By Neil J. Gunther
To resolve functionality difficulties in smooth computing infrastructures, frequently comprising hundreds of thousands of servers working hundreds and hundreds of purposes, spanning a number of stages, you would like instruments that transcend mere reporting. you wish instruments that let functionality research of program workflow around the whole firm. That's what PDQ (Pretty rattling speedy) offers. PDQ is an open-source functionality analyzer according to the paradigm of queues. Queues are ubiquitous in each computing surroundings as buffers, and because any program structure could be represented as a circuit of queueing delays, PDQ is a normal healthy for interpreting approach functionality. development at the luck of the 1st version, this significantly improved moment version now contains 4 elements. half I comprises the foundational recommendations, in addition to a brand new first bankruptcy that explains the significant function of queues in winning functionality research. half II offers the fundamentals of queueing conception in a hugely intelligible variety for the non-mathematician; little greater than high-school algebra being required. half III offers many sensible examples of the way PDQ might be utilized. The PDQ guide has been relegated to an appendix partially IV, in addition to strategies to the workouts contained in every one bankruptcy. all through, the Perl code listings were newly formatted to enhance clarity. The PDQ code and updates to the PDQ guide can be found from the author's site at www.perfdynamics.com
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Additional info for Analyzing Computer System Performance with Perl::PDQ
3. The steady-state average for a given user load is determined by taking measurements over some measurement period T and eliminating any ramp-up or ramp-down periods from the data. 2 Measurement Tools and Techniques Average throughput (X) 26 User load (N) Fig. 3. The relationship between steady-state measurements of the instantaneous throughput X(t) and the system throughput characteristic X(N ). The overall mean throughput characteristic (dashed curve) is determined by repeating (inset plots) the steady-state measurement process in Fig.
Steady-state throughput (upper curve) and the corresponding processor utilization (lower curve) measured on a production system during a peak usage period of about three hours. The dashed horizontal lines are the average throughput and utilization, respectively. 0200 s. 2, because the magnitudes of the fluctuations below the mean (dashed line) are smaller. 3, the estimated numerical value of the mean service time (S) is only reliable because it was derived from steady-state measurements. Since it is always best to err on the side of caution, it is best to use steadystate measurements that are collected during peak usage periods.
4 and 5, a calculated value, like this one, for the service time S can be used as an input parameter for PDQ models. 3. 1) tells us that we may adjust the sample measurement window to remove the severity of the random fluctuations in the data. 1 Steady as She Goes 25 Fig. 2. Steady-state throughput (upper curve) and the corresponding processor utilization (lower curve) measured on a production system during a peak usage period of about three hours. The dashed horizontal lines are the average throughput and utilization, respectively.