New performance material at the Deployment wiki

As promised, we have started to publish some datasheets and reports on the Deployment wiki. In between the necessary work of qualifying and testing new releases, the team has explored some more complex scenarios. Some of these explorations are responses to customer requests, so keep letting us know what’s important to you. Others are topics which have sat dormant in our backlog and we’ve only just recently been able to align resources to achieve them.

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Plan loading improvements in RTC 4.0.3

Everybody works with plans in RTC, whether tiny team plans to multi-year large plans with thousands of items and complex team/owner/plan item relationships. When working with larger, more complex plans, some clients noted sub-optimal performance of plan loading. They sought techniques to optimize their plan usage, and also asked IBM to improve plan load response times.

For the Rational Team Concert 4.x releases, the development team made significant improvements to plan loading behavior. Significant changes were made to 4.0.3. This case study compared identically structured plans of varying sizes with the goal of determining the difference in plan load time between RTC and 4.0.3.

“Using the release the larger plans took more than a minute to load while in 4.0.3 all plans, regardless of size or browser used, took less than a minute to load. In this study plans of all sizes loaded faster in 4.0.3 than in Notably, plans with larger numbers of work items loaded proportionally faster in 4.0.3.”

See Case study: Comparing RTC and 4.0.3 plan loading performance:

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Sharing a JTS server between RTC, RQM and RRC

Key to a successful CLM implementation is separate application servers (Rational Team Concert (RTC), Rational Quality Manager (RQM) and Rational Requirements Composer (RRC)) sharing the same JTS server. Folks have asked about the breaking point of a shared JTS server. From the report:

“Overall, for this set of machines and these workloads, the JTS never became a bottleneck. There was only a small amount of degradation in maximum throughputs (5-10%) even when all 5 CLM servers were at maximum load.”

Throughput was measured in transactions-per-second and graphs show the different combinations of servers connected to the single JTS and the relative loads and transaction rates.

Visit Performance impact of sharing a Jazz Team Server:

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Sizing VMware

Everyone is using virtualization, and VMware’s ESX is popular for deploying Linux and Windows OSes. We offer stated minimum suggested CPU sizes which are applicable to both physical and virtual servers. This particular report looks at the performance impact of varying vCPU sizes of VMware VMs which are serving Rational Team Concert.

“In this study, we were using dual 6-core physical hyper-threaded CPUs that were not able to be translated to 12 or 24 vCPUs within the virtual environment. We found better performance using 16 vCPUs in our Virtual Machines.”

Look at Performance impact of different vCPU sizes within a VMWare hypervisor:

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RRDI 2.0.x sizing guidelines

One of my Jumpstart colleagues wrote a note about sizing the Rational Reporting for Development Intelligence (RRDI), an essential ingredient in most CLM deployments. To properly size RRDI requires understanding the approximate number of concurrent users and estimating how many of them might interact with reports.

Take a look at RRDI 2.0.x sizing guidelines:

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The future

We plan to post more reports as they are completed on the wiki here: As always, let us know what you think is missing or what you’re interesting in hearing more about. You can ask here or on the wiki itself. Thanks.