1. Where to Start, What You Need
Baseline Basics:
Where to Start, What You Need
Erin Stellato
Senior Database Engineer
Hyland Software, Inc.

2. Erin Stellato erin@erinstellato.com @erinstellato
Blog:
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3. Storage and Application
Once Upon a Time…
Windows 2003
Windows 2008 R2
Server
SQL Server 2000
SQL Server 2008
SQL Server
Stayed the same
Storage and Application

4. What’s a Baseline?
Data that represents the “normal” or typical state of the environment
Not a point in time; data is captured over time and averaged
You will have multiple baselines
e.g. business hours, end of month, peak

5. Why Baseline?
Reference point for determining whether performance is better or worse going forward
Determine usage patterns, trending
Starting point for growth and capacity planning
Establishing a Performance Baseline

6. Who?

7. Why you? Establishing a Performance Baseline

8. What data, and from where?
PerfMon
CPU
Memory
Disk
SQL Server Counters
Trace
DMVs
Wait stats, database info, index usage

9. How? How do you capture the data? How often?
How long should it be kept?
How should the data be analyzed?

10. When? It depends… DBA resources Business cycle
Volatility of the environment

11. Roadmap PerfMon PAL Trace ClearTrace RMLUtils Qure DMVs WhoIsActive
All utilities are included with Windows or SQL Server or are free

12. PerfMon
First determine the counters you want to capture

13. Kevin Kline – PerfMon Counters
PDF

15. PerfMon Counters(1) Processor - % Processor Time
System - Processor Queue Length

16. PerfMon Counters(2) Memory – Available Mbytes Paging File - % Usage
SQL Server: Buffer Manager – Page Life Expectancy
SQL Server: Memory Manager
Total Server Memory
Target Server Memory

17. PerfMon Counters(3) Physical Disk Avg Disk sec/Read Avg Disk sec/Write
Disk Reads/sec
Disk Writes/sec

18. PerfMon Counters(4) SQL Server: Access Methods Page Splits/sec
Page Allocated/sec
Range Scans/sec
Full Scans/sec
Index Searches/sec

19. PerfMon Counters(5) SQL Server: SQL Statistics Compilations/sec
Recompilations/sec
SQL Server: General Statistics – User Connections
SQL Server: Databases – Transactions/sec

20. PerfMon Determine: the counters you want to capture the frequency
the duration to capture
when to capture
Be consistent

21. PerfMon Data Analysis
Excel
Database
PAL

23. PerfMon Data Analysis – Database
(demo)
SQL Server Native Client cannot be used with perfmon. Perfmon is a Windows tool that can only be used with DSNs that use the MDAC SQLODBC driver included with Windows.
Relog:

24. Performance Analysis of Logs (PAL)
Available from Codeplex
Utilizes PowerShell
GUI interface, creates HTML output with data and graphs
Analyzes PerfMon data for thresholds
Use default templates, or can create your own
(demo)

25. Trace Capture baselines Utilize when performance issues arise
Set up template for live tracing
Always filter
Profiler GUI vs. trace
Server side vs. Client side
Grant Fritchey – Set up and Schedule a Server Side Trace

26. Trace Data Analysis
Database
ClearTrace
RMLUtils
Qure
(demo)

27. Profiler Data Analysis – ClearTrace
Developed by Bill Graziano
Available from ScaleSQL consulting site
In a 2008 R2 instance, data from 2005 can be imported
(demo)

28. Profiler Data Analysis – RML Utilities
Developed by Microsoft
Used by Customer Service and Support (CSS)
SQL 2008R2 can only import files from the same release
(demo)
x86:
x64:

29. Profiler Data Analysis – Qure
Developed by DBSophic
Useful when you want to compare two trace files
(demo)

30. DMVs Information does not between persist between restarts
Requires VIEW SERVER STATE permission
Excellent references:
Glenn Berry
Tim Ford
Glenn Berry
Tim Ford:

31. DMVs Determine what data you want to capture Wait stats File stats
Table reads/writes
Index usage
Snapshot the data to a table at regular intervals
Store in a separate database
(demo)
Wait stats post from Paul Randal:

32. DMVs – Bad NC Indexes Output

33. WhoIsActive Developed by Adam Machanic
Useful for troubleshooting and obtaining some baseline information
(demo)

34. WhoIsActive: sessions
Kendra Little post for creating destination table:

35. Summary Determine what is most important to baseline and capture
Start simple, work up
Be consistent
Have scripts/methods at the ready to check current values when problems strike

36. Thank you!