Ops ✦ 61outlineAlpha experiment — calibrate; prefer annotate before filter

OTel metric retention assess

Who: Platform/obs engineers. Steps: Feed metric metadata to System One; map answers to retention policy in code; start in annotate mode. Expected effect: cheaper retention focused on valuable series.

Source: https://github.com/ishantanu/jevmetrics ↗ Docs / source ↗

Treat this as an outline — adapt state and questions to your data.

Implement in code — call System One / Jev; compose answers yourself.

Gate on confidence — act, confirm, or escalate before side effects.

Outline sketch

Prompt

# OTel metric retention assess
State: metric name, labels, cardinality hints, and ownership metadata (no raw samples required).
Ask: Choice/Score/Noul on keep value and risk of dropping.
Then: map answers to annotate or filter retention in collector code.

Needs access to: typesafe-sdkopentelemetry

Who it's for

Observability / platform engineers

Steps / how it's set up

Steps (alpha)

Feed metric metadata (not full payloads) to System One.
Map closed answers to retention policy in code.
Prefer annotate mode first; only then filter.

Sources

https://github.com/ishantanu/jevmetrics

This pattern is experimental / alpha. Author-reported behavior — calibrate on your telemetry estate.

Expected effect

Cheaper retention focused on valuable series

Unofficial outline for learning. Paraphrased from public docs and tutorials — not a production recipe. Review sources before you automate anything.