Table of Contents

• Methodologies for Selecting and Managing IT Performance MeasuresMichael Bitterman. 1-2
• Has the IT Benchmark Become Obsolete?Michael Bitterman. 3-4
• Objective Functions for SLA Risk ManagementJames P. Bouhana, Mike Tsykin. 5-14
• Future Big Iron Performance and Capacity Specialists - Where will they come from?Gregory V. Caliri. 15-22
• Application View ReportingJane G. Fiala-Curry, Barbara L. Johnson. 23-30
• Who Measures the Measurers? KPIs and QoS for the Capacity Management Process.Adam Grummitt. 31-32
• UK CMG - Best Paper: Underneath the Spin; a Practical Look at Service Levels (Is what you see what you get?)Malcolm Gunn. 33-42
• To Instrument or Not Instrument, That is the QuestionJames Holtman. 43-54
• The Service-Oriented Organization - People, Politics & PitfallsDenise P. Kalm. 55-64
• Managing and Modernizing Legacy ApplicationsGerry W. Leitao. 65-76
• Using a CDB to Uplevel Your Performance Management and Planning EffortsG. Jay Lipovich. 77-80
• Performance of the Business of a Web PortalMark M. Maccabee. 81-90
• Everything You Know About Monitoring is WrongMazda T. Marvasti. 91-102
• Generation of Test Schedules for Object Oriented ApplicationsTuli Nivas. 103-112
• The Experience of System ResponsivenessSteven C. Seow. 113-118
• Building a Capacity Management Team - Lessons LearnedMary Anne Smith. 119-130
• Performance Testing: A Heuristic ApproachScott Barber. 131-132
• Automating the Analysis of Load Test Results to Assess the Scalability and Stability of a Component-Andre B. Bondi. 133-146
• Improving Simulation Accuracy through the use of Synthetic Alignment IntervalsJeffrey P. Buzen. 147-158
• End-to-End Post-Deployment Capacity Management Framework - An ApproachGaurav Caprihan. 159-170
• Help! Flow Control Issues for B2B Gateway Solved by Rapid Turnaround of Designs using SimulationNick Chapman. 171-182
• How to Select Significant Workloads in Performance ModelsPaolo Cremonesi, Giuliano Casale. 183-192
• Performance Optimization on Game ConsolesBruce Dawson. 193-196
• ARM: Getting Started with Application Response Measurement (ARM) and Java the Easy WayCarl J. De Pasquale. 197-218
• Moore s Law vs. Gates Law - Macro Capacity ManagementYiping Ding. 219-230
• Comparative Architecture Performance Analysis At Design TimeGerald S. Doyle, Elizabeth L. White. 231-242
• Modeling the Performance Impact of Internet Marketing Campaigns on E-Commerce SitesPierre M. Fiorini, Yiping Ding. 243-252
• The Art and Science of MeasurementMark B. Friedman. 253-254
• Capacity Planning Boot CampNeil J. Gunther. 255-256
• A Quantitative Approach for Determining Service Demands in a Network Load Balanced ScenarioVikas Gupta, Sachin Wagh. 257-262
• Engineering Performance Using Control TheoryJoseph L. Hellerstein, Yixin Diao. 263-272
• An Approach for Accurately Recreating Web Workloads from Production DataSuresh K. Khemka, Nikhil Venugopal, Gaurav Caprihan. 273-274
• So I have Data on Each Transaction, How Do I Use It?Luke E. Lofgren. 275-284
• An Empirical Evaluation of Communication and Processing Overhead in Service Oriented ArchitecturesDaniel A. Menascé. 285-292
• Why You Can t See Your Real Performance ProblemsCary V. Millsap. 293-302
• Using Simulation to Forecast Performance: A Case StudyTuli Nivas. 303-312
• Software Performance Lifecycle at a Large National BankAmit Patel. 313-324
• Multiple Dimensions of Performance RequirementsAlexander Podelko. 325-334
• Using SAS/Graph to Display Performance and Capacity DataRichard S. Ralston. 335-336
• Modeling and ForecastingMichael A. Salsburg. 337-338
• The Pros and Cons of Collecting Performance Data using Agentless technologyDima Seliverstov, John Tavares, Tianxiang Zhang. 339-348
• Top 10 Ways to Kill an SPE InitiativeConnie U. Smith, Lloyd G. Williams. 349-350
• Performance Management - Top 10 TrapsMegh Thakkar. 351-352
• System Management by Exception, Part FinalIgor A. Trubin, Ray White. 353-360
• Performance Monitoring Process for Out of Standard ApplicationsJohn S. Van Wagenen. 361-372
• Achieving near Linear Scalability Using Solaris on Numa ArchitecturesRickey C. Weisner. 373-384
• Statistics for Performance Analysis & Capacity PlanningRay Wicks. 385-386
• Software Performance Engineering: A Tutorial IntroductionLloyd G. Williams, Connie U. Smith. 387-398
• Improving Packing Algorithms for Server ConsolidationYasuhiro Ajiro, Atsuhiro Tanaka. 399-406
• Millicomputing: The Coolest Computers and the Flashiest StorageAdrian N. Cockcroft. 407-414
• Directing the Stream: Using Web 2.0 Technologies for Marketing and PerformanceBernard Domanski, Robert J. Domanski. 415-426
• The Right Mix of Utility, Consolidation and Virtualization for Optimum Cost-Capacity-PerformanceAdam Grummitt. 427-428
• Parallel File System Technologies in a Linux Cluster and GRID EnvironmentDominique A. Heger. 429-442
• Seeing It All at Once with BarryMario F. Jauvin, Neil J. Gunther. 443-458
• Death to Dashboards: Alarming, Performance Management Based on Variance, System Prioritization and Other Thoughts on Data VisualizationPeg McMahon, Justin Martin. 459-462
• The Powerful Capacity ManagerChris L. Molloy. 463-470
• The Myth of Precision Planning: Understanding Capacity in an Age of Virtual ParallelismTim R. Norton. 471-482
• VMWare ESX Server Workload Analysis: How to Determine Good Candidates for VirtualizationJohn Paul. 483-484
• Adjusting the Fit: VMware ESX Server Workload Analysis Lessons LearnedJohn Paul. 485-486
• Beyond the Hypervisor HypeMichael A. Salsburg. 487-496
• Enterprise Data Management OptimizationBoris E. Zibitsker. 497-498
• An Open Source ARM 4 ImplementationDavid Carter. 499-502
• Unix/Linux CMG Quick Start CourseAdrian N. Cockcroft. 503-504
• Monitoring and Tuning Open Source DatabasesPeter Johnson. 505-518
• Java Performance Analysis 401Peter Johnson. 519-526
• Consolidated Capacity and Performance ReportingCraig A. Leikis. 527-534
• A Queue Simulation Tool for a High Performance Scientific Computing CenterJames W. McGalliard, Carrie Spear. 535-546
• Configuring Linux on z/VM for PerformanceBarton Robinson. 547-548
• The Promise of Network High Availability Systems - How to Properly Measure Convergence TimesAnkur Chadda. 549-554
• Introduction to TCP/IP Performance ManagementNalini J. Elkins. 555-556
• Your OSPF Network is BAD!Major Lai. 557-558
• Fighting Against Spam: The ETIS Anti-spam Pilot ProjectPieter J. Meulenhoff. 559-568
• Collecting Actionable Information to Effectively Manage Web Application PerformanceHon Wong. 569-580
• The What If s of Storage Capacity PlanningJohn Baker. 581-582
• New Developments in Storage Network ProtocolsTom Clark. 583-592
• Performance Tuning of Storage System using Design of ExperimentsPrabu Dorairaj, Devi Prasad Bhukya, Lakshminarayana Prasad Kantam. 593-602
• Disk Storage Performance Warranties: Why and Why Not?Rich Milner, John Gatch. 603-604
• Mainframe Disk Performance Modeling and Open Systems ApplicabilityLee Reiersgord, John Gatch. 605-606
• A Queueing Analysis of Selected Performance Issues with Virtual Tape and RoboticsWilliam T. Gray. 607-616
• To CUP, or not to CUP, that is the FICON question!Stephen R. Guendert. 617-618
• Understanding the Performance Implications of Buffer to Buffer Credit Starvation In a FICON EnvironmentStephen R. Guendert. 619-628
• Performance Considerations for Archiving DataRandy Kerns. 629-640
• Storage Performance Analysis - Drill-Down Case StudyCharles T. McGavin Jr.. 641-652
• A New Way to Expose Performance Counters on Windows VistaWedson Almeida Filho, Ricky Buch, Insung Park. 653-662
• Understand the Performance Measures of MS Virtual ServerJie Lu, Tianxiang Zhang. 663-672
• Intelligent Aggregation of System Health Data for Managing Large IT EnvironmentsVishal Radhakrishnan, Aaron Spinks, Insung Park. 673-682
• Techniques for Identifying and Optimizing Resource-Intensive Sql Server QueriesJeffry Schwartz. 683-694
• Windows System Performance Measurement and AnalysisJeffry Schwartz. 695-696
• Optimize .NET & J2EE Application Performance Using Browser-to-Database Monitoring and DiagnosticsHon Wong. 697-708
• Modeling Virtualized LPARs using CoadunationClea Zolotow, Elaine Zizzi. 709-710
• A z/OS WLM Update for DB2 EnvironmentsGlenn R. Anderson. 711-712
• A z/OS WLM Guy Discovers Enterprise Workload Manager (EWLM)Glenn R. Anderson. 713-714
• Introduction to z/OS Monitoring, Tuning, and the Workload ManagerGlenn R. Anderson. 715-716
• Evolving DB2 CPU and Response MetricsNed A. Diehl. 717-730
• zIIPS and zAAPs - Understanding Transaction Flows and CPU MeasurementsPeter A. Enrico. 731-732
• CE CMG - Best Paper: J2EE & Mainframes - When Quality MattersWolfram Greis. 733-734
• E2E Performance Monitoring to the Mth Tier (Mainframe Integrated) - The New Industry StandardThomas A. Halinski, Eric Repec. 735-736
• The Myth Of MSU or How Big is the Bucket?Jim Horne. 737-746
• Reclaim your Performance with DB2 v8William R. Miller. 747-752
• Taming the Wild Service DefinitionRich Olcott. 753-754
• The Hidden Cost of TCP/IP on z/OSBill Yeager. 755-760