1. Database hidden disasters…
…and planning against them
FEODOR GEORGIEV 15

2. About me Background - .NET developer Started with - SQL 2000 and DTS
Currently – SQL Server DBA for Enterprise OLTP and BI warehousing solutions 14

3. Disclaimer
Real life examples - The examples and the demos in this presentation are inspired from real life experiences, which have been enhanced for the purpose of the presentation
Lessons learned - nevertheless, to paraphrase Murphy, they can happen to anyone, anywhere, at any time
Test notes here 13

4. Diesel engines and database disasters12

5. All things start small ... The idea: Sell stuff online Hardware setup
Challenge: Setup online shopping site
Estimated size:
Hardware setup
Some disks, some memory, some CPU ...
Data management requirements
Limited user transactions (displaying products, registering users, purchasing) 11

6. Do your homework… Things to consider at this point:
Installation and settings of the hardware and software
Security policy and the volume maintenance tasks (demo)
Creating a database
Default settings… really?
Filesize, log size, growth rate
About filegroup…
Why is the PRIMARY not enough 10

7. Growing pains… The online shopping site 1 year later ...
Challenge: product inventory expansion and customer base growth
Estimated size:
Hardware setup
Add some more disks, memory, CPU
Time to rethink the setup yet?
Data requirements
Increasing volume of user transactions (displaying products, registering users, purchasing)
Store more data: browsing patterns (target users with special offers, optimize operational costs) etc 9

8. Avoid obvious mistakes
Things to consider at this point:
Backup testing – who needs it, anyway
Shrinking the DB(A)!
Passwords audit (demo)
Change management overhead
Lack of change management 8

9. More growing pains… The online shopping site 2 years later ...
Challenge: continuous product inventory expansion and customer base growth
Estimated size:
Hardware setup
Add some more disks, memory, CPU
Time to rethink the setup yet?
Data requirements
Handle increasing volume of user transactions (displaying products, registering users, purchasing)
Process new transaction types (order cancellation, refunds etc)
Store more data: track browsing patterns, product ratings (target users with special offers, optimize operational costs) etc
Prevent fraud 7

10. Zoom in on the database Get ahead of the default settings
Estimate the data throughput (new data, archived data, cost of different solutions)
A stored procedure is worth … a thousand waits
A stored procedure can reduce waits and is easily controlled 6

11. Measure twice, cut it once…
Monitoring and analysis
Setup alerts for severity greater than 17
Alert for file growth
Monitor hardware performance
Performance monitoring for applications
Benchmarking & trending 5

12. Maturity… 4 The online shopping site some years later ... Challenges:
Continuous product inventory expansion and customer base growth
Scalability
Estimated size:
Hardware setup
Add some more disks, memory, CPU
Reactive improvements to the hardware setup
Data requirements
Handle increasing volume of user transactions (displaying products, registering users, purchasing, order cancellation, refunds )
Store more data: track browsing patterns, product ratings (target users with special offers, optimize operational costs) etc
Prevent fraud
Where has my scalability been all these years?! 4

13. Recap Hardware / software considerations
Installation procedures and planning (reducing electricity costs or reducing performance?)
Instance environment
Settings, user rights, object settings
Edition selection
Application growth planning (volume, indexing, fragmentation, file grouping, scalability, reporting, monitoring, administration)
Testing (backups, releases and rollbacks etc)
Tools of the trade
Best Practice Analyzer (BPA)
System Center Advisor
Own compentence 3

14. Expect the unexpected…
Disaster recovery considerations:
Segregate data so that it takes the minimum time to restore
Consider NOT backing up the non-clustered indexes
Document the segregated components by importance
In case of a disaster, restore the most important data first 2

15. For attending this session and PASS SQLRally Nordic 2011, Stockholm
THANK YOU!
For attending this session and PASS SQLRally Nordic 2011, Stockholm 1