
Rule 4: Simplify architecture with services
Rule 5: Automate operational management
Rule 6: Leverage unique cloud properties

37. Rule 3: Handle requests at any scale
a) Scale up
Vertical Scaling
From $0.02/hr
Basic unit of compute capacity
Range of CPU, memory & local disk options
14 Instance types available, from micro through cluster
compute to SSD backed
Scale up with Elastic Compute Cloud (EC2)

38. Rule 3: Handle requests at any scale
a) Scale up
b) Scale out
Trigger
auto-­‐
scaling
policy
aws
autoscaling
create-­‐auto-­‐scaling-­‐group
-­‐-­‐auto-­‐scaling-­‐group-­‐name
MyGroup
-­‐-­‐launch-­‐configuration
MyConfig
-­‐-­‐load-­‐balancer-­‐name
MyELB
-­‐-­‐availability-­‐zones
eu-­‐west-­‐1a
-­‐-­‐min-­‐size
4
-­‐-­‐max-­‐size
200
Auto-scaling
Automatic re-sizing of compute clusters based upon
demand

39. Manually
Send an API call or use CLI to launch/
terminate instances – Only need to
specify capacity change (+/-)
By Schedule
Scale up/down based on date and
time
a) Scale up
b) Scale out
By Policy
Scale in response to changing
conditions, based on user configured
real-time monitoring and alerts
Auto-Rebalance
Instances are automatically launched/
terminated to ensure the application
is balanced across multiple Azs
Rule 3: Handle requests at any scale

40. Manually
Send an API call or use CLI to launch/
terminate instances – Only need to
specify capacity change (+/-)
By Schedule
Scale up/down based on date and
time
Preemptive manual scaling of
capacity
e.g. before a marketing event add 10
more instances
Regular scaling up and down
of instances
e.g. scale from 0 to 2 to process SQS
messages every night or double
capacity on a Friday night
a) Scale up
b) Scale out
By Policy
Scale in response to changing
conditions, based on user configured
real-time monitoring and alerts
Auto-Rebalance
Instances are automatically launched/
terminated to ensure the application
is balanced across multiple Azs
Rule 3: Handle requests at any scale
Dynamic scale based upon
custom metrics
e.g. SQS queue depth, Average CPU
load, ELB latency
Maintain capacity across
availability zones
e.g. Instance availability maintained in
event of AZ becoming unavailable

41. Rule 3: Handle requests at any scale
a) Scale up
b) Scale out
c) Dial it up
Elastic Block Store
Provisioned IOPS up to 1000 per
EBS volume
Predictable performance for
demanding workloads such as
databases
DynamoDB
Provisioned read/write performance
per table
Predictable high performance scaled
via console or API

42. Rule 2: Service requests as fast as possible
Rule 1: Service all web requests
Rule 3: Handle requests at any scale
Rule 4: Simplify architecture with services
Rule 5: Automate operational management
Rule 6: Leverage unique cloud properties

43. Your
Business
70%
On-Premise
Infrastructure
30%
Managing All of the
“Undifferentiated Heavy Lifting”
Rule 4: Simplify architecture with services

44. AWS
Cloud-Based
Infrastructure
Your
Business
More Time to Focus on
Your Business
Configuring Your
Cloud Assets
70%
30%70%
On-Premise
Infrastructure
30%
Managing All of the
“Undifferentiated Heavy Lifting”
Rule 4: Simplify architecture with services

45. Relational Database Service
Database-as-a-Service
No need to install or manage database instances
Scalable and fault tolerant configurations
DynamoDB
Provisioned throughput NoSQL database
Fast, predictable performance
Fully distributed, fault tolerant
architecture
Use RDS for
databases
Use DynamoDB for
high performance
key-value DB
Rule 4: Simplify architecture with services

46. Amazon SQS
Processing task/
processing trigger
Processing
results
Amazon SQS
Reliable, highly scalable, queue
service for storing messages as they
travel between instances
Task A
Task B
(Auto-scaling)
Task C
2
3
1
Simple Workflow
Reliably coordinate processing
steps across applications
Integrate AWS and non-AWS
resources
Manage distributed state in
complex systems
Push inter-process
workflows into the
cloud with SWF
Reliable message
queuing without
additional software
Rule 4: Simplify architecture with services

47. Cloud Search
Elastic search engine based upon
Amazon A9 search engine
Fully managed service with
sophisticated feature set
Scales automatically
Document
Server
Results
Search
Server
Don’t install search
software, use
CloudSearch
Process large
volumes of data cost
effectively with EMR
Elastic MapReduce
Elastic Hadoop cluster
Integrates with S3 & DynamoDB
Leverage Hive & Pig analytics scripts
Integrates with instance types such
as spot
Rule 4: Simplify architecture with services

48. Rule 2: Service requests as fast as possible
Rule 1: Service all web requests
Rule 3: Handle requests at any scale
Rule 4: Simplify architecture with services
Rule 5: Automate operational management
Rule 6: Leverage unique cloud properties

49. Rule 5: Automate operational management
a) Everything is programmable
Compute
Storage
Security
Scaling
Database
Networking
Monitoring
Messaging
Workflow
DNS
Load Balancing
BackupCDN
Access everything via
CLI, API or Console
Achieve the highest levels of
automation sophistication with
ease
Find out more at: aws.amazon.com/developers/getting-started/

50. Rule 5: Automate operational management
a) Everything is programmable
b) Think disposable, one click deployments
Cloud Formation
Automate creation of ‘stacks’ in a repeatable way
Scripting framework for AWS resource creation
Feature Details
Platform support Support for AWS resources from EC2 to IAM
Resource creation Creates AWS resources behind the scenes and
reports on progress
Declarative Specify stacks in JSON format and source
control your environments
Customizable Drive stack creation with paramaters

51. Rule 5: Automate operational management
a) Everything is programmable
b) Think disposable, one click deployments
c) Design for failure, implement self healing
Customize instance startup
Get instances to ask ‘who am I?’
question on startup and be
configured dynamically upon
being answered
Maintain capacity of
instances
Using a minimum pool
size will maintain capacity
in the event of instance
failures
Know what’s going on, take
automated actions
Use CloudWatch standard and
custom metrics to create alarms.
Respond with automated
administration actions
Bootstrapping Auto-scaling Cloud Watch

52. Rule 5: Automate operational management
a) Everything is programmable
b) Think disposable, one click deployments
c) Design for failure, implement self healing

53. Rule 2: Service requests as fast as possible
Rule 1: Service all web requests
Rule 3: Handle requests at any scale
Rule 4: Simplify architecture with services
Rule 5: Automate operational management
Rule 6: Leverage unique cloud properties

54. Rule 6: Leverage unique cloud properties
a) Optimize costs with instance types
EC2 Compute Units
Memory(GB)
0.5
1
2
4
8
16
32
64
128
256
1 2 4 8 16 32 64 128
General'Purpose'
Compute'Op1mized'
GPU'Instances'
Memory'Op1mized'
Storage'Op1mized'
t1.micro'
t1.micro 613 MB
Up to 2 ECUs
(for short bursts)
m1.small 1.7 GB,
1 EC2 Compute Unit
1 virtual core
m1.medium 3.7 GB,
2 EC2 Compute Units
1 virtual core
m1.large 7.5 GB
4 EC2 Compute Units
2 virtual cores
m1.xlarge 15 GB
8 EC2 Compute Units
4 virtual cores
m3.medium 3.7 GB,
3 EC2 Compute Units
1 virtual core
m3.large 7.5 GB
6.5 EC2 Compute Units
2 virtual cores
m3.xlarge 15 GB
13 EC2 Compute Units
4 virtual cores
m3.2xlarge 30 GB
26 EC2 Compute Units
8 virtual cores

55. Rule 6: Leverage unique cloud properties
a) Optimize costs with instance types
EC2 Compute Units
Memory(GB)
0.5
1
2
4
8
16
32
64
128
256
1 2 4 8 16 32 64 128
General'Purpose'
Compute'Op1mized'
GPU'Instances'
Memory'Op1mized'
Storage'Op1mized'
t1.micro'
t1.micro 613 MB
Up to 2 ECUs
(for short bursts)
m1.small 1.7 GB,
1 EC2 Compute Unit
1 virtual core
m1.medium 3.7 GB,
2 EC2 Compute Units
1 virtual core
m1.large 7.5 GB
4 EC2 Compute Units
2 virtual cores
m1.xlarge 15 GB
8 EC2 Compute Units
4 virtual cores
m3.medium 3.7 GB,
3 EC2 Compute Units
1 virtual core
m3.large 7.5 GB
6.5 EC2 Compute Units
2 virtual cores
m3.xlarge 15 GB
13 EC2 Compute Units
4 virtual cores
m3.2xlarge 30 GB
26 EC2 Compute Units
8 virtual cores
EC2 Compute Units
Memory(GB)
0.5
1
2
4
8
16
32
64
128
256
1 2 4 8 16 32 64 128
General'Purpose'
Compute'Op1mized'
GPU'Instances'
Memory'Op1mized'
Storage'Op1mized'
t1.micro'
m2.xlarge 17.1 GB
6.5 EC2 Compute Units
2 virtual cores
m2.2xlarge 34.2 GB
13 EC2 Compute Units
4 virtual cores
m2.4xlarge 68.4 GB
26 EC2 Compute Units
8 virtual cores
cr1.8xlarge 244 GB
88 EC2 Compute Units
32 virtual cores
c1.medium 1.7 GB
5 EC2 Compute Units
2 virtual cores
c3.large 3.75 GB
7 EC2 Compute Units
2 virtual cores
C3.xlarge 7.5 GB
14 EC2 Compute Units
4 virtual cores
c1.xlarge 7 GB
20 EC2 Compute Units
8 virtual cores
C3.2xlarge 15 GB
28 EC2 Compute Units
8 virtual cores
C3.4xlarge 30GB
55 EC2 Compute Units
16 virtual cores
C3.8xlarge 60GB
108 EC2 Compute Units
32 virtual cores
Cc2.8xlarge 60.5GB
88 EC2 Compute Units
32 virtual cores

56. Unix/Linux instances start at $0.02/
hour
Pay as you go for compute power
Low cost and flexibility
Pay only for what you use, no up-front
commitments or long-term contracts
Use Cases:
Applications with short term, spiky, or
unpredictable workloads;
Application development or testing
On-demand instances
1- or 3-year terms
Pay low up-front fee, receive significant
hourly discount
Low Cost / Predictability
Helps ensure compute capacity is available
when needed
Use Cases:
Applications with steady state or
predictable usage
Applications that require reserved capacity,
including disaster recovery
Reserved instances
Bid on unused EC2 capacity
Spot Price based on supply/demand,
determined automatically
Cost / Large Scale, dynamic workload
handling
Use Cases:
Applications with flexible start and end
times
Applications only feasible at very low
compute prices
Spot instances
Rule 6: Leverage unique cloud properties
a) Optimize costs with instance types

57. 0
1000
2000
3000
4000
5000
6000
7000
Reserved Instances
On Demand
Spot
Rule 6: Leverage unique cloud properties
a) Optimize costs with instance types

58. a) Optimize costs with instance types
b) Get insight fast with Elastic MapReduce
Rule 6: Leverage unique cloud properties
Elastic MapReduce
Managed, elastic Hadoop cluster
Integrates with S3 & DynamoDB
Leverage Hive & Pig analytics scripts
Integrates with instance types such as spot
Feature Details
Scalable Use as many or as few compute instances
running Hadoop as you want. Modify the
number of instances while your job flow is
running
Integrated with
other services
Works seamlessly with S3 as origin and output.
Integrates with DynamoDB
Comprehensive Supports languages such as Hive and Pig for
defining analytics, and allows complex
definitions in Cascading, Java, Ruby, Perl,
Python, PHP, R, or C++
Cost effective Works with Spot instance types
Monitoring Monitor job flows from with the management
console

59. a) Optimize costs with instance types
b) Get insight fast with Elastic MapReduce
Elastic
MapReduce
Code Name
node
Output
S3 + SimpleDB
S3 + DynamoDB
Elastic cluster
HDFS
Queries
+ BI
Via JDBC, Pig, Hive
Input data
Rule 6: Leverage unique cloud properties

60. Cluster compute instances
Implement HVM process execution
Intel® Xeon® E5-2670 processors
10 Gigabit Ethernet
Cluster Compute
80 EC2
Compute Units
60GB RAM
3TB Local
Disk
Network placement groups
Cluster instances deployed in a ‘Placement Group’
enjoy low latency, full bisection 10 Gbps bandwidth
10Gbps
Rule 6: Leverage unique cloud properties
a) Optimize costs with instance types
b) Get insight fast with Elastic MapReduce
c) Create a supercomputer backend when you need it

61. Rule 2: Service requests as fast as possible
Rule 1: Service all web requests
Rule 3: Handle requests at any scale
Rule 4: Simplify architecture with services
Rule 5: Automate operational management
Rule 6: Leverage unique cloud properties

62. Common Patterns for Scalable
Web Applications

63. Stateless
Scale horizontally
Loose coupling
Automation

64. Design your application for the AWS Cloud
More details on the AWS Architecture Center at : aws.amazon.com/architecture

65. AWS Training & Certification
Certification
aws.amazon.com/certification
Demonstrate your skills,
knowledge, and expertise
with the AWS platform
Self-Paced Labs
aws.amazon.com/training/
self-paced-labs
Try products, gain new
skills, and get hands-on
practice working with
AWS technologies
aws.amazon.com/training
Training
Skill up and gain
confidence to design,
develop, deploy and
manage your applications
on AWS

66. Scalable Web Applications on AWS
Ian Massingham - Technical Evangelist
17 June 2014

67. @AWS_UKI for local AWS events & news
@AWScloud for Global AWS News and Announcements
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reserved.
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