Performance Tuning Siebel Software on the Sun Platform

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application server. For more information on the individual <strong>Siebel</strong> components please refer to <strong>Siebel</strong> product documentation at www.siebel.com. <strong>Performance</strong> <strong>Tuning</strong> <strong>Siebel</strong> <strong>Software</strong> on the Sun Platform Page 10
3 Optimal Sun/<strong>Siebel</strong> Architecture for Benchmark Workload Sun offers a wide variety of products ranging from hardware and networks to software and storage systems. To obtain the best price/performance from an application, one needs to determine which Sun products are appropriate. This selection process can be achieved by understanding the application's characteristics, picking Sun products suitable to those application characteristics, conducting a series of tests, and then finalizing the choice of machines. For this project, tests were done to characterize web, application, and database performance across the current Sun product line. Hardware was selected based on best price/performance rather than pure performance criteria. Figure 3.1 illustrates the hardware configuration used in the Sun ETC testing. (Note: "SF" stands for Sun Fire server.) Load Generators SF V65x Web Servers SF V440/SF V880 <strong>Siebel</strong> App Servers <strong>Siebel</strong> Gateway Sun Java System Directory Server SF V890 SF V440 SF E2900 SF E2900 SF V440 SF V440 SF V480 Sun StorEdge SE 6320 Key: Network traffic between load generators and web servers Network packets between web servers to app servers Point-Point Gbic between each app server and database server Figure 3.1 <strong>Performance</strong> <strong>Tuning</strong> <strong>Siebel</strong> <strong>Software</strong> on the Sun Platform Page 11
Page 1 and 2: Performance <stron
Page 3 and 4: Abstract This paper discusses the p
Page 5 and 6: 7.6.6 Oracle Parameters Tun
Page 7 and 8: 1 Tuning for Price
Page 9: 2 Siebel Applicati
Page 13 and 14: 3.1 Hardware and Software</
Page 15 and 16: 5 10,000 Concurrent Users: Test Res
Page 17 and 18: 6 Siebel Scalabili
Page 19 and 20: Cost per Siebel Us
Page 21 and 22: 7.1 Tuning Solaris
Page 23 and 24: 7.1.3 The Solaris Kernel and TCP/IP
Page 25 and 26: In the file $SIEBEL_ROOT/bin/enu/ua
Page 27 and 28: 7.2.3 Assignment Manager Tu
Page 29 and 30: MQ series parameter tuning: PERFQMG
Page 31 and 32: Investigating the Reason for the Fa
Page 33 and 34: let a Siebel proce
Page 35 and 36: Description The reason for this sym
Page 37 and 38: Parameter Scope Default Tuned Value
Page 39 and 40: 7.6 Tuning <strong
Page 41 and 42: 86 MB/second 57 MB/second Figure 7.
Page 43 and 44: DATA_51200K INDX_512K DATA_5120K TE
Page 45 and 46: 7.6.4 Solaris MPSS Tuning</
Page 47 and 48: Siebel Object Name
Page 49 and 50: instance_name=oramst job_queue_proc
Page 51 and 52: ORAPERF.S_PRI_LST T4 WHERE T4.PAYME
Page 53 and 54: the database during peak load. In t
Page 55 and 56: use connection pooling, so you woul
Page 57 and 58: Oracle Database Server 1. Larger th
Page 59 and 60: 160 siebelapp2_1 eSalesObjMgr_enu 1
Page 61 and 62:
9.10 To Produce a Stack Trace for t
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Count indv cuml rcnt nsec Lock Call
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5. Once the user has stopped at the
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10 Appendix A: Transaction Response
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eSls1_115DDSubCategory1.3 0.125 0.1
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CC3_2newSolution 0.047 0.136 3.281
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11 Appendix B: Database Objects Gro
Page 75 and 76:
S_OPTY_BU_M8 INDEX 2,334,720 S_ORDE
Page 77 and 78:
log file parallel write 550,101 515
Page 79:
Acknowledgements Thanks to
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