OakTableWorld 2013: Ultimate Exadata IO monitoring – Flash, HardDisk , & Write back cache overhead
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The document discusses monitoring input/output (IO) performance in Oracle Exadata systems. It covers write-back flash cache (WBFC), various methods for monitoring IO using Automatic Workload Repository (AWR) data and cell-level scripts, correlating IO to workload, and scaling monitoring using metric extensions and Business Intelligence Publisher (BIP). The presentation provides examples of visualizing IO performance trends over time using AWR and cell data and measuring the impact of initialization parameters on latency. It also addresses reference bands for disk IO capacity and visualizing workload activity storage area activity by day per node.
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Where Did My CPU Go?
Karl Arao presented on monitoring and capacity planning on consolidated environments. He discussed comparing CPU speeds using benchmarks like TPC-C and SPECint, the difference between cores and threads, common CPU events like CPU wait and scheduler, and tools for CPU monitoring like AWR, Tableau, vmstat and collectl. He showed examples of using these tools to analyze CPU usage across multiple hosts on a consolidated Exadata platform and identify opportunities for CPU redistribution.
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OakTableWorld 2013: Ultimate Exadata IO monitoring – Flash, HardDisk , & Write back cache overhead
- 1. Ultimate Exadata IO monitoring Flash, HardDisk , & Write back cache overhead Presented by: Karl Arao 1
- 2. whoami Karl Arao • Senior Technical Consultant @ Enkitec • Performance and Capacity Planning Enthusiast 7 years DBA experience Oracle ACE, OCP-DBA, RHCE, OakTable Blog: karlarao.wordpress.com Wiki: karlarao.tiddlyspot.com Twitter: @karlarao www.enkitec.com 2
- 4. Agenda • Performance scenario • WBFC • Different ways to Monitoring IO • AWR IO data • Correlate up to the workload and sqlstats data – feedback loop • Cell data - cell_iops.sh • Scaling it! www.enkitec.com 4
- 8. OEM12c storage grid perf www.enkitec.com 8
- 15. Tableau demo on AWR IOPS and Workload data www.enkitec.com 15
- 16. Different views of IO performance with AWR data http://goo.gl/i660CZ SECTION 1: USER IO wait class and cell single block reads latency with curve fitting SECTION 2: Small IOPS vs Large IOPS SECTION 3: Flash vs HD IOPS SECTION 4: Flash vs HD IOPS with read/write breakdown SECTION 5: IO throughput read/write MB/s SECTION 6: Drill down on smart scans affecting cell single block latency on 24hour period www.enkitec.com 16
- 17. www.enkitec.com 17 Measuring the effect of IORM on latency
- 19. www.enkitec.com 19 IORM BASIC IORM AUTO IORM LOW LATENCY
- 20. Tableau demo on Cell data - cell_iops.sh www.enkitec.com 20
- 22. How do you scale? www.enkitec.com 22
- 23. Metric Extensions + BIP www.enkitec.com 23
- 24. www.enkitec.com 24 DB and CELL IOPS/MBs comparison: 1)Create metric extensions for DB and CELL 2)Create the model 3)Graph it in Tableau and BIP 4)Schedule the email of final reports/visualization
- 26. www.enkitec.com 26 Reference band for HardDisk IOPS capacity Check the _OTHER_DATABASE_ IOPS and compare with AWR and CELL numbers for WBFC destage & flash cache metadata operations overhead
- 28. Workload AAS by day per node www.enkitec.com 28
- 29. Summary • WBFC • Different ways to Monitoring IO • AWR IO data • Correlate up to the workload and sqlstats data – feedback loop • Cell data - cell_iops.sh • Scaling it with Metric Extensions and BIP www.enkitec.com 29
- 30. References • WBFC patent http://goo.gl/2WCmw • AWR scripts and cell_iops.sh http://karlarao.wordpress.com/scripts-resources/ • SQL Developer ready AWR scripts http://goo.gl/ocv5b • Different views of IO performance with AWR data http://goo.gl/i660CZ www.enkitec.com 30
Editor's Notes
- Just a brief introduction of myself..