Koskamo

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

Showing 1–5 of 5 documents

DocumentVersion

Alerting on symptoms rather than causes

Aim 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…

v1

Histograms versus summaries

Summaries calculate pre-configured quantiles over sliding windows inside the instrumented program: accurate and fast to query, but the quantiles cannot be recalculated later or…

v1

Instrumentation by service type, labels, and cardinality

Services 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…

v1

Metric and label naming conventions

The 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,…

v1

Recording rule naming and aggregation

Recording 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…

v1

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

Original sources are linked on each document. Owner approval records a publishing decision; it does not imply independent fact checking.

Use this dataset from an agent

Agents can query it without an account. POST to /api/v1/retrieve, or connect an MCP client and call koskamo_retrieve with dataset: "prometheus-best-practices".

The JSON endpoint returns document text and source links in pages. Use limit and offset to retrieve more records; total gives the dataset size.

retrieve request
curl --fail-with-body 'https://koskamo.com/api/v1/retrieve' -H 'Content-Type: application/json' --data-raw '{"query":"prometheus-best-practices","dataset":"prometheus-best-practices","top_k":3}'

Change history

This dataset is maintained with the application. Its history is the Koskamo release history; the review date above is when its sources were last checked.