diff --git a/hive-c0re/src/otel_migrate.rs b/hive-c0re/src/otel_migrate.rs index e67d4887..e7d2342a 100644 --- a/hive-c0re/src/otel_migrate.rs +++ b/hive-c0re/src/otel_migrate.rs @@ -1,18 +1,27 @@ //! One-shot backfill of historical per-agent turn stats into the OTEL -//! collector as `claude_code.token.usage` metrics, so pre-OTEL history -//! shows up alongside the live telemetry stream. Driven by -//! `hivectl migrate-stats`. +//! collector, so pre-OTEL history shows up alongside the live telemetry +//! stream. Driven by `hivectl migrate-stats`. //! //! Reads each agent's `hyperhive-turn-stats.sqlite` (host path via -//! `Coordinator::agent_harness_dir`) and turns the four per-turn token -//! columns into **cumulative** `claude_code.token.usage` counter samples: -//! one series per `(type, model)`, value = the running total at each -//! turn's end time. Cumulative — not delta — because Prometheus/Mimir -//! family backends silently drop delta sums (the same reason the live -//! export forces cumulative temporality in harness-base.nix). The samples -//! are sent as OTLP/HTTP JSON to `/v1/metrics`. Every -//! datapoint carries `hyperhive-migration="true"` so the backfill is -//! distinguishable from the live stream. +//! `Coordinator::agent_harness_dir`) and emits two **cumulative** counter +//! metrics, matching the live Claude Code shape so the backfill merges +//! into the same series: +//! +//! - `claude_code.token.usage` — the four per-turn token columns, one +//! running-total series per `(type, model, session.id)`, sampled at each +//! turn's end time. +//! - `claude_code.session.count` — one increment per turn, split into +//! `start_type` = `fresh` (a session's first turn) / `continue` (the +//! rest), mirroring the per-turn `--continue` model. +//! +//! Cumulative — not delta — because Prometheus/Mimir family backends +//! silently drop delta sums (the same reason the live export forces +//! cumulative temporality in harness-base.nix). Sent as OTLP/HTTP JSON to +//! `/v1/metrics`. Every datapoint carries +//! `hyperhive-migration="true"` (so the backfill is distinguishable from +//! the live stream) and `terminal.type="non-interactive"`. `session.id` is +//! the db's own session id verbatim when present, else a synthetic +//! reproducible `---migration-`. //! //! Timestamps: `turn_stats.{started_at,ended_at}` are epoch *seconds* //! (see `hive-ag3nt` turn.rs), scaled to nanoseconds for OTLP. @@ -20,12 +29,14 @@ use anyhow::{Context, Result}; use rusqlite::Connection; use serde_json::{Value, json}; -use std::collections::HashMap; +use std::collections::{HashMap, HashSet}; use std::path::Path; use crate::coordinator::Coordinator; -const METRIC: &str = "claude_code.token.usage"; +const TOKEN_METRIC: &str = "claude_code.token.usage"; +const SESSION_METRIC: &str = "claude_code.session.count"; +const TERMINAL_TYPE: &str = "non-interactive"; /// Cap datapoints per POST so a long-lived agent's history is chunked /// into reasonably-sized OTLP requests rather than one huge body. @@ -40,6 +51,12 @@ const TOKEN_TYPES: &[(&str, usize)] = &[ ("cacheCreation", 6), ]; +/// Datapoints collected from one agent's stats db, split by metric. +struct AgentPoints { + token: Vec, + session: Vec, +} + /// Run the migration. `endpoint` falls back to `OTEL_EXPORTER_OTLP_ENDPOINT` /// then `HYPERHIVE_OTEL_ENDPOINT`. `only_agent` limits to one agent. /// `dry_run` reports counts without sending. @@ -74,23 +91,35 @@ pub async fn run( if !db.exists() { continue; } - let points = - collect_agent_points(&db).with_context(|| format!("read turn_stats for {agent}"))?; - if points.is_empty() { + let id_prefix = format!("{swarm}-{hive}-{agent}"); + let pts = collect_agent_points(&db, &id_prefix) + .with_context(|| format!("read turn_stats for {agent}"))?; + let n = pts.token.len() + pts.session.len(); + if n == 0 { println!("{agent}: no token rows, skipping"); continue; } hit_agents += 1; - total_points += points.len(); - println!("{agent}: {} datapoints", points.len()); + total_points += n; + println!( + "{agent}: {} token + {} session datapoints", + pts.token.len(), + pts.session.len() + ); if dry_run { continue; } - for chunk in points.chunks(MAX_DATAPOINTS_PER_POST) { - let payload = build_payload(agent, &hive, &swarm, chunk); + for chunk in pts.token.chunks(MAX_DATAPOINTS_PER_POST) { + let payload = build_payload(agent, &hive, &swarm, TOKEN_METRIC, "tokens", chunk); post(&client, &url, &payload) .await - .with_context(|| format!("POST metrics for {agent}"))?; + .with_context(|| format!("POST token.usage for {agent}"))?; + } + for chunk in pts.session.chunks(MAX_DATAPOINTS_PER_POST) { + let payload = build_payload(agent, &hive, &swarm, SESSION_METRIC, "", chunk); + post(&client, &url, &payload) + .await + .with_context(|| format!("POST session.count for {agent}"))?; } } println!( @@ -104,15 +133,16 @@ pub async fn run( Ok(()) } -/// Build cumulative `claude_code.token.usage` datapoints for one agent's -/// stats db. One running-total series per `(type, model)`; a datapoint is -/// emitted whenever that series' value changes (token delta > 0). -fn collect_agent_points(db: &Path) -> Result> { +/// Build cumulative datapoints for one agent's stats db. `id_prefix` is +/// `--`, used to synthesise a `session.id` for rows +/// whose `session_id` FK is NULL (pre-session-tracking turns). +fn collect_agent_points(db: &Path, id_prefix: &str) -> Result { let conn = Connection::open_with_flags(db, rusqlite::OpenFlags::SQLITE_OPEN_READ_ONLY) .context("open stats db read-only")?; + // session_id last so the token column indices (3..=6) stay stable. let mut stmt = conn.prepare( "SELECT started_at, ended_at, model, input_tokens, output_tokens, \ - cache_read_input_tokens, cache_creation_input_tokens \ + cache_read_input_tokens, cache_creation_input_tokens, session_id \ FROM turn_stats ORDER BY ended_at ASC", )?; let rows = stmt.query_map([], |r| { @@ -124,45 +154,91 @@ fn collect_agent_points(db: &Path) -> Result> { r.get::<_, i64>(4)?, r.get::<_, i64>(5)?, r.get::<_, i64>(6)?, + r.get::<_, Option>(7)?, )) })?; - // (type, model) -> (running total, series start time in nanos string) - let mut series: HashMap<(&'static str, String), (u64, String)> = HashMap::new(); - let mut points: Vec = Vec::new(); + // token.usage: (type, model, session.id) -> (running total, series start nanos). + let mut token_series: HashMap<(&'static str, String, String), (u64, String)> = HashMap::new(); + // session.count: start_type -> (running count, series start nanos). + let mut session_counts: HashMap<&'static str, (u64, String)> = HashMap::new(); + let mut seen_sessions: HashSet = HashSet::new(); + let mut migration_idx: u64 = 0; + let mut token = Vec::new(); + let mut session = Vec::new(); + for row in rows { - let (started, ended, model, inp, out, cache_read, cache_create) = row?; + let (started, ended, model, inp, out, cache_read, cache_create, sid) = row?; let cols = [inp, out, cache_read, cache_create]; let start_nanos = u64::try_from(started).unwrap_or(0) * 1_000_000_000; let time_nanos = (u64::try_from(ended).unwrap_or(0) * 1_000_000_000).to_string(); + + // session.id (verbatim db id, else synthetic) + start_type (a + // session's first turn is fresh; every later turn is continue). + let (session_id, is_fresh) = if let Some(id) = sid { + (id.to_string(), seen_sessions.insert(id)) + } else { + let s = format!("{id_prefix}-migration-{migration_idx}"); + migration_idx += 1; + (s, true) + }; + let start_type = if is_fresh { "fresh" } else { "continue" }; + + // session.count: +1 this turn on the start_type series. + let scount = session_counts + .entry(start_type) + .or_insert_with(|| (0u64, start_nanos.to_string())); + scount.0 += 1; + session.push(json!({ + "asInt": scount.0.to_string(), + "startTimeUnixNano": scount.1.clone(), + "timeUnixNano": time_nanos, + "attributes": [ + {"key": "start_type", "value": {"stringValue": start_type}}, + {"key": "terminal.type", "value": {"stringValue": TERMINAL_TYPE}}, + {"key": "hyperhive-migration", "value": {"stringValue": "true"}}, + ], + })); + + // token.usage: per (type, model, session.id) running total. for &(type_, idx) in TOKEN_TYPES { let val = cols[idx - 3]; if val <= 0 { continue; } - let entry = series - .entry((type_, model.clone())) + let entry = token_series + .entry((type_, model.clone(), session_id.clone())) .or_insert_with(|| (0u64, start_nanos.to_string())); entry.0 += u64::try_from(val).unwrap_or(0); - points.push(json!({ + token.push(json!({ "asInt": entry.0.to_string(), "startTimeUnixNano": entry.1.clone(), "timeUnixNano": time_nanos, "attributes": [ {"key": "type", "value": {"stringValue": type_}}, {"key": "model", "value": {"stringValue": model.clone()}}, + {"key": "session.id", "value": {"stringValue": session_id.clone()}}, + {"key": "terminal.type", "value": {"stringValue": TERMINAL_TYPE}}, {"key": "hyperhive-migration", "value": {"stringValue": "true"}}, ], })); } } - Ok(points) + Ok(AgentPoints { token, session }) } -/// Wrap a chunk of datapoints in an OTLP/HTTP JSON `ExportMetricsServiceRequest`. -/// Resource attributes mirror the live export (`hive-serve-otel`): a fixed -/// `service.name` plus this agent's name and the hive/swarm names. -fn build_payload(agent: &str, hive: &str, swarm: &str, points: &[Value]) -> Value { +/// Wrap a chunk of datapoints in an OTLP/HTTP JSON `ExportMetricsServiceRequest` +/// for one cumulative monotonic Sum metric. Resource attributes mirror the +/// live export (`hive-serve-otel`): a fixed `service.name` plus this agent's +/// name and the hive/swarm names. +fn build_payload( + agent: &str, + hive: &str, + swarm: &str, + metric: &str, + unit: &str, + points: &[Value], +) -> Value { json!({ "resourceMetrics": [{ "resource": {"attributes": [ @@ -174,8 +250,8 @@ fn build_payload(agent: &str, hive: &str, swarm: &str, points: &[Value]) -> Valu "scopeMetrics": [{ "scope": {"name": "hyperhive-migration"}, "metrics": [{ - "name": METRIC, - "unit": "tokens", + "name": metric, + "unit": unit, "sum": { // 2 = AGGREGATION_TEMPORALITY_CUMULATIVE "aggregationTemporality": 2,