By Neil J. Gunther
The major motivation for this booklet stems from the remark that the folks who so much have to know how to do functionality research are quite often thwarted through the quantity of
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Extra resources for Analyzing Computer Systems Performance: With Perl: PDQ
1 is 1 yr = 32 × 106 s. 9% available means 32×106 ×10−3 = 32, 000 s or 9 h per year downtime. 99% available means 32 × 106 × 10−4 = 3, 200 s or approximately 1 h of downtime per year. 9999% means 32 × 106 × 10−6 s or 32 s of downtime per year. X% ≡ 10−(2+X) occurrences. 99 . 9% = 10−(number of 9’s) occurrences per year. Achieving and maintaining these levels of availability in a cost-eﬀective manner leads some computer manufacturers to refer to this constraint as The tyranny of the nines. 12). 6.
7 Failing Big Time 37 ∞ MTBF = R(t) dt . 16) by an appropriate choice of h(t). Some of the best known reliability models are based on the exponential, and the Weibull distributions, which we brieﬂy summarize here. Exponential distribution. 17) is constant. 18) R(t) = e−λ t . 16) produces: M T BF = 1 . 19) In other words, the MTBF is just the inverse of the failure rate. The main feature of exponential models is that they represent system failures that are statistically independent or random in time, which is also known as the “ageless” property.
In that case assessing availability (if it can be calculated at all) requires more complicated techniques [Xie 1991] than those brieﬂy presented here. 8 Software Reliability Because software and hardware have very diﬀerent failure modes, modeling the reliability of software tends to be more diﬃcult than it is for hardware. ” This is quantiﬁed in a measure called the mean time between defects (MTBD). Software Failure Rate 225 200 175 150 125 100 2000 4000 6000 8000 Time 10,000 Fig. 11. Software failure model There is always a ﬁnite set of unresolved bugs present in software.
Analyzing Computer Systems Performance: With Perl: PDQ by Neil J. Gunther