Mobile apps have different service requirements from their desktop and web-based analogs. Bandwidth, client processing, and other considerations can impose significant extra demands on a scalable service. This session is a technical discussion of the challenges Flipboard met while scaling a data-intensive mobile app from 0 to 100 million clients and how they are working on scaling 10x using AWS. At each major step, Flipboard has encountered many challenges. Learn about how they handled those challenges and the evolution of their systems architecture, design choices, and software selection.

1. Scaling a Mobile Web App to
100 Million Clients and Beyond
Joey Parsons @joeyparsons
November 14th, 2013
© 2013 Amazon.com, Inc. and its affiliates. All rights reserved. May not be copied, modified, or distributed in whole or in part without the express consent of Amazon.com, Inc.
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3. YOUR PERSONAL
MAGAZINE
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4. The ultimate way to discover, consume & share content
on the mobile, social web
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8. How are mobile apps different?
• WiFi vs Slow connectivity
• Variances in bandwidth and global carriers
• Taking advantage of the local cache
• Control your behavior during latency
• Fast devices — significant opportunity for
client computation
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9. Prototype Phase:
From 0 to 1M users
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10. - Amazon EC2
- Amazon S3
- Amazon RDS
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11. The Initial Launch Night
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12. Things we should have done…
• Make sure to prepare for Amazon limits if you need to
scale quickly
• Make sure your external partners understand the
volumes you’ll be accessing them
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13. Challenges
• Understanding the scale of our services
• Little to no insight into performance
• Beginning to build out tooling for Amazon EC2 but still
in its infancy
• No centralized logging or way of detecting errors
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14. Getting Started:
From 1M to 10M Users
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15. - Amazon EC2
- Amazon RDS
- Amazon S3
- Amazon CloudFront
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16. Architecture Changes
• Different services have different scale profiles — began
the shift towards microservices
• Image content moved to CloudFront
• Moved primary data store to MySQL via Amazon RDS
• Home grown bash scripts for deploys
• Focus on instrumentation
• Logging, Metrics, Monitoring followed suit
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17. SimpleDB for CMDB
Host[i-76e33611]
name[tsd01]
owner[ops]
service[OOS]
service
ami[ami-3f622f56]
type[m1.xlarge]
loc[us-east-1a]
role[flops]
subclass[opentsdb] group[0]
pool[production]
public[50.16.58.220]
private[10.60.43.18]
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Amazon Instance ID
- Name of the instance
Who owns the instance?
IS for in service, OOS for out of
What AMI was used
Type of EC2 instance
Region and Availability Zone
- Type of role
Subclass of role
Group of node
- Production, staging, dev
- Public IP address
- Private IP Address

18. Querying our CMDB
# fl-inst-describe -r flip -p production -g 0 -s IS -o ops
Domain[flipboard.prod.instances] has count[1] hosts meeting
criteria
=======================================
Servers of role flip
=======================================
Host[i-5b8ae323]: name[flip05]
owner[ops]
service[IS]
public[54.226.44.212]
private[10.78.167.211]
role[flip]
group[0] pool[production] subclass[standard]
type[c1.xlarge]
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19. The iPhone Launch Night
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20. Scaling Fast:
10M to 100M Users
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21. Storm Kafka Graphite
Kibana
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22. Architecture Changes
• Heavy focus on instrumentation of all services
• Pipeline of batch processing using Hadoop
• Pipeline of real-time processing using Storm + Kafka
• Keen focus on using appropriately sized EC2
instances
• Moving off of bash scripts, moving to puppet
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23. Mobile application instrumentation
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24. Deploy by groups
All at once?
fl-inst-upgrade -r flip -p production-q
… or …
By group?
fl-inst-upgrade -r flip -p production -g 0 -q
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25. Using CloudWatch metrics for errors
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26. Continued your deploy
fl-inst-upgrade -r flip -p production -g 1 -q
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27. Graphite for all metrics
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28. Millions of metrics with Graphite
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29. d3.js + cubism.js
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30. Monitoring via CloudWatch
Alarm in PagerDuty
Details available in PagerDuty
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31. Lessons Learned
• Use Amazon services when possible (Amazon RDS,
Amazon Redshift, Amazon Route 53)
• Use SSDs where applicable
• Understand your scale and your needs going forward
and invest in Reserved Instances (3 years!)
• But, allow flexibility for changing needs and instance
types
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32. Amazon Technologies Used
• Amazon CloudFront
• Amazon Route 53
• Amazon EC2
• Amazon S3
• Amazon Redshift
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• Amazon RDS
• Amazon SimpleDB
• Amazon SQS
• ElastiCache
• Amazon CloudWatch

33. Beyond:
From 100M Users to 1B!
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34. What’s next?
• Better use of Auto Scaling groups
• Predictive analytics — lots of signals
• Automated remediation
• Heavy focus on using the right instance types for each
service
• Take advantage of new AWS products
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35. The unknown is
exciting …
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36. Questions?
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37. AWS re:Invent 2013
Magazine
http://flip.it/NSNEi
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38. Please give us your feedback on this
presentation
MBL302
As a thank you, we will select prize
winners daily for completed surveys!
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Thank You