juicebox-observability

# Juicebox Observability ## Overview Juicebox provides AI-powered people search and analysis where query performance, dataset ingestion rates, and quota consumption are the primary observability concerns. Monitor analysis completion times to ensure interactive UX, track ingestion pipeline health for data freshness, and watch quota usage to prevent mid-workflow cutoffs. Slow queries or failed ingestions degrade recruiter productivity and data accuracy. ## Key Metrics | Metric | Type | Target | Alert Threshold | |--------|------|--------|-----------------| | Search latency p95 | Histogram | < 2s | > 5s | | Analysis completion time | Histogram | < 10s | > 30s | | Dataset ingestion rate | Gauge | > 100 records/s | < 50 records/s | | API error rate | Gauge | < 1% | > 5% | | Quota usage (daily) | Gauge | < 70% | > 85% | | Query result relevance | Gauge | > 80% precision | < 60% | ## Instrumentation ```typescript async function trackJuiceboxCall(operation: string, fn: () => Promise<any>) { const start = Date.now(); try { const result = await fn(); metrics.histogram('juicebox.api.latency', Date.now() - start, { operation }); metrics.increment('juicebox.api.calls', { operation, status: 'ok' }); return result; } catch (err) { metrics.increment('juicebox.api.errors', { operation, error: err.code }); throw err; } } ``` ## Health Check Dashboard ```typescript async function juiceboxHealth(): Promise<Record<string, string>> { const searchP95 = awai...