Prometheus supports two types of rules which may be configured and then
evaluated at regular intervals: recording rules and alerting
rules. To include rules in Prometheus, create a file
containing the necessary rule statements and have Prometheus load the file via
rule_files field in the Prometheus configuration.
Rule files use YAML.
The rule files can be reloaded at runtime by sending
SIGHUP to the Prometheus
process. The changes are only applied if all rule files are well-formatted.
To quickly check whether a rule file is syntactically correct without starting
a Prometheus server, you can use Prometheus's
promtool command-line utility
promtool check rules /path/to/example.rules.yml
promtool binary is part of the
prometheus archive offered on the
project's download page.
When the file is syntactically valid, the checker prints a textual
representation of the parsed rules to standard output and then exits with
0 return status.
If there are any syntax errors or invalid input arguments, it prints an error
message to standard error and exits with a
1 return status.
Recording rules allow you to precompute frequently needed or computationally expensive expressions and save their result as a new set of time series. Querying the precomputed result will then often be much faster than executing the original expression every time it is needed. This is especially useful for dashboards, which need to query the same expression repeatedly every time they refresh.
Recording and alerting rules exist in a rule group. Rules within a group are run sequentially at a regular interval, with the same evaluation time. The names of recording rules must be valid metric names. The names of alerting rules must be valid label values.
The syntax of a rule file is:
groups: [ - <rule_group> ]
A simple example rules file would be:
groups: - name: example rules: - record: job:http_inprogress_requests:sum expr: sum by (job) (http_inprogress_requests)
# The name of the group. Must be unique within a file. name: <string> # How often rules in the group are evaluated. [ interval: <duration> | default = global.evaluation_interval ] # Limit the number of alerts an alerting rule and series a recording # rule can produce. 0 is no limit. [ limit: <int> | default = 0 ] rules: [ - <rule> ... ]
The syntax for recording rules is:
# The name of the time series to output to. Must be a valid metric name. record: <string> # The PromQL expression to evaluate. Every evaluation cycle this is # evaluated at the current time, and the result recorded as a new set of # time series with the metric name as given by 'record'. expr: <string> # Labels to add or overwrite before storing the result. labels: [ <labelname>: <labelvalue> ]
The syntax for alerting rules is:
# The name of the alert. Must be a valid label value. alert: <string> # The PromQL expression to evaluate. Every evaluation cycle this is # evaluated at the current time, and all resultant time series become # pending/firing alerts. expr: <string> # Alerts are considered firing once they have been returned for this long. # Alerts which have not yet fired for long enough are considered pending. [ for: <duration> | default = 0s ] # Labels to add or overwrite for each alert. labels: [ <labelname>: <tmpl_string> ] # Annotations to add to each alert. annotations: [ <labelname>: <tmpl_string> ]
A limit for alerts produced by alerting rules and series produced recording rules can be configured per-group. When the limit is exceeded, all series produced by the rule are discarded, and if it's an alerting rule, all alerts for the rule, active, pending, or inactive, are cleared as well. The event will be recorded as an error in the evaluation, and as such no stale markers are written.
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