Perform what-if analysis of demand growth scenarios to determine resources required to meet service levels without over-provisioning with TeamQuest Predictor. This capacity planning solution uses sophisticated algorithms that have evolved over decades of experience to provide predictions with 95% accuracy.
TeamQuest Predictor analyzes queuing which affects throughput and response time. Queuing is typically expressed in terms of "stretch factor." This chart shows services running at a stretch factor of 1.2 (meaning good response times and throughput).
TeamQuest Predictor predicts the affects of workload growth and hardware changes. In this chart the stretch factor in the 5th month is predicted to exceed 2, which will negatively affect response time and throughput.
In this chart we see that the resource that will be driven the hardest is CPU. So, we suspect that adding additional CPUs will bring the response time and throughput back to acceptable levels. Next we will predict performance after adding CPUs.
Having added new CPUs, we see that the stretch factor is now back at 1. This indicates negligible queuing is occurring. The system can handle the proposed workload increase.