From understanding reliability and availability, this talks walks you through the why and the how of building multi-region, active-active applications, and especially why serverless is a great fit.

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Adrian Hornsby, Cloud Architecture Evangelist
@adhorn
Building Global, Multi-Region
Serverless Backends
(powered by DynamoDB Global Tables)

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Session objectives
1. Understand System Reliability and Availability.
2. Understand why we build a Multi-Region Active-Active architecture.
3. Understand how to build a Multi-Region Active-Active architecture on
AWS.
4. Hands-on Demo: Building Multi-Region Serverless App.
5. Conclusion.

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System Reliability and Availability

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Failures are a given and
everything will eventually
fail over time.
Werner Vogels
CTO – Amazon.com
“ “

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System failure rate
Early Failures
Wear Out Failures
Observed Failures
Random Failures

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System failure rate
For high-velocity deployments
Early Failures
Wear Out Failures
Observed Failures
Random Failures

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System Availability
Availability =
Normal Operation Time
Total Time
MTBF**
MTBF** + MTTR*
=
* Mean Time To Repair (MTTR)
**Mean Time Between Failure (MTBF)

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Availability
Availability Downtime per year Categories
95% (1-nine) 18 days 6 hours
Batch processing, Data extraction,
Load jobs.
99% (2-nines) 3 days 15 hours Internal Tools, Project Tracking
99.9% (3-nines) 8 hours 45 minutes Online Commerce
99.99% (4-nines) 52 minutes Video Delivery, Broadcast systems
99.999% (5-nines) 5 minutes Telecom Industry (ATM Transactions)
99.9999% (6-nines) 31 seconds Answering to my loved one*
* Joke 
http://royal.pingdom.com/wp-content/uploads/2015/04/pingdom_uptime_cheat_sheet.pdf

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Availability in Series
Part X Part Y
A = Ax Ay

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Availability in Series
Component Availability Downtime
X 99% (2-nines) 3 days 15 hours
Y 99.99% (4-nines) 52 minutes
X and Y Combined 98.99% 3 days 16 hours 33 minutes

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Availability in Parallel
A = 1 – (1 – Ax)2
Part X
Part X

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Availability in Parallel
Component Availability Downtime
X 99% (2-nines) 3 days 15 hours
Two X in parallel 99.99% (4-nines) 52 minutes
Three X in parallel 99.9999% (6-nines) 31 seconds

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“Component redundancy increases
availability significantly!”

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Availability Zone A Availability Zone B Availability Zone C
AWS Region

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Availability Zone A Availability Zone B Availability Zone C
Multi-AZ Well-Architected
Application

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Amazon
DynamoDB
Amazon
RDS
Amazon
ElastiCache
Amazon
S3
Amazon
EFS
Amazon
SQS
Amazon
Kinesis
Amazon
ElasticSearc
h
Default
Configurable for multi-
AZ deployment
Some of the Regional AWS Services
AWS
Lambda
Amazon
API Gateway
AWS
ELB

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Regional services
AZ1 AZ2 AZ3
Service XYZ

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No servers to provision
or manage
Scales with usage
Never pay for idle Availability and fault
tolerance built in
Why Serverless components??

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• 18 Geographic Regions
• 50 Availability Zones (AZs)
• 4 regions and 12 more Availability Zones announced

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Cost of Availability (approx.)
Cost
Availability
Complexity

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Generally speaking a reliable machine has high
availability but an available machine may or may
not be very reliable.

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On reliability
Ability of a system to :
1. Recover from infrastructure or service disruptions
2. Dynamically acquire computing resources to meet demand
3. Mitigate disruptions such as misconfigurations or transient network issues.

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2 important lesson learned

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Exponential Backoff

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Message passing for async. patterns
A
Queue
B
A
Queue
BListener
Pub-Sub

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Web
Instances
Worker
Instance
Worker
Instance
Queue
API
Instance
API
Instance
API
Instance
API: {DO foo}
PUT JOB: {JobID: 0001, Task: DO foo}
API: {JobID: 0001}
GET JOB: {JobID: 0001, Task: DO foo}
Cache
Result:
{
JobID: 0001,
Result: bar
}

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Worker
Instance
Worker
Instance
Queue
API
Instance
API
Instance
API
Instance
Cache
Amazon SNS
Push Notification
User

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Well-Architected Framework
Operational Excellence
Security
Reliability
Performance Efficiency
Cost Optimization

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Why build a Multi-Region
Active-Active architecture?

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Why Multi-Region?
1. Improve Latency for end-users

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Why Multi-Region?
1. Improve Latency for end-users
2. Disaster Recovery
Applications in
US West
Applications in
US East
Users from
San
Francisco
Users from
New York
Service 1
Service 2
Service 3
Service 4
Service 1
Service 2
Service 3
Service 4

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Why Multi-Region?
1. Improve Latency for end-users
2. Disaster Recovery
3. Business Requirements

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Netflix 2013

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Netflix 2016

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Chaos Engineering

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How to build a Multi-Region Architecture on
AWS.

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Data Replication
Component A
Component B
Component C
Latency < 5 ms
Synchronous Asynchronous
Latency > 5 ms

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Process A Process B Process A Process B
Synchronous Asynchronous
Waiting
Working
Continues
get or fetch resultGet result

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Reliable & Secure Network
AWS Region
A
AWS Region
B
Amazon Global Network

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James Hamilton – 2016 re:Invent
Vice President & Distinguished Engineer

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Multi-Region Multi-VPC Connectivity

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S3 - Cross-Region Replication

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Cross-Region Read Replicas for Amazon RDS
** For Aurora, MySQL,
MariaDB and PostgreSQL
engines.

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“Simple” Cross-Region Usage Pattern
• Regional Reads
• All critical writes traffic to
a single master

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Aurora multi-master - scale out reads & writes
First MySQL compatible DB service with scale-out across multiple data centers
Zero application downtime from ANY instance failure
Zero application downtime from ANY AZ failure
Faster write performance and higher scale
Sign up for single-region multi-master preview today;
Multi-Region Multi-Master coming in 2018
Availability
Zone 1
Scale out both reads and writes
Availability
Zone 2
Availability
Zone 3
Application
Read/Write
Master 1
Shared distributed storage volume
Read/Write
Master 2
Read/Write
Master 3

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Amazon DynamoDB
Fast and flexible NoSQL database service for any scale
Fast, consistent performanceHighly scalable Fully managed Business critical
reliability
Consistent single-digit millisecond
latency; DAX in-memory
performance reduces response
times to microseconds
Auto-scaling to hundreds of
terabytes of data that serve
millions of requests per second
Automatic provisioning,
infrastructure
management, scaling,
and configuration with
zero downtime
Data is replicated across
fault tolerant Availability
Zones, with fine-grained
access control

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Prime Day 2017 Metrics
Block Storage – Use of Amazon Elastic Block Store (EBS) grew by 40% year-over-year, with
aggregate data transfer jumping to 52 petabytes (a 50% increase) for the day and total I/O requests
rising to 835 million (a 30% increase).
NoSQL Database – Amazon DynamoDB requests from Alexa, the Amazon.com sites, and the
Amazon fulfillment centers totaled 3.34 trillion, peaking at 12.9 million per second.
Stack Creation – Nearly 31,000 AWS CloudFormation stacks were created for Prime Day in order to
bring additional AWS resources on line.
API Usage – AWS CloudTrail processed over 50 billion events and tracked more than 419 billion, all
in support of Prime Day.
Configuration Tracking – AWS Config generated over 14 million Configuration items for AWS
resources.

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Amazon DynamoDB Global Tables (GA)
First fully managed, multi-master, multi-region database
Build high performance, globally distributed applications
Low latency reads & writes to locally available tables
Disaster proof with multi-region redundancy
Easy to set up and no application rewrites required
Globally dispersed users
Replica (N. America)
Replica (Europe)
Replica (Asia)
Global App
Global Table

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Amazon DynamoDB Streams
• Each stream record appears exactly once in the stream.
• For each item that is modified in a DynamoDB table, the
stream records appear in the same sequence as the actual
modifications to the item
Amazon
DynamoDB
AWS
Lambda
Streams

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Amazon Route 53
• AWS’s Authoritative Domain Name Service.
• Highly available and scalable.
• Supports Traffic Flow through a variety of routing, all of
which can be combined with DNS Failover.
• Enable a variety of low-latency, fault-tolerant
architectures.

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Traffic Routing with Route53
1. Latency Based Routing
Amazon
Route53
Resource A
Resource B

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Traffic Routing with Route53
1. Latency Based Routing
2. Geo DNS
Amazon
Route53
Resource A
In US
Resource B
in EU
User in US

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Traffic Routing with Route53
1. Latency Based Routing
2. Geo DNS
3. Weighted Round Robin
Amazon
Route53
Resource A
In US
Resource B
in EU

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Traffic Routing with Route53
1. Latency Based Routing
2. Geo DNS
3. Weighted Round Robin
4. DNS Failover
Amazon
Route53
Resource A
In US
Resource B
in EU
User in US

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us-west-2
us-east-1
Client
Amazon
Route 53
Regional
API
Endpoint
Regional
API
Endpoint
Custom
Domain
Name
Custom
Domain
Name
API Gateway
API Gateway
Lambda
Lambda
Multi-Region with API Gateway

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Hands-on Demo:
Building Multi-Region Serverless Application

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Amazon
DynamoDB
AWS LambdaAmazon API
Gateway
Amazon
DynamoDB
AWS LambdaAmazon API
Gateway
Amazon
Route53
eu-west-1
us-east-1
GlobalTables
https://globalddb.adhorn.me/

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Amazon
DynamoDB
Amazon
DynamoDB
eu-west-1
us-east-1
GlobalTables

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Amazon
DynamoDB
AWS LambdaAmazon API
Gateway
Amazon
DynamoDB
AWS LambdaAmazon API
Gateway
eu-west-1
us-east-1
GlobalTables

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AWS Lambda Function

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Amazon
DynamoDB
AWS LambdaAmazon API
Gateway
Amazon
DynamoDB
AWS LambdaAmazon API
Gateway
Amazon
Route53
eu-west-1
us-east-1
GlobalTables
https://globalddb.adhorn.me/

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Route53: Traffic Policy

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Conclusion

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We learned about
1. System Reliability and Availability.
2. Why to build a Multi-Region Active-Active architecture.
3. How to build a Multi-Region Active-Active architecture on AWS.
4. We looked at a Multi-Region Serverless App

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Go Build!
@adhorn