mirror of
https://github.com/Memo-2023/mana-monorepo.git
synced 2026-05-16 16:19:40 +02:00
169821de1a
Wire mana-llm service into the monitoring stack: Prometheus (docker/prometheus/prometheus.yml): - Add mana-llm scrape job (port 3025, 15s interval) - Include mana-llm in ServiceDown alert expression Alerts (docker/prometheus/alerts.yml): - New llm_alerts group with 4 rules: - LLMServiceDown: mana-llm down > 1 min (critical) - LLMHighErrorRate: > 10% errors for 5 min (warning) - OllamaProviderDown: > 50% requests via Google fallback (warning) - LLMSlowResponses: p95 > 30s for 5 min (warning) Grafana Dashboard (docker/grafana/dashboards/mana-llm.json): - 6 stat panels: status, req/min, error rate, fallback rate, latency, tokens/min - Requests by Provider (stacked area: Ollama vs Google vs OpenRouter) - Tokens by Type (prompt vs completion) - Latency Percentiles (p50, p90, p99) - Latency by Provider comparison - Requests by Model breakdown - Errors by Type - Google Fallback Rate over time (with threshold coloring) - Provider Distribution pie chart (24h) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
422 lines
11 KiB
JSON
422 lines
11 KiB
JSON
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"includeVars": true,
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"tags": [],
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"targetBlank": false,
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"title": "Master Overview",
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"type": "link",
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"url": "/d/master-overview/master-overview"
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"fieldConfig": {
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"defaults": {
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"color": { "mode": "thresholds" },
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"mappings": [
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{
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"options": {
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"0": { "color": "red", "index": 1, "text": "DOWN" },
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"1": { "color": "green", "index": 0, "text": "UP" }
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"colorMode": "background",
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"graphMode": "none",
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"reduceOptions": { "calcs": ["lastNotNull"] }
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},
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"title": "mana-llm Status",
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"type": "stat",
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"targets": [{ "expr": "up{job=\"mana-llm\"}", "legendFormat": "Status" }]
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"reduceOptions": { "calcs": ["lastNotNull"] }
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"title": "Requests / min",
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"type": "stat",
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"targets": [
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{ "expr": "sum(rate(mana_llm_llm_requests_total[5m])) * 60", "legendFormat": "req/min" }
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"graphMode": "area",
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"reduceOptions": { "calcs": ["lastNotNull"] }
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},
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"title": "Error Rate",
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"type": "stat",
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"targets": [
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{
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"expr": "sum(rate(mana_llm_llm_errors_total[5m])) / (sum(rate(mana_llm_llm_requests_total[5m])) + 0.001) * 100",
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"legendFormat": "errors"
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]
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"graphMode": "area",
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"reduceOptions": { "calcs": ["lastNotNull"] }
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},
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"title": "Google Fallback Rate",
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"type": "stat",
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"targets": [
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{
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"expr": "sum(rate(mana_llm_llm_requests_total{provider=\"google\"}[5m])) / (sum(rate(mana_llm_llm_requests_total[5m])) + 0.001) * 100",
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"legendFormat": "fallback %"
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"colorMode": "value",
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"graphMode": "area",
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"reduceOptions": { "calcs": ["lastNotNull"] }
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},
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"title": "Avg Latency (p50)",
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"type": "stat",
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"targets": [
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{
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"expr": "histogram_quantile(0.50, sum(rate(mana_llm_llm_latency_seconds_bucket[5m])) by (le))",
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"legendFormat": "p50"
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}
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"graphMode": "area",
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"reduceOptions": { "calcs": ["lastNotNull"] }
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},
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"title": "Tokens / min",
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"type": "stat",
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"targets": [
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{ "expr": "sum(rate(mana_llm_tokens_total[5m])) * 60", "legendFormat": "tok/min" }
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]
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},
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"gridPos": { "h": 1, "w": 24, "x": 0, "y": 5 },
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"id": 10,
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"panels": [],
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"title": "Request Traffic",
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"type": "row"
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},
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"custom": { "fillOpacity": 30, "stacking": { "mode": "normal" } },
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"unit": "reqps"
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}
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},
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"options": {
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"legend": { "displayMode": "table", "placement": "bottom", "calcs": ["sum", "mean"] }
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},
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"title": "LLM Requests by Provider",
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"type": "timeseries",
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"targets": [
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{
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"expr": "sum(rate(mana_llm_llm_requests_total{provider=\"ollama\"}[5m])) by (provider)",
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"legendFormat": "Ollama"
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},
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{
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"expr": "sum(rate(mana_llm_llm_requests_total{provider=\"google\"}[5m])) by (provider)",
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"legendFormat": "Google (Fallback)"
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},
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{
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"expr": "sum(rate(mana_llm_llm_requests_total{provider=\"openrouter\"}[5m])) by (provider)",
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"legendFormat": "OpenRouter"
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}
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]
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},
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"options": {
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"legend": { "displayMode": "table", "placement": "bottom", "calcs": ["sum", "mean"] }
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},
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"title": "Tokens by Type",
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"type": "timeseries",
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"targets": [
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{
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"expr": "sum(rate(mana_llm_tokens_total{type=\"prompt\"}[5m])) * 60",
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"legendFormat": "Prompt Tokens/min"
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},
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{
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"expr": "sum(rate(mana_llm_tokens_total{type=\"completion\"}[5m])) * 60",
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"legendFormat": "Completion Tokens/min"
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}
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]
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},
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{
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"collapsed": false,
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"gridPos": { "h": 1, "w": 24, "x": 0, "y": 14 },
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"id": 20,
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"panels": [],
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"title": "Latency & Performance",
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"type": "row"
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},
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"fieldConfig": { "defaults": { "unit": "s", "custom": { "fillOpacity": 10 } } },
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"gridPos": { "h": 8, "w": 12, "x": 0, "y": 15 },
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"id": 21,
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"options": { "legend": { "displayMode": "table", "placement": "bottom" } },
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"title": "LLM Latency Percentiles",
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"type": "timeseries",
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"targets": [
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{
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"expr": "histogram_quantile(0.50, sum(rate(mana_llm_llm_latency_seconds_bucket[5m])) by (le))",
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"legendFormat": "p50"
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},
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{
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"expr": "histogram_quantile(0.90, sum(rate(mana_llm_llm_latency_seconds_bucket[5m])) by (le))",
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"legendFormat": "p90"
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},
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{
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"expr": "histogram_quantile(0.99, sum(rate(mana_llm_llm_latency_seconds_bucket[5m])) by (le))",
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"legendFormat": "p99"
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}
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]
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},
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"fieldConfig": {
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"defaults": { "unit": "s", "custom": { "fillOpacity": 30, "stacking": { "mode": "none" } } }
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},
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"gridPos": { "h": 8, "w": 12, "x": 12, "y": 15 },
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"id": 22,
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"options": { "legend": { "displayMode": "table", "placement": "bottom" } },
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"title": "Latency by Provider (p50)",
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"type": "timeseries",
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"targets": [
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{
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"expr": "histogram_quantile(0.50, sum(rate(mana_llm_llm_latency_seconds_bucket{provider=\"ollama\"}[5m])) by (le))",
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"legendFormat": "Ollama p50"
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},
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{
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"expr": "histogram_quantile(0.50, sum(rate(mana_llm_llm_latency_seconds_bucket{provider=\"google\"}[5m])) by (le))",
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"legendFormat": "Google p50"
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}
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]
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},
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{
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"collapsed": false,
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"gridPos": { "h": 1, "w": 24, "x": 0, "y": 23 },
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"id": 30,
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"panels": [],
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"title": "Models & Errors",
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"type": "row"
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},
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"fieldConfig": { "defaults": { "unit": "reqps", "custom": { "fillOpacity": 30 } } },
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"gridPos": { "h": 8, "w": 12, "x": 0, "y": 24 },
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"id": 31,
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"options": { "legend": { "displayMode": "table", "placement": "bottom", "calcs": ["sum"] } },
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"title": "Requests by Model",
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"type": "timeseries",
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"targets": [
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{
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"expr": "sum(rate(mana_llm_llm_requests_total[5m])) by (model)",
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"legendFormat": "{{ model }}"
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}
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]
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},
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"fieldConfig": { "defaults": { "unit": "short", "custom": { "fillOpacity": 30 } } },
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"gridPos": { "h": 8, "w": 12, "x": 12, "y": 24 },
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"id": 32,
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"options": { "legend": { "displayMode": "table", "placement": "bottom", "calcs": ["sum"] } },
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"title": "Errors by Type",
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"type": "timeseries",
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"targets": [
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{
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"expr": "sum(rate(mana_llm_llm_errors_total[5m])) by (error_type)",
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"legendFormat": "{{ error_type }}"
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}
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]
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},
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{
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"collapsed": false,
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"gridPos": { "h": 1, "w": 24, "x": 0, "y": 32 },
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"id": 40,
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"panels": [],
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"title": "Fallback Analysis",
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"type": "row"
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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{ "color": "yellow", "value": 10 },
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{ "color": "red", "value": 50 }
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]
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}
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}
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},
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"gridPos": { "h": 8, "w": 12, "x": 0, "y": 33 },
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"id": 41,
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"title": "Google Fallback Rate Over Time",
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"type": "timeseries",
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"targets": [
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{
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"expr": "sum(rate(mana_llm_llm_requests_total{provider=\"google\"}[5m])) / (sum(rate(mana_llm_llm_requests_total[5m])) + 0.001) * 100",
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"legendFormat": "Fallback %"
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}
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]
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},
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{
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"datasource": { "type": "prometheus", "uid": "${datasource}" },
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"fieldConfig": { "defaults": { "unit": "short" } },
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"gridPos": { "h": 8, "w": 12, "x": 12, "y": 33 },
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"id": 42,
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"options": { "legend": { "displayMode": "table", "placement": "bottom", "calcs": ["sum"] } },
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"title": "Provider Request Distribution (Pie)",
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"type": "piechart",
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"targets": [
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{
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"expr": "sum(increase(mana_llm_llm_requests_total{provider=\"ollama\"}[24h]))",
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"legendFormat": "Ollama"
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},
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{
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"expr": "sum(increase(mana_llm_llm_requests_total{provider=\"google\"}[24h]))",
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"legendFormat": "Google"
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},
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{
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"expr": "sum(increase(mana_llm_llm_requests_total{provider=\"openrouter\"}[24h]))",
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"legendFormat": "OpenRouter"
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}
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]
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}
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],
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"schemaVersion": 39,
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"tags": ["mana", "llm", "ai"],
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"templating": {
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"list": [
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{
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"current": { "selected": false, "text": "VictoriaMetrics", "value": "victoria-metrics" },
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"hide": 0,
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"includeAll": false,
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"name": "datasource",
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"options": [],
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"query": "prometheus",
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"type": "datasource"
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}
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]
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},
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"time": { "from": "now-6h", "to": "now" },
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"title": "Mana LLM Gateway",
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"uid": "mana-llm",
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"version": 1
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}
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