By building your application with AWS Lambda, Amazon API Gateway, and Amazon DynamoDB, you can free yourself from the burden of managing servers while gaining agility and simple scaling. After introducing the basics of building microservices with AWS Lambda and Amazon API Gateway, the session highlights how the Democratic National Committee (DNC) Technology Team uses AWS Lambda and Amazon DynamoDB microservices to provide campaigns and state parties customized applications on top of a core data platform. This serverless architecture has helped the DNC Technology Team improve their microservice functionality and development process, ensuring their applications are performant through the extremely erratic usage levels of a campaign cycle.

1. © 2016, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Ben Snively, Senior Solutions Architect, AWS
Mike Jensen, Director of Engineering, DNC
June 21, 2016
Getting Started with Serverless
Architectures

2. Agenda
• (20m) AWS serverless architectures
• Microservices and serverless technologies
• AWS Lambda
• Amazon API Gateway
• Amazon DynamoDB
• (25m) Customer Feature—DNC
• DNC Goals
• Lambda use case—voter registration
• Lambda use case—opposition research
• DynamoDB use case—donation prefills

3. Microservices architecture
The microservice architectural style is an approach to developing a
single application as a suite of small services, each running in
its own process and communicating with lightweight mechanisms,
often an HTTP resource API. These services are built around
business capabilities and independently deployable by fully
automated deployment machinery. There is a bare minimum of
centralized management of these services, which may be written
in different programming languages and use different data
storage technologies.
-- James Lewis and Martin Fowler

4. Benefits of microservices for Amazon
System operation is simple
(developers can be on-call )
Agility
(new features added quickly)
Innovation as its best
(team has time to think big)
Short build/test/release cycles
(fix problems soon)
Software architecture is easier to maintain and evolve
Scalable software
(horizontal scalability)
Fast development pace
(developers fully focused on writing code)
Customers excited
(new software releases every day!)

5. What is serverless computing?
• VMs
• Machine as the unit of scale
• Abstracts the hardware
• Containers
• Application as the unit of scale
• Abstracts the OS
• Serverless
• Functions as the unit of scale
• Abstracts the language runtime
AWS Lambda
Amazon ECS
Amazon EC2

6. Microservices and AWS Lambda
AWS Lambda + Amazon API Gateway is the easiest
way to create microservices
• Event handlers one function per event type
• Serverless back ends one function per API / path
• Data processing one function per data type

7. AWS Lambda: serverless computing
Run code without servers. Pay only for the compute time you consume. Be happy.
Triggered by events or called from APIs:
• PUT to an Amazon S3 bucket
• Updates to Amazon DynamoDB table
• Call to an Amazon API Gateway endpoint
• Mobile app back-end call
• And many more…
Makes it easy to:
• Perform real-time data processing
• Build scalable back-end services
• Glue and choreograph systems

8. Continuous
scaling
No servers to
manage
Never pay for
idle—no cold
servers (only
happy
accountants)
Benefits of AWS Lambda

9. Pay per request
• Buy compute time in
• 100 ms increments for
21 microcents
• Request charge of 20
microcents
• No hourly, daily, or
monthly minimums
• No per-device fees
Never pay for idle!
Free Tier
1 million requests and 400,000 gigabytes of
compute every month, every customer

10. Using AWS Lambda
Bring your own code
• Node.js, Java, Python
• Bring your own libraries
(even native ones)
Simple resource model
• Select power rating from
128 MB to 1.5 GB
• CPU and network allocated
proportionately
• Reports actual usage
Flexible authorization
• Securely grant access to
resources, including VPCs
• Fine-grained control over
who can call your functions
Flexible use
• Call or send events
• Integrated with other AWS
services
• Build whole serverless
ecosystems

11. Amazon API Gateway: serverless APIs
Internet
Mobile apps
Websites
Services
AWS Lambda
functions
AWS
Amazon API
Gateway cache
Endpoints on
Amazon EC2
Any other publicly
accessible endpointAmazon
CloudWatch
Amazon
CloudFront
Amazon
API Gateway

12. Benefits of Amazon API Gateway
Create a unified API
front end for
multiple
microservices
DDoS protection
and throttling for
back-end systems
Authenticate and
authorize requests

13. NoSQL database
Fully managed
Single-digit millisecond latency
Massive and seamless scalability
Low cost
Amazon
DynamoDB

14. Predictable, low latency performance
Consistent single-digit millisecond latency even at massive scales

15. Writes
Replicated continuously to 3 AZs
Persisted to disk (custom SSD)
Reads
Strongly or eventually consistent
No latency trade-off
Automatic replication for rock-solid durability and availability

16. Amazon DynamoDB is a schemaless database
Attributes
Schemaless
Schema is defined per item
Items
Table
Item
key

17. Common use cases

18. Use case: data processing
Example: Amazon S3 bucket triggers
Amazon S3 bucket events
Original object
Compressed object
1
2
3
AWS Lambda

19. Use case: automatically scalable back ends
1. AWS Mobile SDK + Amazon Cognito for mobile app
Or AWS IoT for devices
1. AWS Lambda runs the code
2. Amazon API Gateway (if you want your own endpoint)
3. Amazon DynamoDB holds the data
AWS Lambda
Amazon
DynamoDB

20. Use case: serverless web apps
1. Amazon S3 for serving static content
2. AWS Lambda for dynamic content
3. Amazon API Gateway for https access
4. Amazon DynamoDB for NoSQL data storage
Dynamic content
in AWS Lambda
Data stored in
Amazon
DynamoDB
Amazon API
Gateway
Static content in
Amazon S3

21. re:Invent 2015
• Python
• Scheduled functions
• Longer running times (5 min.)
• Versioning
Recent launches
Since re:Invent
• Higher code storage limits (from 5 GB
to 75 GB)
• Custom VPC
• 1-minute schedules
• Regional launch: Frankfurt
• Node.js 4.3.2
• 1-click CORs setup
• Stage variables
• Custom (AWS Lambda) authorizers
• Built-in Swagger import/export
• AWS CloudFormation support for API
Gateway and versions

22. Mike Jensen
Director of Engineering, DNC

23. DNC – What We Do
 Our goal is to get Democrats elected, up and down the
ballot
 The Engineering Team provides infrastructure building
and campaign support
 We meet campaigns at their level of technical expertise

24. Why We Use AWS
 Security, Stability, Scalability
 No second chances – Only one election day!

25. Application Use
Expected
Traffic
Expected
Traffic
Unexpected
Traffic
Unexpected
Traffic

26. How We Handle This
 Testing, testing, testing!
 S3 for static sites/assets
 ELBs and Auto Scaling groups
 Microservice Architecture
 New! - Lambda and DynamoDB

27. Lambda Use Case 1 – Voter Registration
 The most important data for us
 Old system – monolithic, server intensive
 Difficult to update, maintain, add feature requests

Registration
Service
IwillVote
User
Voter Laws
API
IwillVote
System
Registration
Database
VAN

28. Lambda Use Case 1 – Voter Registration
 Split out service functionality
 Voter registration processing using Lambda
 SQS backup and Lambda re-trigger
Registration
Database
IwillVote
User
Voter Laws
API
IwillVote
Service
VANRegistration
ServiceRegistration
API
Registration
Function
Registration
Queue

29. Lambda Use Case 2 – Opposition Research
 Opposition research is crucial
 Many systems require manual input
 Lambda → Ready when the event occurs
Upload
User
Processing
User
File
Uploader
Research
System
Research
Database

30. Lambda Use Case 2 – Opposition Research
 Lambda triggers on updates - processes and uploads
data
 Available to research teams immediately
 Nothing is missed
Research
System
Research
Database
S3
Triggered
Processing
Upload
User
Scraper
System
RSS
Triggered
Downloads
Research
Storage

31. Not Everything Is Perfect
 No native Ruby functions (yet) – possible, but not easy,
using Ansible, mruby, or JRuby
 Limited error reporting
 Disk space limits – larger processing jobs have to be
triggered manually on a separate system
 Refactoring applications is development intensive

32. DynamoDB – Donation Pre-fills

33. DynamoDB – Donation Pre-fills
 Campaigns/committees are funded entirely through
donations
 Election law requires extensive collection of donor data
 Our job – make it as easy as possible for people to
support Democratic groups
 Our solution – pre-fill what we can using hash id’s

34. DynamoDB – Donation Pre-fills

35. DynamoDB – Donation Pre-fills
 DynamoDB makes the easy – key/value store with
donor pre-fill data
 Fast and secure access to data
 Event based traffic – EOQ, major media events
 Scale up without downtime

36. Takeaways
 AWS is great for the operational speed of campaigns
 Lambda and DynamoDB have very specific use cases
 Additional stability and scalability for services we
provide
 We are excited for future integrations

37. Thank you!