Why not just use the OTel filter processor?

The filter processor needs explicit operator conditions and Adaptive Metrics leans on usage and cardinality. This processor infers likely operational value from names, descriptions, units, scope, and attribute keys first, then deterministic protection rules and thresholds decide what the Collector does.

Will it drop data on the first batch before Jev answers?

No. For an unprotected metric without a fresh cached assessment it keeps the incoming metric, queues an async request, and only uses the validated cached answer for later batches until expiry or eviction. Assessment-only batches are never emitted.

Does reduce mode downsample noisy series?

No. Filtering removes an entire metric and its datapoints, with no downsampling, dimension reduction, or automatic aggregation. A Jev recommendation of reduce is advisory and does not implement those operations.

What setup catches most first-run failures?

You need Go, Make, the Collector builder at the pinned release, and Docker for the mock-inference demo with its dashboard and end-to-end check. Live inference additionally needs a TypeSafe key and network access to the Jev endpoint.

What four questions does the processor send to Jev?

relevance, redundancy and keep are nouls, and action is a choice recommending keep, reduce or drop. Only the keep probability drives the keep or drop decision; the other answers are exposed for review and do not override the policy.

Can I evaluate jevmetrics without an API key?

Yes. make demo-up runs the actual Collector in annotation mode with mock inference by default, so no key is required, and make demo-check runs an end-to-end check against a bundled Grafana dashboard.

What does annotate mode add to my telemetry?

It preserves the incoming metrics and emits four companion gauges: jev.metric.relevance, redundancy, keep_probability and recommended_action, carrying metric.name, jev.model and a per-instance jev.collector.id. Original datapoints are unchanged, but annotation adds volume.

CommunityJev Integrations & Adapters

Jevmetrics

Experimental OpenTelemetry Collector processor that asks Jev about metric metadata and applies explicit keep or drop policy, starting in annotate mode.

See highlights

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Stars: 5
Language: Go
License: APACHE-2.0
Published by: Community
Author: ishantanu
Last verified: Oct 2026

ishantanu/jevmetrics

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Jev inference for metric assessment and retention in OpenTelemetry.

Forks: 0
Last pushed: Updated Oct 2026

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About this project

Jev inference for metric assessment and retention in OpenTelemetry. jevmetrics is an experimental OpenTelemetry Collector metrics processor. It calls TypeSafe’s Jev model to infer the likely operational value of metric instruments from their metadata, then applies deterministic policy to the returned probabilities.

Quoted from the project's README. Read the full README.

Tagscommunity awesomejev catalog-import

Works forJev for Classification

Used inJev for Software & DevTools

Languages: Go

Highlights

Sends metric metadata as four typed questions with the keep probability driving filtering decisions.
Runs inference asynchronously with validated, cached answers while incoming metrics keep flowing.
Annotate mode adds jev.metric companion gauges and policy counters without modifying originals.
Reduce mode drops whole metrics by policy; protected metrics bypass inference entirely.

Watch out

Alpha status, so start with annotate and evaluate filtering and savings on your own telemetry; annotation preserves input but adds companion volume. Copy reviewed against the repository README on 2026-10-04, not from running it.

Questions about this entry

Short answers drawn from the linked project or page.

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