Data Antipatterns - All Your Base

Are you running a database in the cloud? Worried that you're doing it wrong?

Engine Yard supports a broad set of databases with flexibility for customers to modify and configure. However, freedom to adapt and extend standard functionality comes with unexpected negative consequences: modifications can seriously affect durability and performance. I've observed common problems, patterns and best practices with big (and not so big) data. I'll highlight the most common pitfalls and discuss how to avoid them.

Video for this talk is available here: http://vimeo.com/83755776

Transcript

1. ANTI PATTERNS DATA
2. ines @ Engine Yard.com @Randommood And I’m a happy dog! I N E S S O M B R A I work with Databases
3. Engine Yard
4. ZOMG, the horror!
5. .BACKUPS yes, we are going there
6. “I know you. You know you. And I know you know that I know you” White Goodman (no relationship to White October)
7. Boring Definition #1 Backups Copy and archiving of data Goal is to restore the state of a DB Many types - blah
8. Anti-Pattern #1 Taking too many backups Not free, they requires resources Full backup every hour, really? What about backup retention?
9. Anti-Pattern #2 Taking too few backups Enough to minimize the risk of data loss due to corrupted backup files yes,
10. The untested backup Anti-Pattern #3
11. Doing backups right Logically test backups Errorless restore is not enough. Test logical data too
12. Doing backups right Know your types & tools Take logical and binary backups Continuous archiving & hot backup utilities
13. Doing backups right Practice restores Backups alone do not constitute DR. Have a plan & practice it Server extensions and configuration matter when restoring
14. “I want a ridiculously good looking Database” Derek Zoolander (honestly, Ben Stiller rules)
15. Obvious statement #1 Many DB choices
16. Cargo culting your database Anti-Pattern #4 Failure to understand use case, strengths & weaknesses of a new database
17. RDBMS for Session Data Anti-Pattern #5 Often means at least one write per request Any DB issue/task may cause app to hang Tables have a tendency to bloat
18. Modeling, it’s all the same Anti-Pattern #6
19. Data Model Consistency needs Availability needs Scaling needs Operational story & cost Doing it right Know your needs
20. Doing it right Spike it, forealsies Spike it with your data and traffic. Best way to gain operational experience
21. Doing it right Leverage new features Relational databases are getting quite versatile Evaluate clustered MySQL options
22. We have a cloud deployment! Happy team on shipping day, lmfao if you don’t celebrate like this
23. Cloud-based databases, they are real Obvious statement #2 Databases can live in the cloud quite well Many IaaS, PaaS, & DBaaS options Easy to get started & may be economical
24. Where did my instance go? Anti-Pattern #7
25. Anti-Pattern #8 Cloud, it’s just like hardware It’s not. Cloud resources are virtualized Capacity planning and monitoring matter. A lot
26. Anti-Pattern #9 Shit doesn’t happen You are not immune to infrastructure failures. Plan for it
27. Anti-Pattern #10 Storage is the same Instance storage is not persisted (use EBS) Data locality matters Don’t run your cloud DBs too hot!
28. Doing cloud right Know your cloud deployments Replication in the cloud is a must-have Put DB master & replicas in different AZs
29. Doing cloud right Learn high availability & disaster recovery Get good at replica promotions (some work involved) Understand and invest in DR/HA. Know your options
30. Doing cloud right Know your system Invest in monitoring Know your data distribution & querying patterns Know baseline behavior
31. Questions?