Time-based SLIs aggregate metric data over a timeslice
to mark it as success or failure.
This can also reduce the resolution of the data.
For example, probing an endpoint every 60 seconds to see if it is available,
assumes that the endpoint is available for the entire 60 seconds.
Another common example is to compare the average of data points with a desired
valud. Averages hide the spikes and valleys in the data.
It is better to use
percentiles
instead.
Another example is percentiles. When calculating the 99th percentile of the
latency every 5 minutes, the aggregation window is 5 x 60 = 300 seconds.
Typical timeslice lengths
| Timeslice |
Seconds |
|
| {{ p.title }} |
{{ p.seconds }} |
|