Percentage Calculation
Availability is usually expressed as a percentage of uptime in a given year. The following table shows the downtime that will be allowed for a particular percentage of availability, presuming that the system is required to operate continuously. Service level agreements often refer to monthly downtime or availability in order to calculate service credits to match monthly billing cycles. The following table shows the translation from a given availability percentage to the corresponding amount of time a system would be unavailable per year, month, or week.
| Availability % | Downtime per year | Downtime per month* | Downtime per week |
|---|---|---|---|
| 90% ("one nine") | 36.5 days | 72 hours | 16.8 hours |
| 95% | 18.25 days | 36 hours | 8.4 hours |
| 97% | 10.96 days | 21.6 hours | 5.04 hours |
| 98% | 7.30 days | 14.4 hours | 3.36 hours |
| 99% ("two nines") | 3.65 days | 7.20 hours | 1.68 hours |
| 99.5% | 1.83 days | 3.60 hours | 50.4 minutes |
| 99.8% | 17.52 hours | 86.23 minutes | 20.16 minutes |
| 99.9% ("three nines") | 8.76 hours | 43.8 minutes | 10.1 minutes |
| 99.95% | 4.38 hours | 21.56 minutes | 5.04 minutes |
| 99.99% ("four nines") | 52.56 minutes | 4.32 minutes | 1.01 minutes |
| 99.999% ("five nines") | 5.26 minutes | 25.9 seconds | 6.05 seconds |
| 99.9999% ("six nines") | 31.5 seconds | 2.59 seconds | 0.605 seconds |
| 99.99999% ("seven nines") | 3.15 seconds | 0.259 seconds | 0.0605 seconds |
Uptime and availability are not synonymous. A system can be up, but not available, as in the case of a network outage.
In general, the number of nines is not often used by a network engineer when modeling and measuring availability because it is hard to apply in formula. More often, the unavailability expressed as a probability (like 0.00001), or a downtime per year is quoted. Availability specified as a number of nines is often seen in marketing documents.
The use of the "nines" (cf. Class of 9s and Nines (engineering)) has been called into question, since it does not appropriately reflect that the impact of unavailability varies with its time of occurrence.
Read more about this topic: High Availability
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