Disk Array Performance Estimation

1. Disk Array Performance Estimation AGH University of Science and Technology Department of Computer Science Jacek Marmuszewski Darin Nikołow, Marek Pogoda, Renata Slota, Jacek Kitowski

2. Outline • Introduction • motivation for performance estimation of disk array • problems connected with estimation of disk array • requirements for disk array estimator • Solution • Environment • Disk Array Performance Tests • Estimation Model • Estimation Quality Tests • Future work

3. Introductionmotivation for performance estimation of disk array • Proper and efficient performance estimation of storage systems is essential for many processes occurring in distributed computational environments such as: • replica selection, • new replica creation, • creating VO specifying data storage performance requirements in SLA, • guarantying the fulfillment of SLA within VO.

4. Introductionproblems connected with estimation of disk array • Complexity of algorithms used to determine best solution for storing data • Shared resources • Virtualization

5. Introductionrequirements for disk array estimator • Estimator response time • Estimator response time • Estimation quality

6. Solution • Model identification via active experiments

7. Environmentgeneral view - User / Application - Disk Array - Host / Server

8. Server 1 Xeon QuadCore 4GB RAM Test Environment Disk Array 1 • Infortrend A16F-G2430 • 2GB cache • 16x 1TB HDD – SATA, RAID6 • 2x 4/8 Gbit/s fiber channel interface • Disk Array 2 • Intel Entery Storage System SS4200-E • 4 x 500GB HDD - SATA • RAID5 • 1 Gbit Ethernet • Server 2 • Intel Core2Duo E4400 2.0Ghz • 2GB RAM

9. Test Environment Monitoring daemon Sending data using ICE Monitoring daemon Estimator Service & database Monitoring daemon ICE – Internet Communication Engine form ZeroC - Disk Array - Host / Server

10. Disk Array Performance Tests • Tests written in C • Using 'fwrite' • Synchronizing (flushing) once – before ending test usu

11. Disk Array Performance Tests

12. Disk Array Performance Tests

13. Model How to obtain those values automatically ?

14. speed Model Cache size - stored in cache - stored on HDDs size

15. Model Cache usage estimation • Monitoring i/o operation on every host! • Knowledge of NIC speed and HDDs speed Best way : Get this information directly form Disk Array

16. Model Multiple users – average bandwidth usage • Divide bandwidth equally to all hosts • On host, divide bandwidth equally to all users • If host/user in not using its all bandwidth divide it to others • Use this value as „Max Disk Array Speed” • Do the same for „Max HDD's speed” value

17. History time History time Model Multiple users – estimating future r/w speed • Don't use current speed! • Use weighted mean for statistical r/w data. speed speed s0 s1 s2 s3 s0 s1 s2 s3 time time

18. Estimation quality tests

19. Estimation quality tests

20. Estimation quality testsfor multiple users

21. Estimation quality testsfor multiple users

22. Estimation quality testsfor multiple users • Average absolute performance estimation error: 34,8 MB/s • Maximal absolute performance estimation error: 64,4 MB/s • Average absolute performance estimation error: 8,2 % • Maximal absolute performance estimation error: 13,9 % • Average estimator response time (+ ICE) = ~1.2ms ICE – Internet Communication Engine form ZeroC

23. Summary and Future Works • Collecting more data directly form Disk Array administration / diagnostic tools • Analyzing more data – searching for patterns in Disk Array usage.

24. Thank You