Metric types reference
The following monitoring metrics are available in each interface:
Cumulative metric for a numerical value that only increases while the server is running.
Counts that reflect volatile data, such as the number of requests, are reset to 0 when the server starts up.
Metric for a numerical value that can increase or decrease.
Metric that samples observations, and counts them in buckets, as well as providing a sum of all observed values.
LDAP metrics show histograms as JSON objects. JSON histograms for entry sizes (in bytes) have the following fields:(1)
Metric that samples observations, providing a count of observations, sum total of observed amounts, average rate of events, and moving average rates across sliding time windows.
LDAP metrics show summaries as JSON objects. JSON summaries have the following fields:(1)
The Prometheus view does not provide time-based statistics, as rates can be calculated from the time-series data. Instead, the Prometheus view includes summary metrics whose names have the following suffixes or labels:
Metric combining a summary with other statistics.
LDAP metrics show summaries as JSON objects. JSON summaries have the following fields(1)
The Prometheus view does not provide time-based statistics. Rates can be calculated from the time-series data.
(1) Monitoring metrics reflect sample observations made while the server is running. The values are not saved when the server shuts down. As a result, metrics of this type reflect data recorded since the server started.
Metrics that show etime measurements in milliseconds (ms) continue to show values in ms even if the server is configured to log etimes in nanoseconds.
The calculation of moving averages is intended to be the same
as that of the
where the moving average plotted over time is smoothed by weighting that decreases exponentially.
For an explanation of the mechanism, refer to the Wikipedia section,
Exponential moving average.