Performance Tuning Siebel Software on the Sun Platform

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Introduction To ensure that the most demanding global enterprise customers can meet their deployment requirements, engineers from <strong>Siebel</strong> Systems and Sun are working jointly on several engineering projects. Their common goal is to further enhance <strong>Siebel</strong> server performance on Sun’s highly-scalable Solaris Operating System. This article is an effort to document and spread knowledge of tuning and optimizing <strong>Siebel</strong> 7 eBusiness Applications Suite on the Solaris platform. All of the techniques discussed here are lessons learned from a series of performance tuning studies conducted under the auspices of the <strong>Siebel</strong> Platform Sizing and <strong>Performance</strong> Program (PSPP). The tests conducted under this program are based on real-world scenarios derived from <strong>Siebel</strong> Systems customers, which reflect some of the most frequently used and most critical components of the <strong>Siebel</strong> eBusiness Applications Suite. This article also provides tips and best practices--based on our experience--for field staff, benchmark engineers, system administrators, and customers who are interested in achieving optimal performance and scalability with their <strong>Siebel</strong>-on-Sun installations. The following areas are addressed in this paper: • What are the unique features of the Solaris Operating System that reduce risk while helping to improve the performance and stability of <strong>Siebel</strong> applications? • For maximum scalability at a low cost, what is the optimal way to configure <strong>Siebel</strong> on the Solaris OS? • How does Sun’s Chip Multithreading (CMT) technology based on the UltraSPARC IV processor benefit <strong>Siebel</strong> solutions? • How can transaction response times be improved for end users in large <strong>Siebel</strong>-on- Sun deployments? • How can an Oracle database running on Sun StorEdge be tuned for higher performance for <strong>Siebel</strong> software? The performance and scalability testing was conducted at Sun’s Enterprise Technology Center (ETC) in Menlo Park, California, by Sun’s Market Development Engineering (MDE) with assistance from <strong>Siebel</strong> Systems. The ETC is a massive, distributed testing facility packing more computer power than many Fortune 1000 corporations. A facility of this magnitude provides the resources needed to test the limits of software on a much greater scale than most enterprises will ever require. <strong>Performance</strong> <strong>Tuning</strong> <strong>Siebel</strong> <strong>Software</strong> on the Sun Platform Page 6
1 <strong>Tuning</strong> for Price/<strong>Performance</strong>: Summary The Solaris Operating System is the cornerstone software technology that enables Sun to deliver high performance and scalability for <strong>Siebel</strong> applications; and the OS contains a number of features that enable customers to tune for optimal price/performance levels. Among the core features of the Solaris OS that contributed to the superior results achieved in the tests: Solaris MTmalloc: A standard feature with the Solaris system was enabled on the <strong>Siebel</strong> application servers. This is an alternate memory allocator module that was built specifically for multithreaded applications such as <strong>Siebel</strong>. The MTmalloc routines provide a faster, concurrent malloc implementation. This feature resulted in lowering CPU consumption by 35%. Though memory consumption doubled as a side effect, overall price/performance benefits are positive. There have been improvements made on MTmalloc in Solaris 10 OS which reduce the space-inefficiency penalty. More details on this topic are available in Section 7.1.1. <strong>Siebel</strong> Process Size: For an application process running on the Solaris OS, the default setting for stack and data size is unlimited. We found that <strong>Siebel</strong> software running with the default Solaris system setting caused bloated stack size and runaway processes that compromised scalability and stability of <strong>Siebel</strong> on the Solaris OS. Limiting the stack size to 1MB and increasing the data size limit to 4GB resulted in increased scalability and higher stability. Both adjustments let a <strong>Siebel</strong> process use its process address space more efficiently, fully utilizing the total process address space of 4GB available to a 32-bit application process. A significant drop in failure rate of transactions (only eight failures out of 1.2 million total transactions!) was observed as a result of these two changes. More details on this topic are available in Section 7.3. Solaris Alternate Threads Library: Solaris 8 OS provides an alternate threads implementation with a one-level model (1x1) in which user-level threads are associated one-to-one with lightweight processes (LWPs). This implementation is simpler than the standard (MxN) two-level model in which user-level threads are multiplexed over (possibly) fewer LWPs. When used on <strong>Siebel</strong> Application Servers, the 1x1 model provided good performance improvements to the <strong>Siebel</strong> multithreaded applications. More details on this topic are available in Section 7.1.2. Solaris Multiple Page Size Support (MPSS): A standard feature available in Solaris 9 OS and subsequent versions, MPSS gives applications the ability to run on the same OS with more than one page size. Use of this Solaris library allows a larger heap size to be set for certain applications, which results in better performance due to reduced TLB miss%. This feature was enabled on the Oracle server and resulted in performance gains. More details on this topic are available in Section 7.6.4. Solaris Resource Manager was used on all tiers of the setup to efficiently manage CPU resources. This resulted in fewer process migrations and translated to higher cache hits. <strong>Performance</strong> <strong>Tuning</strong> <strong>Siebel</strong> <strong>Software</strong> on the Sun Platform Page 7
Page 1 and 2: Performance <stron
Page 3 and 4: Abstract This paper discusses the p
Page 5: 7.6.6 Oracle Parameters Tun
Page 9 and 10: 2 Siebel Applicati
Page 11 and 12: 3 Optimal Sun/Siebel</stron
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
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Oracle Database Server 1. Larger th
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160 siebelapp2_1 eSalesObjMgr_enu 1
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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
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S_OPTY_BU_M8 INDEX 2,334,720 S_ORDE
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log file parallel write 550,101 515
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Acknowledgements Thanks to
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Performance Tuning Siebel Software on the Sun Platform

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