By Neil J. Gunther
To remedy functionality difficulties in smooth computing infrastructures, usually comprising hundreds of thousands of servers working thousands of functions, spanning a number of ranges, you would like instruments that transcend mere reporting. you wish instruments that permit functionality research of program workflow around the complete firm. that is what PDQ (Pretty rattling quickly) presents. 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 will be represented as a circuit of queueing delays, PDQ is a common healthy for reading procedure performance.
Building at the good fortune of the 1st variation, this significantly extended moment variation now includes 4 components. half I comprises the foundational suggestions, in addition to a brand new first bankruptcy that explains the imperative position of queues in profitable functionality research. half II offers the fundamentals of queueing concept in a hugely intelligible sort for the non-mathematician; little greater than high-school algebra being required. half III provides many sensible examples of the way PDQ might be utilized. The PDQ handbook has been relegated to an appendix partially IV, in addition to options to the routines contained in every one chapter.
Throughout, 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
Distributed timing protocols such as NTP (Sect. 2) can help to resolve the correct ordering of sampled performance data. 7 Virtual Clocks For the sake of completeness we point out that virtual time should not be confused with the discussion of logical time in Sect. 5. , causality) to be violated under certain circumstances. Under Time Warp, processes are permitted to proceed as rapidly as possible by advancing clocks without concern for possible violations of causality. This approach introduces the possibility of an erroneous simulation occurring.
90th percentile occurs at S90 ≈ 7S/3 3. 95th percentile occurs at S95 ≈ 9S/3 Since the distribution of arrival rates and service times is assumed to be exponentially distributed in PDQ (Chap. 6), this rule of thumb can also be applied to those attributes in PDQ models. In Sect. 5 it was pointed out that measurements of end-to-end response times on real computer systems require a more general distribution than the exponential distribution. Based on Sect. 1, an obvious candidate is the gamma probability distribution.
Once again, there cannot be any missing links. The network services link in Fig. 5 has been expanded to become four links: 1. NIC card 30 1 Time—The Zeroth Performance Metric 2. LAN networking 3. Router 4. WAN networking while the server link in Fig. 5 has been expanded to become two links: 1. ) 2. Server disks Finer resolution of process times requires additional instrumentation probes; this is not always available, but it is always a worthy goal. 1 Bottlenecks and Queues We shall further formalize this timing chain concept in terms of the queue residence times in Chap.
Analyzing Computer System Performance with Perl::PDQ by Neil J. Gunther