Cloud computing gives you a number of advantages, such as the ability to scale your web application or website on demand. If you have a new web application and want to use cloud computing, you might be asking yourself, "Where do I start?" Join us in this session to understand best practices for scaling your resources from zero to millions of users. We show you how to best combine different AWS services, how to make smarter decisions for architecting your application, and how to scale your infrastructure in the cloud.

1. © 2015, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Joel Williams, AWS Solutions Architect
October 8, 2015
Scaling Up to Your
First Million Users1011
ARC301

2. Joel Williams
• Amazon Web Services Solutions Architect (July 2012)
AWS re:Invent 2015

3. AWS re:Invent 2015
WHO
ARE
YOU?

4. So how do we scale?

5. http://i.telegraph.co.uk/multimedia/archive/02674/CLIMBER_2674482b.jpg

7. Now that’s a lot
of things to read!
This is NOT
where we
want to start!

8. Auto Scaling
…is a tool and a destination.

9. It’s not the single thing that
fixes everything.

10. What do we need first?

11. Some basics…

12. US-WEST (Oregon)
EU (Ireland)
ASIA PACIFIC
(Tokyo)
US-WEST (N. California)
SOUTH
AMERICA (Sao
Paulo)
US-EAST (N. Virginia)
AWS GOVCLOUD (US)
ASIA PACIFIC
(Sydney)
ASIA PACIFIC
(Singapore)
CHINA (Beijing)
Regions
EU (Frankfurt)
INDIA (2016)

13. US-WEST (Oregon)
EU (Ireland)
ASIA PACIFIC
(Tokyo)
US-WEST (N. California)
SOUTH
AMERICA (Sao
Paulo)
US-EAST (N. Virginia)
AWS GOVCLOUD (US)
ASIA PACIFIC
(Sydney)
ASIA PACIFIC
(Singapore)
CHINA (Beijing)
Availability Zones
EU (Frankfurt)
INDIA (2016)

14. Edge locations

15. TECHNICAL &
BUSINESS
SUPPORT
Account
Management
Support
Professional
Services
Solutions
Architects
Training &
Certification
Security
& Pricing
Reports
Partner
Ecosystem
AWS
MARKETPLACE
Backup
Big Data
& HPC
Business
Apps
Databases
Development
Industry
Solutions
Security
APPLICATION
SERVICES
Queuing
Notifications
Search
Orchestration
Email
ENTERPRISE
APPS
Virtual
Desktops
Storage
Gateway
Sharing &
Collaboration
Email &
Calendaring
Directories
HYBRID CLOUD
MANAGEMENT
Backups
Deployment
Direct
Connect
Identity
Federation
Integrated
Management
SECURITY &
MANAGEMENT
Virtual Private
Networks
Identity &
Access
Encryption
Keys
Configuration Monitoring Dedicated
INFRASTRUCTURE
SERVICES
Regions
Availability
Zones
Compute Storage
Databases
SQL, NoSQL,
Caching
CDNNetworking
PLATFORM
SERVICES
App
Mobile
& Web
Front-end
Functions
Identity
Data Store
Real-time
Development
Containers
Source
Code
Build
Tools
Deployment
DevOps
Mobile
Sync
Identity
Push
Notifications
Mobile
Analytics
Mobile
Backend
Analytics
Data
Warehousing
Hadoop
Streaming
Data
Pipelines
Machine
Learning

16. TECHNICAL &
BUSINESS
SUPPORT
Account
Management
Support
Professional
Services
Solutions
Architects
Training &
Certification
Security
& Pricing
Reports
Partner
Ecosystem
AWS
MARKETPLACE
Backup
Big Data
& HPC
Business
Apps
Databases
Development
Industry
Solutions
Security
APPLICATION
SERVICES
Queuing
Notifications
Search
Orchestration
Email
ENTERPRISE
APPS
Virtual
Desktops
Storage
Gateway
Sharing &
Collaboration
Email &
Calendaring
Directories
HYBRID CLOUD
MANAGEMENT
Backups
Deployment
Direct
Connect
Identity
Federation
Integrated
Management
SECURITY &
MANAGEMENT
Virtual Private
Networks
Identity &
Access
Encryption
Keys
Configuration Monitoring Dedicated
INFRASTRUCTURE
SERVICES
Regions
Availability
Zones
Compute Storage
Databases
SQL, NoSQL,
Caching
CDNNetworking
PLATFORM
SERVICES
App
Mobile
& Web
Front-end
Functions
Identity
Data Store
Real-time
Development
Containers
Source
Code
Build
Tools
Deploymen
t
DevOps
Mobile
Sync
Identity
Push
Notifications
Mobile
Analytics
Mobile
Backend
Analytics
Data
Warehousing
Hadoop
Streaming
Data
Pipelines
Machine
Learning

17. Solutions
Architects

18. Solutions Architects

19. APPLICATION
SERVICES
Queuing
Notifications
Search
Orchestration
Email
SECURITY &
MANAGEMENT
Virtual Private
Networks
Identity &
Access
Encryption
Keys
Configuration Monitoring Dedicated
INFRASTRUCTURE
SERVICES
Regions
Availability
Zones
Compute Storage
Databases
SQL, NoSQL,
Caching
CDNNetworking
PLATFORM
SERVICES
App
Mobile
& Web
Front-end
Functions
Identity
Data Store
Real-time
Development
Containers
Source
Code
Build
Tools
Deployment
DevOps
Mobile
Sync
Identity
Push
Notifications
Mobile
Analytics
Mobile
Backend
Analytics
Data
Warehousing
Hadoop
Streaming
Data
Pipelines
Machine
Learning

20. AWS building blocks
Inherently highly available and
fault-tolerant services
Highly available with
the right
architecture
 Amazon CloudFront
 Amazon Route 53
 Amazon S3
 Amazon DynamoDB
 Elastic Load Balancing
 Amazon EFS
 AWS Lambda
 Amazon SQS
 Amazon SNS
 Amazon SES
 Amazon SWF
 …
 Amazon EC2
 Amazon EBS
 Amazon RDS
 Amazon VPC

21. So let’s start from…

22. 1 user
You

23. 1 User
• Amazon Route 53 for DNS
• A single Elastic IP
• A single Amazon EC2 instance
• With full stack on this host
• Web app
• Database
• Management
• And so on…
Amazon
EC2
instance
Elastic IP
User
Amazon
Route 53

24. “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
c4.8xlarge
m3.2xlarge
t2.micro

25. “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
c4.8xlarge
m3.2xlarge
t2.micro

26. 1 User
• 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
User
Amazon
Route 53

27. 1 User
• 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
User
Amazon
Route 53

28. Users >1

29. Users > 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
User
Amazon
Route 53

30. 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 Server
Oracle
MySQL
PostgreSQL
MariaDB
Amazon Aurora
BYOL or license
Included
Amazon
Redshift
Massively parallel,
petabyte-scale data
warehouse service
Fast, powerful, and
easy to scale
Database options

31. 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 Server
Oracle
MySQL
PostgreSQL
MariaDB
Amazon Aurora
BYOL or license
Included
Amazon
Redshift
Massively parallel,
petabyte-scale data
warehouse service
Fast, powerful, and
easy to scale
Database options

32. Amazon Aurora
• Automatic storage scaling (up to 64 TB)
• Up to 15 read-replicas
• Continuous (incremental) backups to
Amazon S3
• 6-way replication across 3 AZs
• MySQL Compatible

33. To NoSQL, or not to NoSQL?

34. Some folks won’t like this,
but…

35. Start with SQL databases

36. Why start with SQL?
• Established and well-worn technology.
• Lots of existing code, communities, books, and tools.
• 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 doing something SUPER peculiar with the data or you have MASSIVE amounts of it.
…but even then SQL will have a place in your stack.

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

38. > 5 TB in year one?
Incredibly data intensive workload?
OK!
You might need NoSQL.

39. Why else might you need NoSQL?
• Super low-latency applications
• Metadata-driven datasets
• Highly nonrelational data
• Need schema-less data constructs*
• Massive amounts of data (again, in the TB range)
• Rapid ingest of data (thousands of records/sec)
*Need!= “It’s easier to do dev without schemas”

40. Users >100

41. Users >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
RDS DB
instance
User
Amazon
Route 53

42. Users >1000

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

44. Elastic Load Balancing
• Highly available
• 1 - 65535
• Health checks
• Session stickiness
• Secure sockets layer
• Monitoring
• Logging

45. horizontally
vertically

47. Users > 10,000s–100,000s
RDS DB Instance
Active (Multi-AZ)
Availability Zone Availability Zone
RDS DB Instance
Standby (Multi-AZ)
ELB
Balancer
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 53User

48. What about
performance and efficiency?

49. Lighten the Load

50. RDS DB Instance
Active (Multi-AZ)
Availability Zone
ELB
Balancer
Amazon S3
Amazon
CloudFront
Amazon
Route 53
User
Shift some load around
Web Instances
• static content to Amazon S3
and Amazon CloudFront
Move…

51. Amazon Simple Storage Service (S3)
• Object-based storage
• Highly durable
• Great for static assets
• “Infinitely scalable”
• Objects up to 5 TB in size
• Optional encryption

52. Amazon CloudFront
• Cache content for faster delivery
• Lower load on origin
• Dynamic and static content
• Streaming video
• Custom SSL certificates
• Low TTLs (as short as 0 seconds)
• Free origin fetches?
• Optimized for AWS

53. Amazon CloudFront
ResponseTime
ServerLoad
Response
Time
Server
Load
Response
Time
Serve
rLoad
No CDN CDN for Static
Content
CDN for Static &
Dynamic Content
0
20
40
60
80
8:00AM
9:00AM
10:00AM
11:00AM
12:00PM
1:00PM
2:00PM
3:00PM
4:00PM
5:00PM
6:00PM
7:00PM
8:00PM
9:00PM
VolumeofData
Delivered(Gbps)

54. Shift some load around
• static content to Amazon S3 and
Amazon CloudFront
Move…
• session/state to Amazon
DynamoDB
• DB caching to Amazon
ElastiCache RDS DB Instance
Active (Multi-AZ)
Availability Zone
ELB
Balancer
Amazon S3
Amazon
CloudFront
Amazon
Route 53
User
ElastiCache DynamoDB
Web Instances

55. Amazon DynamoDB
• Managed NoSQL database
• Provisioned throughput
• Fast, predictable performance
• Fully distributed, fault tolerant
• JSON support
• Items up to 400 KB

56. Amazon Elasticache
• Managed Memcached or Redis
• Scale from one to many nodes
• Self-healing (replaces dead instance)
• Single digit ms speeds (usually)
• Local to a single AZ for Memcache
• Multi-AZ possible with Redis

57. Shift some load around
Move…
• static content to Amazon S3
and Amazon CloudFront
• session/state to Amazon
DynamoDB
• DB caching to Amazon
ElastiCache
• dynamic content to Amazon
CloudFront
RDS DB Instance
Active (Multi-AZ)
Availability Zone
ELB
Balancer
Amazon S3
Amazon
CloudFrontUser
ElastiCache DynamoDB
Web Instances
Amazon
Route 53

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

59. Auto Scaling!

60. Automatic resizing of compute clusters
Define min/max pool sizes
CloudWatch metrics drive scaling
On-demand or Spot instances
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, us-west-2b
Auto Scaling

61. Sunday Monday Tuesday Wednesday Thursday Friday Saturday
Typical weekly traffic to Amazon.com

62. Sunday Monday Tuesday Wednesday Thursday Friday Saturday
Typical weekly traffic to Amazon.com
Provisioned capacity

63. November
November traffic to Amazon.com

64. Provisioned capacity
November
November traffic to Amazon.com

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

66. November traffic to Amazon.com
November

67. Auto Scaling
lets you do this!

68. = one user
= 100,000 users= 1,000,000 users

69. Users >500,000

70. Users > 500,000+
Availability Zone
Amazon
Route 53
User
Amazon S3
Amazon
CloudFront
Availability Zone
ELB
Balancer
DynamoDB
RDS 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)

71. Users > 500,000+
Availability Zone
Amazon
Route 53
User
Amazon S3
Amazon
CloudFront
Availability Zone
ELB
Balancer
DynamoDB
RDS 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)

72. Use automation

73. AWS application management solutions
Convenience Control
Higher-level services Do it yourself
AWS
Elastic Beanstalk
AWS
OpsWorks
AWS
CloudFormation
Amazon EC2

74. AWS CodeDeploy
• Deploys your code to a “fleet” of EC2 instances
• 1 – 10,000s of instances
• Automatically schedules updates (multiple AZs)
• Application and Deployment groups described in
YAML-formatted files
• Can reference Auto Scaling Groups
• AWS Management Console, CLI, or APIs
• Can be used with Chef recipes or Puppet scripts

75. Users >500,000+
• Monitoring, metrics, and logging
• If you can’t build it internally,
outsource it! (third-party SaaS)
• What are customers saying?
• Try to squeeze as much performance
out of each service/component

76. AGGREGATE
LEVEL
METRICS
LOG
ANALYSIS
EXTERNAL
SITE
PERFORMANCE
HOST
LEVEL
METRICS

77. There are further
improvements to be made
in breaking apart our
web/app layer

78. SOA
What does this mean?

80. Now that’s a lot
of things to read!
This is NOT
where we
want to start!

81. This is NOT
where we
want to start!
This IS where
we want to start!
Now that’s a lot
of things to read!

82. SOAing
Move services into their own tiers.
• Treat them separately and scale
them independently.
Amazon and AWS do this extensively!
It offers flexibility and greater
understanding of each component

83. Loose coupling + SOA = winning
DON’T REINVENT THE WHEEL
• Email
• Queuing
• Transcoding
• Search
• Databases
• Monitoring
• Metrics
• Logging
• Compute
Amazon
CloudSearch
Amazon SQSAmazon SNS
Amazon Elastic
Transcoder
Amazon SWFAmazon SES
AWS Lambda

84. • Reliable (Multi-AZ)
• Scalable (unlimited messages)
• Secure (queue authentication)
• Simple (simple APIs)
Application Services – Amazon SQS
SQS
messages
Get
Message
Instance
Put
Message
Instance
Amazon SNS Topic
Publish
Notification
Queue Is Subscribed
to Topic

85. Compute / Platform – AWS Lambda
• Functions triggered by events
• JavaScript, Java… and Python
• Managed
• Implicit scaling
S3 Bucket
Lambda
Push: Event
Notification
DynamoDB
Pull: DynamoDB
Stream
Kinesis
Pull:
Kinesis Stream

86. Loose coupling sets you free!
The looser they're coupled, the bigger they scale
• Independent components
• Design everything as a black box
• Decouple interactions
• Favor services with built-in redundancy and scalability rather than
building your own
S3 Bucket
Lambda
Push: Event
Notification
DynamoDB
Pull: DynamoDB
Stream
Amazon
Kinesis
Pull:
DynamoDB Stream
SQS
messages
Get
Message
Instance
Put
Message
Instance
Amazon SNS Topic
Publish
Notification
Queue Is Subscribed
to Topic

87. Users >1,000,000

88. Users >1 million+
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

89. Users >1 million+
RDS DB Instance
Active (Multi-AZ)
Availability Zone
ELB
Balancer
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
DynamoDB
Amazon SQS
ElastiCache
Worker
Instance
Worker
Instance
Amazon
CloudWatch
Internal App
Instance
Internal App
Instance Amazon SES
Lambda

90. The next big steps

91. Users >10,000,000

92. Users >5 million - 10 million
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 dataset up across multiple hosts
• Moving some functionality to other types of DBs (NoSQL, Graph)

93. Database federation
• Split up databases by function/purpose
• Harder to do cross-function queries
• Essentially delays sharding/NoSQL
• Won’t help with single huge functions/tables
Forums DB
Users DB
Products
DB

94. Sharded horizontal scaling
• More complex at the application layer
• No practical limit on scalability
• Operation complexity/sophistication
• Shard by function or key space
• RDBMS or NoSQL
User ShardID
002345 A
002346 B
002347 C
002348 B
002349 A
CBA

95. Shifting functionality to NoSQL
• Similar in a sense to federation
• Again, think about the earlier points for when you
need NoSQL vs. SQL
• Leverage managed services like DynamoDB
Some use cases:
• Leaderboards/scoring
• Rapid ingest of clickstream/log data
• Temporary data needs (cart data)
• “Hot” tables
• Metadata/lookup tablesDynamoDB

96. A quick review

97. A quick review
• Multi-AZ your infrastructure.
• Make use of self-scaling services—ELB, Amazon S3,
Amazon SNS, Amazon SQS, Amazon SWF, Amazon SES, and
more.
• Build in redundancy at every level.
• Start with SQL. Seriously.
• Cache data both inside and outside your infrastructure.
• Use automation tools in your infrastructure.

98. A quick review continued
• Make sure you have good metrics/monitoring/logging
tools in place
• Split tiers into individual services (SOA)
• Use Auto Scaling once you’re ready for it
• Don’t reinvent the wheel
• Move to NoSQL if and when it makes sense

99. Putting all this together
means we should now
easily be able to handle
11+ million users!

100. To infinity...

101. User >11 million
Iterating on top of the
patterns seen here will get
you up and over 100 million
users

102. • More fine-tuning of your application
• More SOA of features/functionality
• Going from Multi-AZ to multi-region
• Possibly start to build custom solutions
• Deep analysis of your entire stack
User >11 million

103. Next steps?
READ!
aws.amazon.com/documentation
aws.amazon.com/architecture
aws.amazon.com/start-ups
START USING AWS:
aws.amazon.com/free/

104. Ask for Help!
forums.aws.amazon.com
aws.amazon.com/premiumsupport/
Your Account Manager
A Solutions Architect

105. Thank you!
Joel Williams

106. Remember to complete
your evaluations!

107. Related Sessions
DVO303 - Scaling Infrastructure Operations with AWS Service Catalog,
AWS Config, and AWS CloudTrail
Friday, Oct 9, 9:00 AM - 10:00 AM – Lido 3001B
DVO201 - Scaling Your Web Applications with AWS Elastic Beanstalk
Friday, Oct 9, 9:00 AM - 10:00 AM – Titan 2306
CMP201 - All You Need To Know About Auto Scaling
Friday, Oct 9, 10:15 AM - 11:15 AM – San Polo 3506