docs(grafana): sample dashboards for API latency & backend hot-path (refs #7)

Author: pmcfadin

docs/grafana/api_latency_by_route.json

@@ -0,0 +1,59 @@
+{
+  "__inputs": [],
+  "__requires": [],
+  "annotations": {
+    "list": []
+  },
+  "editable": true,
+  "gnetId": null,
+  "graphTooltip": 0,
+  "id": null,
+  "iteration": 1650000000000,
+  "links": [],
+  "panels": [
+    {
+      "datasource": "Prometheus",
+      "fieldConfig": {
+        "defaults": {
+          "unit": "s"
+        },
+        "overrides": []
+      },
+      "gridPos": {
+        "h": 9,
+        "w": 24,
+        "x": 0,
+        "y": 0
+      },
+      "id": 1,
+      "options": {
+        "showHeader": true
+      },
+      "title": "HTTP Request Duration p95 by Route",
+      "type": "timeseries",
+      "targets": [
+        {
+          "expr": "histogram_quantile(0.95, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, handler))",
+          "legendFormat": "{{handler}}",
+          "refId": "A"
+        }
+      ]
+    }
+  ],
+  "refresh": "10s",
+  "schemaVersion": 36,
+  "style": "dark",
+  "tags": ["killrvideo", "latency"],
+  "templating": {
+    "list": []
+  },
+  "time": {
+    "from": "now-30m",
+    "to": "now"
+  },
+  "timepicker": {},
+  "timezone": "browser",
+  "title": "KillrVideo – API Latency by Route",
+  "uid": "kv-api-latency",
+  "version": 1
+} 

docs/grafana/backend_hot_path.json

@@ -0,0 +1,69 @@
+{
+  "schemaVersion": 36,
+  "title": "KillrVideo – Backend Hot-Path Latency (p95)",
+  "uid": "kv-hotpath",
+  "timezone": "browser",
+  "panels": [
+    {
+      "type": "timeseries",
+      "title": "Astra DB Query p95",
+      "id": 1,
+      "gridPos": {"h": 8, "w": 24, "x": 0, "y": 0},
+      "datasource": "Prometheus",
+      "fieldConfig": {"defaults": {"unit": "s"}},
+      "targets": [
+        {
+          "expr": "histogram_quantile(0.95, sum(rate(astra_db_query_duration_seconds_bucket[5m])) by (le))",
+          "refId": "A"
+        }
+      ]
+    },
+    {
+      "type": "timeseries",
+      "title": "YouTube Fetch p95",
+      "id": 2,
+      "gridPos": {"h": 8, "w": 24, "x": 0, "y": 8},
+      "datasource": "Prometheus",
+      "fieldConfig": {"defaults": {"unit": "s"}},
+      "targets": [
+        {
+          "expr": "histogram_quantile(0.95, sum(rate(youtube_fetch_duration_seconds_bucket[5m])) by (le, method))",
+          "legendFormat": "{{method}}",
+          "refId": "A"
+        }
+      ]
+    },
+    {
+      "type": "timeseries",
+      "title": "Vector Search p95",
+      "id": 3,
+      "gridPos": {"h": 8, "w": 24, "x": 0, "y": 16},
+      "datasource": "Prometheus",
+      "fieldConfig": {"defaults": {"unit": "s"}},
+      "targets": [
+        {
+          "expr": "histogram_quantile(0.95, sum(rate(vector_search_duration_seconds_bucket[5m])) by (le))",
+          "refId": "A"
+        }
+      ]
+    },
+    {
+      "type": "timeseries",
+      "title": "Recommendation Generation p95",
+      "id": 4,
+      "gridPos": {"h": 8, "w": 24, "x": 0, "y": 24},
+      "datasource": "Prometheus",
+      "fieldConfig": {"defaults": {"unit": "s"}},
+      "targets": [
+        {
+          "expr": "histogram_quantile(0.95, sum(rate(recommendation_generation_duration_seconds_bucket[5m])) by (le))",
+          "refId": "A"
+        }
+      ]
+    }
+  ],
+  "time": {"from": "now-30m", "to": "now"},
+  "refresh": "10s",
+  "tags": ["killrvideo", "performance"],
+  "editable": true
+}