Obama for America를 통해서 본 AWS에서의 데이터 분석 (정윤진 책임, Solutions Architect)

1. Obama For America on AWS
Younjin Jeong
Solutions Architect

2. What am I talking about today?
What was OFA? Why is this relevant?
• Who did it?
• What did they build?
How did they do that?
• Technologies and Tradeoffs
• Services vs. Software
What did they learn from building something so big?

3. Full Disclosure
I work for AWS
AWS does not endorse
political candidates
Yes, I talk too much

4. So here’s the Idea
~30th biggest E-commerce operation, globally
~200 distinct new applications, many mobile
Hundreds of new, untested analytical approaches
Processing hundreds of TB of data on thousands of servers
Spikes of hundreds of thousands of concurrent users
FUN FUN FUN

5. a few constraints…
~30th biggest E-commerce operation, globally
~200 distinct applications, many mobile
Hundreds of new, untested analytical approaches
Processing hundreds of TB of data on thousands of servers
Spikes of hundreds of thousands of concurrent users
Critically compressed budget
Less than a year to execute
Volunteer and near-volunteer development team
Core systems will be used for a single critical day
Constitutionally-mandated completion date
NOT
NOT

6. CHALLENGE ACCEPTED !

7. Built by guys and gals like these: Obama For America

8. Business as usual..
…for a technology startup

9. Election Day – OFA Headquarters

10. So they built it all, and it worked

12. Typical Charts

14. How?

15. The old approach, even from Amazon 

16. The old approach.. Might have some problems..

17. Cloud Computing Benefits
No Up-Front
Capital Expense
Low Cost
Pay Only for
What You Use
Self-Service
Infrastructure
Easily Scale
Up and Down
Improve Agility &
Time-to-Market
Deploy

18. OFA’s Infrastructure
awsofa.info

19. Web-Scale Applications

20. 500k+ IOPS DB Systems

21. Services API

22. Ingredients
Ubuntu nginx boundary Unity jQuery SQLServer hbase
NewRelic EC2 node.js Cybersource hive ElasticSearch
Ruby Twilio EE S3 ELB boto Magento PHP EMR SES
Route53 SimpleDB Campfire nagios Paypal CentOS
CloudSearch levelDB mongoDB python securitygroups
Usahidhi PostgresSQL Github apache bootstrap SNS
cloudformation Jekyll RoR EBS FPS VPC Mashery
Vertica RDS Optimizely MySQL puppet tsunamiUDP R
asgard cloudwatch ElastiCache cloudopt SQS cloudinit
DirectConnect BSD rsync STS Objective-C dynamoDB

23. Data Stores
Ubuntu nginx boundary Unity jQuery SQLServer hbase
NewRelic EC2 node.js Cybersource hive ElasticSearch
Ruby Twilio EE S3 ELB boto Magento PHP EMR SES
Route53 SimpleDB Campfire nagios Paypal CentOS
CloudSearch levelDB mongoDB python securitygroups
Usahidhi PostgresSQL Github apache bootstrap SNS
cloudformation Jekyll RoR EBS FPS VPC Mashery
Vertica RDS Optimizely MySQL puppet tsunamiUDP R
asgard cloudwatch ElastiCache cloudopt SQS cloudinit
DirectConnect BSD rsync STS Objective-C dynamoDB

24. Development Frameworks
Ubuntu nginx boundary Unity jQuery SQLServer hbase
NewRelic EC2 node.js Cybersource hive ElasticSearch
Ruby Twilio EE S3 ELB boto Magento PHP EMR SES
Route53 SimpleDB Campfire nagios Paypal CentOS
CloudSearch levelDB mongoDB python securitygroups
Usahidhi PostgresSQL Github apache bootstrap SNS
cloudformation Jekyll RoR EBS FPS VPC Mashery
Vertica RDS Optimizely MySQL puppet tsunamiUDP R
asgard cloudwatch ElastiCache cloudopt SQS cloudinit
DirectConnect BSD rsync STS Objective-C dynamoDB

25. Sites
Communications
Ad Targeting
Ops Tools
Analytics
Apps
Micro-targeting
Micro-listening
Reporting
Registrations
Volunteer
Coordination
Etc, etc, etc.

26. Technology Choice
Polyglot Development
Cloud Hosting
Expected Tradeoff
More Complex Ops
Diverse, App-centered
Databases
Less Infra Control,
performance
More Complex Ops,
Fragility, Data Corruption
SOA, queue-based system
integrations
Dev Complexity, slower
system performance

27. Technology Choice
Polyglot
Development
Cloud Hosting
Diverse, Appcentered Databases
SOA, queue-based
system integrations
Expected Tradeoff
More Complex
Ops
Upside
Build as little as
possible, rev-1 faster,
reuse dev skills
Less Infra Control,
performance
More Complex
Ops, Fragility,
Data Corruption
Scale, Speed, Cost
Dev Complexity,
slower system
performance
Scalability,
serviceability,
operational
flexibility, and
substantially faster
in aggregate
Heterogeneous
Resilience, right
tools for the job

30. No time to waste

31. This applies to lots of services!
ELB
ElastiCache
RDS
CloudSearch
Route53
S3
CloudFront
DynamoDB
You can mostly do
these on your own…
But do you have extra:
focus, expertise, time, research,
money, risk-tolerance, staff,
dedication to
innovate, operations coverage, scalability in design...

32. Looks pretty simple.
Inserts 7.5m records in DynamoDB, in 8 minutes

33. One thing that is difficult to prepare for…

34. No pressure…

35. They had this built for the previous 3
months, all on the East Coast.

36. They had this built for the previous 3
months, all on the East Coast.
We built this
part in 9 hours
to be safe.
AWS +
Puppet +
Netflix Asgard +
CloudOpt +
DevOps =
Cross-Continent FaultTolerance On-Demand

38. Replication across the continent..
http://tsunami-udp.sourceforge.net/

39. So what did they learn?
Game Day: Practice failures so you know what to do.
Loose-Coupling: Ops easy, scale easy, test easy, fix easy…
Fail-Forward: features, quality, and focus are all critical.
HA in Depth: S3 static pages, de-coupled UI, jekyll/hyde
Cloud works.

40. What will you do next?

41. Maybe look at some of their Ruby code?
https://github.com/democrats/voter-registration

42. AMAZON REDSHIFT

43. AMAZON REDSHIFT
Redshift runs on HS type instances
HS1.8XL: 128 Go RAM, 16 Coeurs, 16 To de contenu compressé, 2 Go/sec en lecture
HS1.XL: 16 Go RAM, 2 Coeurs, 2 To de contenu compressé

44. Extra Large Node
(HS1.XL)
Single node
Cluster 2-32 Nodes (4 To – 64 To)
Eight Extra Large Node (HS1.8XL)
Cluster 2-100 Nodes (32 To – 1.6 Po)

45. JDBC/ODBC
10 GigE
(HPC)
Ingestion
Backup
Restoration
Amazon DynamoDB

52. AMAZON EC2
AMAZON
DYNAMODB
AMAZON RDS
AMAZON ELASTIC
MAPREDUCE
AMAZON
REDSHIFT
AMAZON S3
AWS STORAGE
GATEWAY
DATA CENTER

53. Thank you!
Younjin Jeong - AWS
younjin@amazon.com