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

1. DATA
ANTI
PATTERNS

2. I work with
Databases
And I’m a
happy dog!
I
S
N
O M
E
B
S
R
A
ines @ Engine Yard.com
@Randommood

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
Copy and archiving
of data
Goal is to restore
the state of a DB
Backups
Many types - blah

8. Anti-Pattern #1
Not free, they
requires resources
Full backup every
hour, really?
Taking too
What about backup
many
backups retention?

9. Anti-Pattern #2
Taking too
few
backups
Enough to minimize
the risk of data loss
due to corrupted
backup files
yes,

10. this

11. totes

12. happens!

13. Anti-Pattern #3
The untested backup

14. Doing backups right
Logically
test
backups
Errorless restore
is not enough.
Test logical data
too

15. Doing backups right
Take logical and
binary backups
Continuous archiving
Know your
hot backup utilities
types
tools

16. Doing backups right
Practice
restores
Backups alone do not
constitute DR. Have a
plan practice it
Server extensions and
configuration matter
when restoring

17. “I want a
ridiculously
good
looking
Database”
Derek Zoolander
(honestly, Ben Stiller rules)

18. Obvious statement #1
Many DB
choices

19. Anti-Pattern #4
Failure to
understand use
case, strengths
weaknesses of a
Cargo
new database
culting your
database

20. Anti-Pattern #5
Often means at least
one write per request
Tables have a
tendency to bloat
RDBMS for
Any DB issue/task may
Session
cause app to hang
Data

21. Anti-Pattern #6
Modeling, it’s all the same

22. Doing it right
Data Model
Consistency needs
Availability needs
Know your
needs
Scaling needs
Operational story
cost

23. Doing it right
Spike it,
forealsies
Spike it with your
data and traffic.
Best way to gain
operational
experience

24. Doing it right
Leverage
new
features
Relational databases
are getting quite
versatile
Evaluate clustered
MySQL options

25. We have a cloud deployment!
Happy team on shipping day, lmfao if you don’t celebrate like this

26. Obvious statement #2
Databases can live in
the cloud quite well
Many IaaS, PaaS,
DBaaS options
Cloud-based
databases,
they are real
Easy to get started
may be economical

27. Anti-Pattern #7
Where did my instance go?

28. Anti-Pattern #8
Cloud, it’s
just like
hardware
It’s not. Cloud
resources are
virtualized
Capacity planning
and monitoring
matter. A lot

29. Anti-Pattern #9
Shit doesn’t
happen
You are not
immune to
infrastructure
failures.
Plan for it

30. Anti-Pattern #10
Instance storage is
not persisted (use
EBS)
Data locality matters
Storage is
the same
Don’t run your cloud
DBs too hot!

31. Doing cloud right
Know your
cloud
deployments
Replication in the
cloud is a must-have
Put DB master
replicas in different
AZs

32. 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

33. Doing cloud right
Invest in monitoring
Know baseline
behavior
Know your
system
Know your data
distribution
querying patterns

34. Questions?