View this presentation to understand how technological innovation can mean rapid intervention in situations that threaten lives. View examples from two customers that use AWS in very different situations who are both able to move quickly to address pressing societal problems partially due to their implementation of AWS and their reliance to mobile technology that allows them to scale beyond their own staff and resources and accelerate impact.

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Herman Coomans, Senior Solutions Architect, AWS
Michael Jenkins, Chief Architect (VINE), Emergency Management Victoria
Kristin Boorse, Senior Product Manager, THORN
June 21, 2016
AWS Customers Saving Lives with
Mobile Technology

2. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Michael Jenkins, Chief Architect (VINE)
Emergency Management Victoria
June 21, 2016
Emergency Management in AWS
From on-premises, to elastic, to serverless

3. “Leading emergency management in Victoria
by working with communities, government,
agencies and business to strengthen their
capacity to withstand, plan for, respond to and
recover from emergencies”.
June 2016

4. Emergency Management Victoria Image Credit: Simon Yeo
https://www.flickr.com/photos/smjb/5418501102/

5. Demand is sudden and unpredictable

7. Our journey to the future
2012
Traditional web
app, on premises
2014
Elastic web app,
improved
functionality
2016
Serverless
SPA/mobile,
inherently
available and
scalable
Quality
- Reliability
- Performance
- Simplicity
Functionality
Fire-only All hazards Preparation and recovery
2014
Elastic mobile
app back end

8. 2012 – Original on-premises web app

9. 2014 – Design principles
Design for resilience
• Reduce single points of failure
• Use Amazon CloudFront to reduce the compute dependency during
high demand and simplify security design
• Design for multiple Availability Zones and regions from day one
Design for capacity
• Deliver the application tier with Auto Scaling groups and load
balance evenly over the availability zones
Separate data integration from delivery
• Ensure the system can evolve with new data services, while
decoupling the delivery tier from these data services

10. AWS Cloud
Availability Zone
Amazon EC2
Data Integration
Server
Availability Zone
Auto scaling Group
Amazon CloudFront CDN
http://emergency.vic.gov.au
Amazon EC2
Web Application
Auto scaling Group
Amazon EC2
Mapping Cache
Application
Availability Zone
Auto scaling Group
Amazon EC2
Web Application
Auto scaling Group
Amazon EC2
Mapping Cache
Application
Amazon EC2
MySQL Database
(Read-Write)
Amazon EC2
Mapping
Application
Amazon EC2
MySQL Database
(Read Replica)
Availability Zone
Amazon EC2
MySQL Database
(Fail Over)
Availability Zone
Amazon EC2
MySQL Database
Data Integration
Amazon EC2
Proprietary
Integration Server
2014 – Elastic version of the website

11. 2014 – Elastic mobile back end
Push Notif Broker
APNS
iOS
GCM
Android
Auto Scaling action
• +100% instances
• 5m grace & cooldown
Total fire ban
Amazon SQS queue
Incidents / warnings
Amazon SQS queue
Master node Slave nodes
Sender nodes
Notif batches
Amazon SQS queue
Auto Scaling action
• +50% instances
• 5 m grace and cooldown
Amazon CloudWatch alarm
• > 1000 messages
Auto Scaling action
• +200% instances
• 5m grace & cooldown
Amazon CloudWatch alarm
• > 2000 messages
End user
OSOM feed
Incident
Amazon CloudWatch alarm
• > 500 messages

12. 2016 – Design principles
Design for serverless operation
• Reduce architectural complexity and points of failure further
• Minimise the infrastructure costs, particularly the “at rest” cost
• Reduce time to scale / respond to usage spikes
Design for zero maintenance
• Remove servers and software to eliminate patching, security
management, and maintenance
Design for a single-page web application and mobile
• Trust the client to compose and manage the application
• Mobile responsive and native application
Build a foundation for future functionality
• Start with a clean slate with well defined interfaces for extension

13. 2016 – Serverless version of the web site
AWS Cloud
AP-SouthEast-2 Region
Amazon CloudFront CDN
http://emergency.vic.gov.au
Behavior 1
/2013-01-01
Behavior 2
/
Amazon S3 Object Store
Bucket: public-info
/em-public
Static resources for web
site (HTML, CSS JS)
/data
Dynamic data sets for
web site (JSON)
Amazon CloudSearch
EM-Public Search
Vicmap
Address
Vicmap
Locality
Vicmap
Postcode
Vicmap
Township
Amazon Route
53
emergency.vic.
gov.au
AWS Lambda
Data Integration Suite
EM-Public-Feed (OSOM processor)
AP-NorthEast-1 Region
AP-SouthEast-2 Region
Virtual Private Cloud
Amazon EC2
Content Management
System

14. Virtual Private Cloud
AWS Cloud
Amazon Dynamo DB
Notification Batch Audit
Email Batch SMS Batch
Push
Notification
Batch
AWS Lambda
Event Processing Suite
AP-SouthEast-2 Region
Virtual Private Cloud
Amazon EC2
Content Management
System
AP-NorthEast-1 RegionAP-SouthEast-2 Region
Amazon CloudFront CDN
http://em-public.ci.devcop.em.vic.gov.au
Search Behaviour
/2013-01-01
Site Behaviour
/
Amazon S3 Object Store
Bucket: public-info
/
Site resources
/public
Dynamic data
Amazon CloudSearch
EM-Public Search
Vicmap
Address
Vicmap
Locality
Vicmap
Postcode
Vicmap
Township
Amazon Route
53
devcop.em.vic.
gov.au
AWS Lambda
Data Integration Suite
EM-Public-Feed (OSOM processor)
AP-NorthEast-1 Region
Amazon API Gateway
EM-Public API
/user
(create)
/user/login
/user/
delete
/user/verify
API Behaviour
/api
/user/
pwreset
/user/
update
AWS Lambda
User Management Suite
User Login
User
Delete
User Verify
User
Password
Reset
User
Disable
User
Create
User
Update
Amazon SNS
Event Trigger
SES Email
Delivery
SES Email
Delivery
/site
CMS site
Amazon PostgreSQL RDS
User & Geospatial Database
User Data Watch Zones Audit
Event-Watch
Zone Matcher
& Batcher
Email Bounce
Processor
Email Batch
Delivery
Processor
2016+ – Serverless website + mobile and API

15. “…had been outside just 20
minutes earlier checking…”
“… just 30-40 m away from the
house.”
“Without the app we wouldn’t
have known.”

16. Thank you!

17. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Kristin Boorse
June 21, 2016
Spotlight
USING MACHINE LEARNING AND NATURAL LANGUAGE
PROCESSING TO COMBAT HUMAN TRAFFICKING: GOING MOBILE

18. THORN
DRIVES TECHNOLOGY
INNOVATION TO FIGHT CHILD
SEXUAL EXPLOITATION.

19. MORE THAN 100,000 NEW ADS POSTED EVERY DAY IN
THE ESCORT SERVICES SECTION OF BACKPAGE.COM
*Thorn Survivor Survey (2012)
OF THE UNDERAGE SEX TRAFFICKING VICTIMS
SAID THEY HAD BEEN ADVERTISED OR
SOLD ONLINE*
LAW ENFORCEMENT DOESN’T HAVE ENOUGH
TIME TO NAVIGATE THE ONLINE COMMERCIAL
SEX MARKET TO FIND CHILDREN AND
IDENTIFY THEIR TRAFFICKERS.
1OO,OOO+
To provide law enforcement with intelligence and leads about suspected human trafficking networks and
individuals in order to identify victims and connect them with resources.
MISSION
The problem

20. POWERED BY THORN AND
DIGITAL REASONING

21. Placeholder Spotlight Video

22. 42%
INVESTIGATORS REPORT A TIME
SAVINGS OF 42% IN THEIR HUMAN
TRAFFICKING INVESTIGATIONS
POWERED BY THORN AND DIGITAL
REASONING
Look how far we have come…

23. Going mobile

24. 2,500+
LAW ENFORCEMENT
INVESTIGATORS
50
STATES USING
SPOTLIGHT
600+
AGENCIES USING
SPOTLIGHT
860+
SPOTLIGHT ASSISTED
INVESTIGATIONS
300+
VICTIMS IDENTIFIED
63+
TRAFFICKERS
IDENTIFIED
*Thorn October 2015 user survey, with an 9% response rate
Results since launch

25. Thank you!