A talk about how to create a spohisticated logging system to help you track data from several webservices in one central place. How to make the logged data searchable, so it's possible to run analytics to spot bugs in the software. It's also a story about MongoDB adoption on Youwin.com - an online bookmaker, where we integrate 30+ webservices (payment providers, game providers, etc.).

1. Creating MongoDB Based Logging System
in Webservice Heavy Environment
Arkadiusz Goralski
@MongoDB London 2013
piątek, 29 marca 13

2. Web service Heavy Environment
Web Application
Web
Server 1
Web
Server 2 ... Web
Server n
piątek, 29 marca 13

3. Web service Heavy Environment
Web Application
Web
Server 1
Web
Server 2 ... Web
Server n
Gaming Providers
Sportsbook Slots
Live Mini
betting games
Casino Poker
Live Account
dealer Management
piątek, 29 marca 13

4. Web service Heavy Environment
Web Application
Web
Server 1
Web
Server 2 ... Web
Server n
Gaming Providers Payment Providers
Sportsbook Slots Skrill Ukash Ecocard
Live Mini
Neteller Paysafe Instadebit
betting games
Bank
Casino Poker Visa Ecocard
transfers
Live Account
Mastercard Envoy Webmoney
dealer Management
piątek, 29 marca 13

5. Web service Heavy Environment
Web Application
Web
Server 1
Web
Server 2 ... Web
Server n
Gaming Providers Payment Providers Other Subsystems
Bonus Common
Sportsbook Slots Skrill Ukash Ecocard engine Wallet
Live Mini
Neteller Paysafe Instadebit Price feeds Mobile API
betting games
Bank
Casino Poker Visa Ecocard Anti fraud Geo IP
transfers
Live Account
Mastercard Envoy Webmoney
dealer Management
piątek, 29 marca 13

6. Different dialects
SOAP JSON RPC
Web
REST JSON XML RPC
Application
REST XML HTTP Calls
piątek, 29 marca 13

7. How to keep sanity?
• why the deposit failed for user ... ?
• user ... claims he didn’t place this bet?
• can you give me a number of users that ... ?
• can you tell me what user ... was doing on ... ?
• why user ... couldn’t log in?
• why customer ... couldn’t open an account?
piątek, 29 marca 13

8. Why MongoDB
is a good fit
• schemaless
• fire and forget
• scalable and easy to replicate
• capped collections & tailable cursor
• centralized
• easy remote access
piątek, 29 marca 13

9. MongoDB deployment
Web Application
Web
Server 1
Web
Server 2 ... Web
Server n
piątek, 29 marca 13

10. MongoDB deployment
Web Application
Web
Server 1
Web
Server 2 ... Web
Server n
Replica Set
Payment Providers
MongoDB MongoDB MongoDB MongoDB
(host 1) (host 2) (host 3) (hidden)
piątek, 29 marca 13

11. MongoDB deployment
Web Application
Web
Server 1
Web
Server 2 ... Web
Server n
Replica Set
Payment Providers
MongoDB MongoDB MongoDB MongoDB
(host 1) (host 2) (host 3) (hidden)
Log Viewer
RealPayment Providers
time Simple Simple Real time
log viewer queries reports alerts
Secondary preferred
piątek, 29 marca 13

12. MongoDB deployment
Web Application
Web
Server 1
Web
Server 2 ... Web
Server n
Replica Set
Payment Providers
MongoDB MongoDB MongoDB MongoDB
(host 1) (host 2) (host 3) (hidden)
Log Viewer Data mining
RealPayment Providers
time Simple Simple Real time Payment Providers
Heavy
Analytics
log viewer queries reports alerts queries
Secondary preferred Hidden node only
piątek, 29 marca 13

13. Log entry schema
piątek, 29 marca 13

14. Log entry schema
Prepare web
service request
piątek, 29 marca 13

15. Log entry schema
Prepare web
service request
JSON-ize Send it
piątek, 29 marca 13

16. Log entry schema
Prepare web
service request
JSON-ize Send it
JSON-ize Get the result
piątek, 29 marca 13

17. Log entry schema
Prepare web
service request
JSON-ize Send it
JSON-ize Get the result
Was is
successful
piątek, 29 marca 13

18. Log entry schema
Prepare web
service request
JSON-ize Send it
JSON-ize Get the result
Was is
successful
Proceed with
Save it execution
piątek, 29 marca 13

19. So you're logging data to
MongoDB, now what?
• all data is searchable (including web service
specific data)
• you can use the aggregation framework
• trace user sessions across different web
services
• just sit and watch the logs
piątek, 29 marca 13

20. Detect anomalies
in the data
• realtime issue analysis
• subsystem failures
• fraud
• traffic anomalies
piątek, 29 marca 13

21. Data mining
• create a replica for analytics
• analyze customer behaviour
• spot fraudulent activity
• create reports
• proactive support
• deployment analytics
• police enquiries
piątek, 29 marca 13

22. Share the logs
• don’t be a human interface to MongoDB
• the more you share the more time is
saved, your time
• just a simple query interface is enough
• give separate node to marketing people
piątek, 29 marca 13

23. Push notifications
When something goes really bad
Alert Scenarios
Email
Tailable cursor
Node.js Severity Text
MongoDB
app rating message
Call people,
it's serious!
piątek, 29 marca 13

24. Open Source
Alternatives
• GrayLog (uses MongoDB)
• LogStash (MongoDB output plugins)
• Fluent (MongoDB storage)
piątek, 29 marca 13

25. Thank you
Have fun with MongoDB
piątek, 29 marca 13