The rate and irate functions in monitoring systems, such as Prometheus, are designed to calculate the per-second average rate of increase of a time series over a specified time range. If these functions are not producing data even when the original indicator exists, there could be several reasons:
Insufficient Data Points: The time range specified for the rate or irate function might be too short, resulting in no data points being available to calculate the rate. For example, if you are trying to calculate the rate over the last minute but there were no data points in the last minute, the function will return no data.
Data Gaps: There might be gaps in the data where no samples were recorded. If the time series has missing data points within the specified time range, the rate calculation will not produce meaningful results.
Incorrect Label Matching: When using rate or irate with by or without clauses, ensure that the labels match exactly between the original metric and the aggregation. Mismatched labels can lead to no data being returned.
Metric Type: Ensure that the original metric is a counter type. rate and irate functions are specifically designed for counter metrics, which are monotonically increasing. If the metric is a gauge, which can go up and down, these functions will not work as expected.
Time Series Discontinuity: If the time series has been discontinued or reset, the rate calculation might not produce data. For example, if a counter is reset to zero, the rate function will not be able to calculate the rate accurately.
For example, consider a scenario where you have a counter metric http_requests_total that records the total number of HTTP requests. If you use the rate function like this:
rate(http_requests_total[1m])
But there were no HTTP requests in the last minute, the function will return an empty result because there are no data points to calculate the rate.
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