Prometheus best practices
Source-linked guidance on Prometheus fundamentals: metric and label naming, instrumentation, alerting, histograms versus summaries, and recording rules. Scoped to Prometheus; not a general monitoring or PromQL corpus.
Documents
| Document | Version |
|---|---|
Alerting on symptoms rather than causesAim for as few alerts as possible, alerting on symptoms associated with end-user pain rather than trying to catch every possible cause; alerts should link to relevant consoles… | |
Histograms versus summariesSummaries calculate pre-configured quantiles over sliding windows inside the instrumented program: accurate and fast to query, but the quantiles cannot be recalculated later or… | |
Instrumentation by service type, labels, and cardinalityServices fit three main types. Online-serving systems need queries, errors, and latency; count queries when they end so they line up with error and latency stats. Offline… | |
Metric and label naming conventionsThe Prometheus naming conventions are a style guide and collection of best practices, not a requirement. A metric name MUST comply with the data model for valid characters,… | |
Recording rule naming and aggregationRecording rules follow the naming form level:metric:operations: level is the aggregation level and labels of the rule output, metric is the metric name unchanged except for… |
Source, review, and usage
- Published on Koskamo by
- Koskamo editorial
- Version
- 1
- Documents
- 5 documents
- Reviewed
- 2026-10-04
- Agent lookups
- 0 in the last 90 days
- Reuse
- Original summaries; linked sources retain their own terms.
- Review status
- Maintained with the application; source links supplied
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