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‎control_plane/src/epsilon_alloc.rs‎

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//! control_plane has no dependency on data_plane, so the canonical one-liner is
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//! re-stated here — keep the two in sync.)
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/// Admission sampling probability under the unified ε-floor law,
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/// `p = 1/(1 + ε²·rate)`.
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///
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1.0 / (1.0 + epsilon * epsilon * rate)
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}
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/// GOS budget split (design §7, Layer B) — **exact linear peel**.
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///
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/// The staleness term `ε_st` is a *deterministic worst-case* bound, so it adds
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(eps_sa, eps_st)
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}
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#[cfg(test)]
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mod tests {
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use super::*;
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assert!(derive_sample_p(0.05, 100.0) > derive_sample_p(0.05, 10_000.0));
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assert!(derive_sample_p(0.01, 1000.0) > derive_sample_p(0.10, 1000.0));
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}
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}

‎control_plane/src/main.rs‎

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@@ -1315,12 +1315,6 @@ async fn handle_plan(State(st): State<AppState>, Json(spec): Json<QuerySpec>) ->
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.into_response()
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}
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async fn handle_get_plan(
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State(st): State<AppState>,
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Path(metric): Path<String>,
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.into_response()
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}
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/// Bootstrap YAML config for agent collectors.
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///
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/// Collectors start with:
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.with_context(|| format!("emit_for_runtime failed for `{metric}`"))
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}
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/// Returns the current EMA cost model state — blended benchmark + observed costs
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/// per sketch type. Useful for diagnosing whether the online cost model has
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/// received sufficient observations to meaningfully influence plan selection.

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