This document summarizes a DevOpsDays TLV 2015 Ignite Session about how Tamar Labs helped Vioozer scale their mostly-Python product from 10 users to 10 million users in 10 days. It describes the challenges of making a small-scale stateful product work at a massive scale for every phone in Tijuana, including managing critical sections, reducing state dependency, geographic matching, optimal matching of users, handling mismatches, and input grouping using various technologies like Redis, rtree, ELK, Storm, and Streamparse. The key was critical section management using Storm to allow the system to handle massive concurrency and scale.

1. Ignite Session
DevOpsDays TLV 2015

2. From
10 Users
to
10 Million
in
10 Days
Adam Lev-Libfeld // Tamar Labs // October ‘15

3. Vioozer
+
Tamar Labs

4. take a nice
mostly-pythonic
partly-stateful
relatively-small scale
product

5. make it work
for
every phone
in
Tijuana

6. active
users
live
questions

7. thinking
in
critical sections

8. minimizing state
dependency

9. a fresh take
on
geographic matching
using
a whiteboard

10. critical section #1
sample space reduction
a stateful nightmare

11. soft decisions
using
rtree

12. critical section #2
optimal matching
a business logic maze

13. hard decisions
using
redis

14. critical section #3
mismatch handling
concurrency hell

15. dehydration
from seconds to days

16. input grouping
using
ELK

17. putting it together

18. critical section
management
using
storm*

19. critical section
management
using
storm*
*streamparse

20. the value
of a single
stack choice

21. thank you
adam@tamarlabs.com
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