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Metric Drop & Aggregation Recommender

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Find metrics and labels that no Grafana dashboard, alert, recording rule or query uses. Get ranked drop & aggregation recommendations with savings, plus OTel Collector, Prometheus relabel and recording-rule configs.

Pricing

from $500.00 / 1,000 metrics analyzeds

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Developer

Justin Hagerty

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Monthly active users

11 days ago

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Changelog — Metric Drop & Aggregation Recommender

0.1.0 — unreleased

Initial version.
Generated Collector processors validated against otelcol-contrib 0.115.1/0.150.1 (config validation and an end-to-end run); frozen as snapshot tests. Fix: histogram _sum/_count are extracted as non-monotonic sums (monotonic ones were exported as <name>_sum_total, breaking queries) and renamed to the Prometheus name when the inventory uses OTel names.
Relabel regexes escape label values for RE2 (e.g. route="/api/v1.0").
New output prometheus-remote-write: write_relabel_configs that drop unused series and keep only the recorded series of aggregated metrics, merged into an existing remote_write section.
MUO-HIST-002 suggests concrete bucket boundaries from the histogram's le values (kept per family from every inventory format, or bucketBounds in the list format), keeping SLO thresholds that histogram_quantile results are compared with, plus an OTel SDK view snippet.
Existing filter-processor OTTL conditions are parsed and evaluated per metric (and/or/not, metric.type, unit, resource and data-point attributes); attribute-dependent conditions are reported as partial drops.
Per-job attribution: job/jobs in the inventory (or a complete job label) scopes existing metric_relabel_configs per scrape job, and generated relabel rules only go to jobs that emit the metric.
MUO-COST-003: estimated-savings summary line in REPORT.md.
Performance: ~50k series / 1,000 dashboards analysed in about a second (cached label-need analysis, faster family grouping, libyaml emitter).
PromQL parser (selectors, regex/UTF-8 names, aggregations, vector matching, set ops, functions, subqueries, offset/@) with top-down label-dependency analysis and a conservative fallback for unparsable queries.
Inventory formats: metric list JSON/YAML, Prometheus series/names/metadata exports, TSDB status, OTLP/JSON, exposition text.
Usage sources: Grafana dashboards (rows, collapsed rows, variables, macros), Prometheus/Mimir rule files (incl. PrometheusRule CRDs, ruler exports), query lists and query logs; transitive recording-rule usage.
Recommendations: drop metric/family, aggregate labels, drop label values, drop histogram buckets/summary quantiles, bucket reduction, exponential histograms, interval increase, shared recording rules. Each comes with savings, confidence, evidence and risk notes.
Generated OTel Collector processors (merged into a supplied config), Prometheus metric_relabel_configs, recording rules, vendor-neutral JSON and a phased rollout plan with verification queries.
61 rules (MUO-*). See RULES.md.
Pay-per-event: metrics-analyzed ($0.50) and rules-generated ($0.25). Unparsable inventories are free.

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