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Another memory trick to calculate the allowed downtime duration for an "-nines" availability percentage is to use the formula seconds per day. For example, 90% ("one nine") yields the exponent 4 − 1 = 3 {\displaystyle 4-1=3} , and therefore the allowed downtime is 8.64 × 10 3 {\displaystyle 8.64\times 10^{3}} seconds per day.
In this context, a "one nine" (90%) uptime indicates a system that is available 90% of the time or, as is more commonly described, unavailable 10% of the time – about 72 hours per month. [8] A "five nines" (99.999%) uptime describes a system that is unavailable for at most 26 seconds per month. [8]
A weaker three-sigma rule can be derived from Chebyshev's inequality, stating that even for non-normally distributed variables, at least 88.8% of cases should fall within properly calculated three-sigma intervals. For unimodal distributions, the probability of being within the interval is at least 95% by the Vysochanskij–Petunin inequality ...
Uptime is a measure of system reliability, expressed as the period of time a machine, typically a computer, has been continuously working and available. Uptime is the opposite of downtime. Htop adds an exclamation mark when uptime is longer than 100 days.
Continuous availability is an approach to computer system and application design that protects users against downtime, whatever the cause and ensures that users remain connected to their documents, data files and business applications.
In the frequency domain (for example, looking at the Fourier transform of the step response, or using an input that is a simple sinusoidal function of time) the time constant also determines the bandwidth of a first-order time-invariant system, that is, the frequency at which the output signal power drops to half the value it has at low ...
The confidence interval can be expressed in terms of a long-run frequency in repeated samples (or in resampling): "Were this procedure to be repeated on numerous samples, the proportion of calculated 95% confidence intervals that encompassed the true value of the population parameter would tend toward 95%." [19]
A tolerance interval (TI) is a statistical interval within which, with some confidence level, a specified sampled proportion of a population falls. "More specifically, a 100×p%/100×(1−α) tolerance interval provides limits within which at least a certain proportion (p) of the population falls with a given level of confidence (1−α)."