PCA Recording Rules & Aggregation Flashcards
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What is the primary purpose of recording rules in Prometheus?
Answer: To precompute expensive PromQL expressions and store results as new time series
Recording rules evaluate PromQL expressions on a schedule and write the results as new metric series, making repeated queries faster.
What naming convention does Prometheus recommend for recording rule metric names?
Answer: level:metric:operations (e.g., job:http_requests_total:rate5m)
The recommended format is level:metric:operations, encoding aggregation level, source metric, and transformations into the name.
In a Prometheus rule file, which YAML key defines a recording rule's output metric name?
Answer: record
The `record` key in a rule group entry specifies the name of the new time series that the rule's expression will be written to.
How are recording rule files loaded into Prometheus?
Answer: Via the rule_files directive in prometheus.yml listing file paths or globs
The rule_files section of prometheus.yml accepts file paths and glob patterns pointing to YAML files containing rule groups.
What happens when Prometheus evaluates a recording rule that produces no series (empty result)?
Answer: No new data points are written for that evaluation interval
If a recording rule returns an empty result, Prometheus simply writes nothing for that interval, leaving a gap in the recorded metric.
What is the `interval` field in a Prometheus rule group used for?
Answer: Setting how frequently all rules in the group are evaluated
The interval field overrides the global evaluation_interval for a specific rule group, allowing different groups to evaluate at different frequencies.