1. © 2014 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.© 2014 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.
Scaling on AWS for the
First 10 Million Users
Ian Massingham, Technical Evangelist
30 April 2014@IanMmmm
ianmas@amazon.com

2. Scaling to 10M Users: A Story in Four Parts
• Intro and Initial Steps
• Building Blocks
• Tools and Monitoring
• 10M Users and Beyond

3. So how do we scale?

4. not where we want to start
a lot of things to read

5. Auto Scaling is a tool and a
destination. It’s not the single
thing that fixes everything.

6. What do we
need first?

7. Some basics…

8. • $7B+ retail business
• 8,000+ employees
• A whole lot of servers
Every day, AWS adds enough
server capacity to power that
entire $7B enterprise
2004 2014

9. Support
Certification
Training
Professional Services
Technology Partners
Consulting Partners
AWS Marketplace
Ecosystem
Elastic Beanstalk for Java, Node.js, Python,
Ruby, PHP and .Net
OpsWorks
CloudFormation
Containers & Deployment (PaaS)
Management &
Administration
IAM
CloudWatch
CloudTrail
APIs and SDKs
Management Console
Cloud HSM
Command Line Interface
Direct Connect
Route 53
VPC
Networking
Analytics
Data Pipeline
Redshift
EMR
Kinesis
SWF
SNS
SQS
CloudSearch
SES
AppStream
CloudFront
Application Services
WorkSpaces
Regions
Availability Zones
Content Delivery POPs
Storage Gateway
S3
EBS
Glacier
Import/Export
DynamoDB
ElastiCache
Storage
Compute
Databases
RDS
MySQL, PostgreSQL
Oracle, SQL Server
Elastic Load Balancer
EC2
Auto Scaling

10. So let’s start from day
one, user one ( you )

11. Day One, User One:
• A single EC2 instance
– With a full stack on this host
• Web app
• Database
• Management
• etc.
• A single Elastic IP address
• Amazon Route 53 for DNS
EC2
instance
Elastic IP
address
Amazon
Route 53
User

12. “We’re gonna need a bigger box”
• Simplest approach
• Can now leverage PIOPs
• High I/O instances
• High memory instances
• High CPU instances
• High storage instances
• Easy to change instance sizes
• Will hit an endpoint eventually m3.xlarge
m1.small
i2.4xlarge

13. “We’re gonna need a bigger box”
• Simplest approach
• Can now leverage PIOPs
• High I/O instances
• High memory instances
• High CPU instances
• High storage instances
• Easy to change instance sizes
• Will hit an endpoint eventually m3.xlarge
m1.small
i2.4xlarge

14. Day One, User One:
• We could potentially get
to a few hundred to a few
thousand depending on
application complexity
and traffic
• No failover
• No redundancy
• Too many eggs in one
basket
EC2
instance
Elastic IP
address
Amazon
Route 53
User

15. Day One, User One:
• We could potentially get
to a few hundred to a few
thousand depending on
application complexity
and traffic
• No failover
• No redundancy
• Too many eggs in one
basket
EC2
instance
Elastic IP
address
Amazon
Route 53
User

16. Day Two, User >1:
First, let’s separate out
our single host into
more than one:
• Web
• Database
– Make use of a database
service?
Web
instance
Database
instance
Elastic IP
address
Amazon
Route 53
User

17. Self-Managed Fully-Managed
Database server
on Amazon EC2
Your choice of
database running on
Amazon EC2
Bring Your Own
License (BYOL)
Amazon
DynamoDB
Managed NoSQL
database service
using SSD storage
Seamless scalability
Zero administration
Amazon RDS
Microsoft SQL,
Oracle, MySQL or
PostgreSQL as a
managed service
Flexible licensing
BYOL or License
Included
Amazon
Redshift
Massively parallel,
petabyte-scale, data
warehouse service
Fast, powerful and
easy to scale
Database Options

18. Scaling to 10M Users: A Story in Four Parts
• Intro and Initial Steps
• Building Blocks
• Tools and Monitoring
• 10M Users and Beyond

19. But how do I choose
the DB technology I
need? SQL? NoSQL?

20. Start with SQL
databases

21. Why start with SQL?
• Established and well-worn technology
• Lots of existing code, communities, books, background,
tools, etc.
• You aren’t going to break SQL DBs in your first 10 million
users. No really, you won’t*.
• Clear patterns to scalability
* Unless you are manipulating data at MASSIVE scale; even then, SQL will have a
place in your stack

22. AH HA! You
said “massive
amounts”, I
will have
massive
amounts!

23. If your usage is such that you will be
generating several TB ( >5 ) of data
in the first year OR have an
incredibly data-intensive workload…
you might need NoSQL

24. Regardless, why NoSQL?
• Super low latency applications
• Metadata driven datasets
• Highly non-relational data
• Need schema-less data constructs*
• Massive amounts of data (again, in the TB range)
• Rapid ingest of data ( thousands of records/sec )
• Already have skilled staff
*Need != “it is easier to do dev without schemas”

25. When NoSQL = Yes…
investigate use of DynamoDB

26. Amazon Dynamo DB
• Managed, 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 Amazon CloudWatch
Secure Integrates with AWS Identity and
Access Management (AWS IAM)
Amazon EMR Integrates with Amazon EMR for
complex analytics on large datasets

27. But back to the main
path… Let’s see how
far SQL at the core
can grow

28. User >100:
First, let’s separate out
our single host into
more than one:
• Web
• Database
– Use Amazon RDS to make
your life easier
Web
instance
Elastic IP
address
RDS DB
instance
Amazon
Route 53
User

29. User > 1000:
Next, let’s address the
lack of failover and
redundancy issues:
• Elastic Load Balancing
• Another web instance
– In another Availability Zone
• Enable Amazon RDS Multi-AZ
Web
instance
Amazon RDS DB instance
Active (Multi-AZ)
Availability Zone Availability Zone
Web
instance
Amazon RDS DB instance
Standby (Multi-AZ)
Elastic Load
Balancing
Amazon
Route 53
User

30. • Create highly-scalable applications
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 Amazon CloudWatch
Elastic Load
Balancing
Elastic Load Balancing

31. Scaling this horizontally
and vertically
will get us pretty far
( 10s-100s of thousands )

32. User >10ks-100ks:
RDS DB Instance
Active (Multi-AZ)
Availability Zone Availability Zone
RDS DB Instance
Standby (Multi-AZ)
Elastic Load
Balancing
RDS DB Instance
Read Replica
RDS DB Instance
Read Replica
RDS DB Instance
Read Replica
RDS DB Instance
Read Replica
Web
instance
Web
instance
Web
instance
Web
instance
Web
instance
Web
instance
Web
instance
Web
instance
Amazon
Route 53
User

33. This will take us pretty far,
honestly, but we care
about performance and
efficiency, so let’s clean up with
some components and services

34. Shift some load around:
Think components and
services:
• Move static content from the
web instance to Amazon S3
and Amazon CloudFront
• Move session/state and DB
caching to Amazon
ElastiCache or Amazon
DynamoDB
• More on services later…
Web
instance
RDS DB Instance
Active (Multi-AZ)
Availability Zone
Elastic Load
Balancing
Amazon S3
Amazon
CloudFront
Amazon
Route 53
User
ElastiCache
Amazon
DynamoDB

35. Working with Amazon S3
• Object-based storage for the web
• Designed for 11 9s of durability
• Good for things like:
– Static assets (css, js, images, videos)
– Backups
– Logs
– Ingest of files for processing
• “Infinitely scalable”
• Supports fine-grained permission control
• Ties in well with CloudFront
• Ties in with Amazon EMR
• Acts as a logging endpoint for Amazon
S3/CloudFront/Billing
• Supports encryption at transit and at rest
• Reduced redundancy 1/3 cheaper
• Amazon Glacier for super long term
storage

36. CloudFront
Amazon CloudFront is a web service for
scalable content delivery:
• Cache static content at the edge for faster delivery
• Helps lower load on origin infrastructure
• Dynamic and static content
• Streaming video
• Zone apex support
• Custom SSL certificates
• Low TTLs (as short as 0 seconds)
• Lower costs for origin fetches (between Amazon
S3 / Amazon EC2 and CloudFront)
• Optimized to work with Amazon EC2, Amazon S3,
Elastic Load Balancing, and Amazon Route 53
Response
Time
Server
Load
Response
Time
Server
Load
Response
Time
Server
Load
No
CDN
CDN
for
sta6c
content
CDN
for
sta6c
&
dynamic
content
0
20
40
60
80
8:00
AM
9:00
AM
10:00
AM
11:00
AM
12:00
PM
1:00
PM
2:00
PM
3:00
PM
4:00
PM
5:00
PM
6:00
PM
7:00
PM
8:00
PM
9:00
PM
VolumeofData
Delivered(Gbps)

37. Shift some load around:
Let’s lighten the load on our
web and database
instances:
• Move static content from the
web instance to Amazon S3
and CloudFront
• Move dynamic content from
the load balancer to
CloudFront
• Move session/state and DB
caching to ElastiCache or
Amazon DynamoDB
Web
instance
RDS DB Instance
Active (Multi-AZ)
Availability Zone
Elastic Load
Balancer
Amazon S3
Amazon
CloudFront
Amazon
Route 53
User
ElastiCache
Amazon
DynamoDB

38. Scaling to 10M Users: A Story in Four Parts
• Intro and Initial Steps
• Building Blocks
• Tools and Monitoring
• 10M Users and Beyond

39. Now that our web tier is
much more lightweight,
we can revisit the
beginning of our talk…

40. Auto Scaling!

41. 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;
compa6ble
with
VPC
aws
autoscaling
create-­‐auto-­‐scaling-­‐
group
-­‐-­‐auto-­‐scaling-­‐group-­‐name
MyGroup
-­‐-­‐launch-­‐configuration-­‐name
MyConfig
-­‐-­‐min-­‐size
4
-­‐-­‐max-­‐size
200
-­‐-­‐availability-­‐zones
us-­‐west-­‐2c
Auto Scaling
Amazon
CloudWatch

42. November
traffic
to
Amazon.com
76%
24%
Provisioned capacity
November

43. Auto Scaling
lets you do this!

44. Auto Scaling can help from
one instance to thousands
and back down

45. User >500k+:
Availability Zone
Amazon
Route 53
User
Amazon S3
Amazon
CloudFront
Availability Zone
Elastic Load
Balancing
Amazon
DynamoDBRDS DB Instance
Read Replica
Web
instance
Web
instance
Web
instance
ElastiCache RDS DB Instance
Read Replica
Web
instance
Web
instance
Web
instance
ElastiCacheRDS DB Instance
Standby (Multi-AZ)
RDS DB Instance
Active (Multi-AZ)

46. Use Tools:
Managing your infrastructure will become an ever
increasing important part of your time. Use tools to
automate repetitive tasks.
• Tools to manage AWS resources
• Tools to manage software and configuration on your
instances
• Automated data analysis of logs and user actions

47. AWS Application Management Solutions
AWS
Elastic Beanstalk
AWS
OpsWorks
AWS
CloudFormation
Amazon EC2
Convenience Control
Higher-level services Do it yourself

48. Host-Based Configuration Management
Two big players:
– Opscode Chef
– PuppetLabs Puppet
• Both do more or less the same thing
• Both have syntax that isn’t too dissimilar
• Use HBCM with one of the tools from the previous slide
• Spend the time required to learn them
• Can’t scale easily without HBCM
• Growing in popularity: Salt, Ansible

49. User >500k+:
You’ll potentially start to run into issues with speed and
performance of your applications:
• Have monitoring/metrics/logging in place
– If you can’t build it internally, outsource it! (3rd party SaaS)
• Pay attention to what customers are saying works well
• Squeeze as much performance as you can out of each
service/component

50. User >1mil+:
Reaching a million and above is going to require some bit
of all the previous things:
• Multi-AZ
• Elastic Load Balancing between tiers
• Auto Scaling
• Service-oriented architecture
• Serving content smartly (Amazon S3/CloudFront)
• Caching off DB
• Moving state off tiers that auto-scale

51. User >1mil+:
RDS DB Instance
Active (Multi-AZ)
Availability Zone
Elastic Load
Balancing
RDS DB Instance
Read Replica
RDS DB Instance
Read Replica
Web
instance
Web
instance
Web
instance
Web
instance
Amazon
Route 53
User
Amazon S3
Amazon
CloudFront
Amazon
DynamoDB
Amazon SQS
ElastiCache
Worker
instance
Worker
instance
Amazon
CloudWatch
Internal app
instance
Internal app
instance
Amazon SES

52. The next big steps

53. User >5mil – 10mil:
You’ll potentially start to run into issues with your database
around contention on the write master.
How can you solve it?
• Federation ~ splitting into multiple DBs based on function
• Sharding ~ splitting one data set up across multiple hosts
• Moving some functionality to other types of DBs (NoSQL)

54. …and there you have it.
10 Million

55. Scaling from 1 to 10 million users
Boyan Dimitrov,
Senior Systems Engineer at Hailo

56. AWS Summits 2014

57. AWS Summits 2014

58. AWS Summits 2014
The world’s highest-rated taxi app - over 13,000 five-
star reviews
To date, Hailo has carried more than 9 million
passengers
Hailo has over 50,000 registered taxi drivers
worldwide

59. November 2011: Hailo 1.0 Launch
Users: 1
Regions: eu-west-1
AWS Summits 2014

60. eu-west-1
Java
MYSQL
PHP
Architecture specifics
• Monolithic PHP and Java applications
• Built and supported by 3-4 backend engineers
• MySQL master-master replication for
resilience
• Multi-AZ since day 1
• City-specific environments
AWS specifics
Route 53 ELB S3
AWS Summits 2014

61. Challenges
• Hard to develop new features
• Painful to push code changes
• Adding new instances and adding more capacity is a very slow process
• Unreliable and slow failover procedures
• SPOF
AWS Summits 2014

62. December 2013: Hailo 2.0
AWS Summits 2014
Users: 1 000 000+
Regions: eu-west-1, us-east-1, ap-northeast-1

63. Architecture specifics
• SOA built in Go and Java
• Seamless service discovery, service to service communication,
monitoring and instrumentation
• Everything is automated
• Ability to scale services up and down based on demand
AWS specifics
Route 53 ELB S3
AWS Summits 2014
Autoscaling Cloudfront Redshift

64. eu-west-1
Message
Bus+
Go
Services
Proxy Layer
Java
Services
C*
us-east-1
Proxy Layer
C*
ap-northeast -1
Proxy Layer
C*
AWS Summits 2014
Distributed
Queue+
Message
Bus+
Distributed
Queue+
Message
Bus+
Distributed
Queue+
Go
Services
Java
Services
Go
Services
Java
Services

65. Challenges
• Hard to develop new features
Completing new features in days, not months
• Painful to push code changes
Seamless service deployment and ability to run multiple versions of a service
• Adding new instances and adding more capacity is slow
Our servers scale up and down based on demand
• Unreliable and slow failover procedures
Automated reaping of misbehaving services and AZ failover
• SPOF
Fault-tolerant distributed services architecture
AWS Summits 2014

66. Important KPI
AWS Summits 2014

67. The Future
AWS Summits 2014

68. AWS Summits 2014

69. AWS Summits 2014

70. Tooling
AWS Summits 2014

71. AWS Summits 2014

72. AWS Summits 2014

73. AWS Summits 2014

74. Thank
you,
any
ques6ons?
AWS Summits 2014
boyan@hailocab.com
@nathariel

75. Next Steps?
READ!
• aws.amazon.com/documentation
• aws.amazon.com/architecture
• aws.amazon.com/start-ups

76. AWS Partner Trail
Win a Kindle Fire
• 10 in total
• Get a code from our
sponsors

77. Please rate
this session
using the AWS
Summits App
and help us
build better
events

78. #AWSSummit
@AWScloud @AWS_UKI

79. © 2014 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.© 2014 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.
Scaling on AWS for the
First 10 Million Users
Thank you!
Ian Massingham, Technical Evangelist
30 April 2014
ianmas@amazon.com
@IanMmmm