flash slides of "QMining startu empowered by appengine & amazon" QMining leverage extensivelyappengine & now amazon plateform to speedup its iterative dev process. This talk will focus on pros & con of appengine (Paas) vs amazon(IaaS).

1. (preview)
francis@qmining.com
President & CEO

2. What do we do?
● Data-Mining
● Machine
Learning
● BIGDATA
● Cloud

3. Startup context
● Low resources
● Employee cost way more then a service
● Yes we know that:
○ appengine is a PaaS (Platform as a service)
○ amazon is more a IaaS (Infrastructure)
● But it is 2 alternatives for startups

4. Subjective: Google bias
+10

5. Python framework
framework Great (app.yaml) learning curve
Score
+10 -10

6. Deployment
deployment script 173 lines (wrapper on 625 lines (using extensively
appcfg.py) boto)
deployment time < 1 minutes 2-5 minutes
need a deployment script No Yes
Score
+10 -10

7. Simple test: load generator
Issues so many limits none
Score
-10 +10

8. Scaling
Issue 500 req/sec; low None
req/instance
Score
-20 +10

9. Pricing
Issue not predictable Higher then estimated
Score
-20 +10

10. Support: Multi-tenant/openid
Issue None Nothing
Score
+10 0

11. Support https
Issue None Nothing
Score
+10 -10

12. Support: logs, alias & data access
Issue None Nothing
Score
+20 -20

13. Support BigData
Issue None error logging
Score
+10 +10

14. Conclusion
Pros ● framework ● less limits
● deployment ● Scaling
● multi-tenant ● Pricing
● https
● log & data
visualisation
General Score
+20 -20
Prototyping 2 weeks 4 months
Production
The best of both world might be heroku a Cloud application platform but we haven't tried it

15. You hate your day job?
francis@qmining.com
President & CEO