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© 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Joel Williams, AWS Solutions Architect
November 29, 2016
Scaling Up to Your
First Million Users1011
ARC201
Joel Williams
• AWS Solutions Architect (July 2012)
AWS re:Invent 2016
AWS re:Invent 2016
WHO
ARE
YOU?
http://i.telegraph.co.uk/multimedia/archive/02674/CLIMBER_2674482b.jpg
Now that’s a lot
of things to read!
This is NOT
where we
want to start!
It’s not the single thing that
fixes everything.
What do we need first?
Some basics…
AWS Global Infrastructure
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
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
Solutions
Architects
Solutions Architects
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
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
So let’s start from…
You
1 User
Amazon
EC2
instance
Elastic IP
User
Amazon
Route 53
“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
“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
1 User
• 100s? 1000s?
• No failover
• No redundancy
• Too many eggs in one
basket
EC2
Instance
Elastic IP
User
Amazon
Route 53
Users >1
Users > 1
Web
Instance
Database
Instance
Elastic IP
User
Amazon
Route 53
Self-managed Fully managed
Amazon EC2 Amazon
DynamoDB
Amazon RDS Amazon
Redshift
Database options
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
To NoSQL, or not to NoSQL?
Start with SQL databases
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.
AH HA! You said
“massive
amounts”
> 5 TB in year one?
Incredibly data intensive workload?
OK!
You might need NoSQL.
Why else might you need NoSQL?
• Super low-latency applications
• Metadata-driven datasets
• Highly nonrelational data
• Need schema-less data constructs*
• Rapid ingest of data (thousands of records/sec)
• Massive amounts of data (again, in the TB range)
*Need!= “It’s easier to do dev without schemas”
Users >100
Users >100
Web
instance
Elastic IP
RDS DB
instance
User
Amazon
Route 53
Users >1000
Users >1000
Web
Instance
RDS DB Instance
Active (Multi-AZ)
Availability Zone Availability Zone
Web
Instance
RDS DB Instance
Standby (Multi-AZ)
Load
balancer
User
Amazon
Route 53
Elastic Load Balancing
• Highly available
• 1 - 65535
• Health checks
• Session stickiness
• Monitoring / Logging
• Secure sockets layer
Application Load Balancer
• Highly available
• 1 - 65535
• Health checks
• Session stickiness
• Monitoring / logging
• Content-based routing
• Container-based apps
• WebSockets
• HTTP/2
horizontally
vertically
Users >100,000
Users > 10,000s–100,000s
RDS DB Instance
Active (Multi-AZ)
Availability Zone Availability Zone
RDS DB Instance
Standby (Multi-AZ)
Load
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
What about
performance and efficiency?
Lighten the Load
RDS DB Instance
Active (Multi-AZ)
Availability Zone
Load
balancer
Amazon S3
Amazon
CloudFront
Amazon
Route 53
User
Shift some load around
Web Instances
Availability Zone
Web Instances
RDS DB Instance
Standby (Multi-AZ)
RDS DB Instance
Active (Multi-AZ)
Availability Zone
Load
balancer
Amazon S3
Amazon
CloudFront
Amazon
Route 53
User
Shift some load around
Web Instances
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
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
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)
Shift some load around
RDS DB Instance
Active (Multi-AZ)
Availability Zone
Load
balancer
Amazon S3
Amazon
CloudFront
Amazon
Route 53
User
ElastiCache DynamoDB
Web Instances
Amazon DynamoDB
• Managed NoSQL database
• Provisioned throughput
• Fast, predictable performance
• Fully distributed, fault tolerant
• JSON support
• Items up to 400 KB
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
Shift some load around
RDS DB Instance
Active (Multi-AZ)
Availability Zone
Load
balancer
Amazon S3
Amazon
CloudFrontUser
ElastiCache DynamoDB
Web Instances
Amazon
Route 53
Now that our web tier is
much more lightweight, we
can revisit the beginning
of our talk…
Auto Scaling!
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
Sunday Monday Tuesday Wednesday Thursday Friday Saturday
Typical weekly traffic to Amazon.com
Sunday Monday Tuesday Wednesday Thursday Friday Saturday
Typical weekly traffic to Amazon.com
Provisioned capacity
November
November traffic to Amazon.com
Provisioned capacity
November
November traffic to Amazon.com
November traffic to Amazon.com
76%
24%
November
Provisioned capacity
November traffic to Amazon.com
November
Auto Scaling
lets you do this!
Users > 500,000+
Availability Zone
Amazon
Route 53
User
Amazon S3
Amazon
CloudFront
Availability Zone
Load
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)
Users > 500,000+
Availability Zone
Amazon
Route 53
User
Amazon S3
Amazon
CloudFront
Availability Zone
Load
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)
Use automation
AWS application management solutions
Convenience Control
Higher-level services Do it yourself
AWS
Elastic Beanstalk
AWS
OpsWorks
AWS
CloudFormation
Amazon EC2
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
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
AGGREGATE
LEVEL
METRICS
LOG
ANALYSIS
EXTERNAL
SITE
PERFORMANCE
HOST
LEVEL
METRICS
There are further
improvements to be made
in breaking apart our
web/app layer
SOA
What does this mean?
Now that’s a lot
of things to read!
This is NOT
where we
want to start!
This is NOT
where we
want to start!
This IS where
we want to start!
Now that’s a lot
of things to read!
SOAing
Move services into their own tiers.
• Treat them separately
• Scale them independently.
It offers flexibility and greater
understanding of each component
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
• 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
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
Amazon
Kinesis
Pull:
Amazon Kinesis
Stream
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
• Don’t build 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
Users >1,000,000
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 (SOA)
• Serving content smartly (Amazon S3/CloudFront )
• Caching off DB
• Moving state off tiers that auto scale
Users >1 million+
RDS DB Instance
Active (Multi-AZ)
Availability Zone
load 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
The next big steps
Users >10,000,000
Users >5 million - 10 million
Database Issues?
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)
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
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
Shifting functionality to NoSQL
• Similar in a sense to federation
• 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 tables
DynamoDB
A quick review
A quick review
• Multi-AZ your infrastructure.
• Make use of self-scaling services—ELB, Amazon S3,
Amazon SNS, Amazon SQS, Amazon SWF, Amazon SES, etc.
• Build in redundancy at every level.
• Start with SQL. Seriously.
• Cache data both inside and outside your infrastructure.
• Use automation tools in your infrastructure.
A quick review continued
• Make sure you have good metrics/monitoring/logging
• 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
11+ million users!
To infinity...
• 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
• AWS EC2 Container Service
• AWS Lambda
User >11 million
Next steps?
READ!
aws.amazon.com/documentation
aws.amazon.com/architecture
aws.amazon.com/start-ups
START USING AWS:
aws.amazon.com/free/
Ask for Help!
forums.aws.amazon.com
aws.amazon.com/premiumsupport/
Your Account Manager
A Solutions Architect
Thank you!
Joel Williams
Remember to complete
your evaluations!
Related Sessions
DEV206 – Scaling Your Web Applications with AWS Elastic Beanstalk
Tue, Nov 29, 11:00 AM – 12:00 PM – Venetian, Level 2, Opaline Theatre
Thurs, Dec 1, 2:00 PM – 3:00 PM – Venetian, Level 2, Titan 2305
ARC305 – From Monolithic to Microservices: Evolving Architecture
Patterns in the Cloud
Wed, Nov 30, 2:00 PM – 3:00 PM – Venetian, Level 2, Venetian Theatre
Fri, Dec 2, 9:00 AM – 10:00 AM – Venetian, Level 4, Lando 4205
CMP201 – Auto Scaling – The Fleet Management Solution for Planet Earth
Thurs, Dec 1, 5:00 PM – 6:00 PM – Venetian, Level 2, Opaline Theatre

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AWS re:Invent 2016: Scaling Up to Your First 10 Million Users (ARC201)

  • 1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Joel Williams, AWS Solutions Architect November 29, 2016 Scaling Up to Your First Million Users1011 ARC201
  • 2. Joel Williams • AWS Solutions Architect (July 2012) AWS re:Invent 2016
  • 5.
  • 6. Now that’s a lot of things to read! This is NOT where we want to start!
  • 7. It’s not the single thing that fixes everything.
  • 8. What do we need first?
  • 11.
  • 12. 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
  • 13. 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. 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
  • 17. 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
  • 18. So let’s start from…
  • 19. You
  • 21. “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
  • 22. “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
  • 23. 1 User • 100s? 1000s? • No failover • No redundancy • Too many eggs in one basket EC2 Instance Elastic IP User Amazon Route 53
  • 26. Self-managed Fully managed Amazon EC2 Amazon DynamoDB Amazon RDS Amazon Redshift Database options
  • 27. 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
  • 28. To NoSQL, or not to NoSQL?
  • 29. Start with SQL databases
  • 30. 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.
  • 31. AH HA! You said “massive amounts”
  • 32. > 5 TB in year one? Incredibly data intensive workload? OK! You might need NoSQL.
  • 33. Why else might you need NoSQL? • Super low-latency applications • Metadata-driven datasets • Highly nonrelational data • Need schema-less data constructs* • Rapid ingest of data (thousands of records/sec) • Massive amounts of data (again, in the TB range) *Need!= “It’s easier to do dev without schemas”
  • 35. Users >100 Web instance Elastic IP RDS DB instance User Amazon Route 53
  • 37. Users >1000 Web Instance RDS DB Instance Active (Multi-AZ) Availability Zone Availability Zone Web Instance RDS DB Instance Standby (Multi-AZ) Load balancer User Amazon Route 53
  • 38. Elastic Load Balancing • Highly available • 1 - 65535 • Health checks • Session stickiness • Monitoring / Logging • Secure sockets layer
  • 39. Application Load Balancer • Highly available • 1 - 65535 • Health checks • Session stickiness • Monitoring / logging • Content-based routing • Container-based apps • WebSockets • HTTP/2
  • 42. Users > 10,000s–100,000s RDS DB Instance Active (Multi-AZ) Availability Zone Availability Zone RDS DB Instance Standby (Multi-AZ) Load 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
  • 45. RDS DB Instance Active (Multi-AZ) Availability Zone Load balancer Amazon S3 Amazon CloudFront Amazon Route 53 User Shift some load around Web Instances Availability Zone Web Instances RDS DB Instance Standby (Multi-AZ)
  • 46. RDS DB Instance Active (Multi-AZ) Availability Zone Load balancer Amazon S3 Amazon CloudFront Amazon Route 53 User Shift some load around Web Instances
  • 47. 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
  • 48. 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
  • 49. 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)
  • 50. Shift some load around RDS DB Instance Active (Multi-AZ) Availability Zone Load balancer Amazon S3 Amazon CloudFront Amazon Route 53 User ElastiCache DynamoDB Web Instances
  • 51. Amazon DynamoDB • Managed NoSQL database • Provisioned throughput • Fast, predictable performance • Fully distributed, fault tolerant • JSON support • Items up to 400 KB
  • 52. 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
  • 53. Shift some load around RDS DB Instance Active (Multi-AZ) Availability Zone Load balancer Amazon S3 Amazon CloudFrontUser ElastiCache DynamoDB Web Instances Amazon Route 53
  • 54. Now that our web tier is much more lightweight, we can revisit the beginning of our talk…
  • 56. 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
  • 57. Sunday Monday Tuesday Wednesday Thursday Friday Saturday Typical weekly traffic to Amazon.com
  • 58. Sunday Monday Tuesday Wednesday Thursday Friday Saturday Typical weekly traffic to Amazon.com Provisioned capacity
  • 61. November traffic to Amazon.com 76% 24% November Provisioned capacity
  • 62. November traffic to Amazon.com November
  • 64. Users > 500,000+ Availability Zone Amazon Route 53 User Amazon S3 Amazon CloudFront Availability Zone Load 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)
  • 65. Users > 500,000+ Availability Zone Amazon Route 53 User Amazon S3 Amazon CloudFront Availability Zone Load 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)
  • 67. AWS application management solutions Convenience Control Higher-level services Do it yourself AWS Elastic Beanstalk AWS OpsWorks AWS CloudFormation Amazon EC2
  • 68. 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
  • 69. 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
  • 71. There are further improvements to be made in breaking apart our web/app layer
  • 73.
  • 74. Now that’s a lot of things to read! This is NOT where we want to start!
  • 75. This is NOT where we want to start! This IS where we want to start! Now that’s a lot of things to read!
  • 76. SOAing Move services into their own tiers. • Treat them separately • Scale them independently. It offers flexibility and greater understanding of each component
  • 77. 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
  • 78. • 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
  • 79. 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 Amazon Kinesis Pull: Amazon Kinesis Stream
  • 80. 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 • Don’t build 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
  • 82. 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 (SOA) • Serving content smartly (Amazon S3/CloudFront ) • Caching off DB • Moving state off tiers that auto scale
  • 83. Users >1 million+ RDS DB Instance Active (Multi-AZ) Availability Zone load 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
  • 84. The next big steps
  • 86. Users >5 million - 10 million Database Issues? 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)
  • 87. 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
  • 88. 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
  • 89. Shifting functionality to NoSQL • Similar in a sense to federation • 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 tables DynamoDB
  • 91. A quick review • Multi-AZ your infrastructure. • Make use of self-scaling services—ELB, Amazon S3, Amazon SNS, Amazon SQS, Amazon SWF, Amazon SES, etc. • Build in redundancy at every level. • Start with SQL. Seriously. • Cache data both inside and outside your infrastructure. • Use automation tools in your infrastructure.
  • 92. A quick review continued • Make sure you have good metrics/monitoring/logging • 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
  • 95. • 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 • AWS EC2 Container Service • AWS Lambda User >11 million
  • 100. Related Sessions DEV206 – Scaling Your Web Applications with AWS Elastic Beanstalk Tue, Nov 29, 11:00 AM – 12:00 PM – Venetian, Level 2, Opaline Theatre Thurs, Dec 1, 2:00 PM – 3:00 PM – Venetian, Level 2, Titan 2305 ARC305 – From Monolithic to Microservices: Evolving Architecture Patterns in the Cloud Wed, Nov 30, 2:00 PM – 3:00 PM – Venetian, Level 2, Venetian Theatre Fri, Dec 2, 9:00 AM – 10:00 AM – Venetian, Level 4, Lando 4205 CMP201 – Auto Scaling – The Fleet Management Solution for Planet Earth Thurs, Dec 1, 5:00 PM – 6:00 PM – Venetian, Level 2, Opaline Theatre