diff --git a/OpenTelemetryPlan/Phase9_taskList.md b/OpenTelemetryPlan/Phase9_taskList.md
index e45c5bcd77..a172cd2e52 100644
--- a/OpenTelemetryPlan/Phase9_taskList.md
+++ b/OpenTelemetryPlan/Phase9_taskList.md
@@ -42,7 +42,7 @@ These metrics serve multiple external consumer categories identified during rese
 
 - In `src/libxrpl/nodestore/Database.cpp`, extend existing `beast::insight` registrations to add:
   - Gauge: `node_reads_total` (cumulative read operations)
-  - Gauge: `node_reads_hit` (cache-served reads)
+  - Gauge: `node_reads_hit` (fetches that found an object — not a cache hit; `fetchHitCount_` increments whatever served the fetch)
   - Gauge: `node_writes` (cumulative write operations)
   - Gauge: `node_written_bytes` (cumulative bytes written)
   - Gauge: `node_read_bytes` (cumulative bytes read)
diff --git a/docker/telemetry/grafana/dashboards/ledger-data-sync.json b/docker/telemetry/grafana/dashboards/ledger-data-sync.json
index 755d040a85..8d27906799 100644
--- a/docker/telemetry/grafana/dashboards/ledger-data-sync.json
+++ b/docker/telemetry/grafana/dashboards/ledger-data-sync.json
@@ -1481,7 +1481,7 @@
     },
     {
       "title": "NodeStore Read Latency (Bottleneck Discriminator)",
-      "description": "###### What this is:\n*The single measurement that separates the two ways a ledger sync stalls. Both modes look identical from the job queue -- the ledgerData lane sits at its concurrency limit of 3 with work waiting -- so lane occupancy on its own diagnoses nothing. Read latency does separate them, because the two modes load opposite ends of the storage path.*\n\n###### How it's computed:\n*Two views of the same quantity. Lifetime is the nodestore_state{metric=\"read_mean_us\"} gauge, which is total fetch microseconds divided by total fetches since process start, so it moves slowly and shows the run as a whole. Windowed is rate(node_reads_duration_us) / rate(node_reads_total) over the panel interval, so it reacts within one scrape. The axis is logarithmic because the two modes differ by more than an order of magnitude and a linear axis flattens the lower one.*\n\n###### Reading it:\n*Below about 10 microseconds per read means the backend is answering from the page cache and reads are not the constraint; if the lane is still full, the cost is on the write side -- check NuDB Writer Queue Depth next. Above about 100 microseconds per read, together with a high hit ratio on NuDB Cache Hit Ratio, means objects are being found but paid for with disk latency on every access. High latency with a low hit ratio is a different thing again: the working set does not fit and misses are scanning every backend. The threshold lines at 10 and 100 mark the two boundaries.*\n\n###### Healthy range:\n*Single-digit microseconds per read on a warm synced node, with lifetime and windowed close together.*\n\n###### Watch for:\n*Windowed rising well above lifetime: the recent window is much worse than the run average, which is the earliest reading of a cache that has just gone cold. A measured cold-read episode peaked at 223 microseconds and settled in the 13-35 range while still hitting 88 percent or better, and that shape hung a node for roughly 25 minutes. Also treat a flat 8-9 microsecond line during a stall as informative rather than reassuring -- it rules reads out and points at the write path.*\n\n###### Source:\n[nodestore/backend/NuDBFactory.cpp](https://github.com/XRPLF/rippled/blob/develop/src/libxrpl/nodestore/backend/NuDBFactory.cpp)\n\n###### Function:\n`Database::getFetchDurationUs / NuDB backend read path`",
+      "description": "###### What this is:\n*The single measurement that separates the two ways a ledger sync stalls. Both modes look identical from the job queue -- the ledgerData lane sits at its concurrency limit of 3 with work waiting -- so lane occupancy on its own diagnoses nothing. Read latency does separate them, because the two modes load opposite ends of the storage path.*\n\n###### How it's computed:\n*Two views of the same quantity. Lifetime is the nodestore_state{metric=\"read_mean_us\"} gauge, which is total fetch microseconds divided by total fetches since process start, so it moves slowly and shows the run as a whole. Windowed is rate(node_reads_duration_us) / rate(node_reads_total) over the panel interval, so it reacts within one scrape. The axis is logarithmic because the two modes differ by more than an order of magnitude and a linear axis flattens the lower one.*\n\n###### Reading it:\n*Below about 10 microseconds per read means the backend is answering from the page cache and reads are not the constraint; if the lane is still full, the cost is on the write side -- check NuDB Writer Queue Depth next. Above about 100 microseconds per read, together with a high found ratio on NuDB Read Found Ratio, means objects are being found but paid for with disk latency on every access. High latency with a low found ratio is a different thing again: the working set does not fit and misses are scanning every backend. The threshold lines at 10 and 100 mark the two boundaries.*\n\n###### Healthy range:\n*Single-digit microseconds per read on a warm synced node, with lifetime and windowed close together.*\n\n###### Watch for:\n*Windowed rising well above lifetime: the recent window is much worse than the run average, which is the earliest reading of a cache that has just gone cold. A measured cold-read episode peaked at 223 microseconds and settled in the 13-35 range while still hitting 88 percent or better, and that shape hung a node for roughly 25 minutes. Also treat a flat 8-9 microsecond line during a stall as informative rather than reassuring -- it rules reads out and points at the write path.*\n\n###### Source:\n[nodestore/backend/NuDBFactory.cpp](https://github.com/XRPLF/rippled/blob/develop/src/libxrpl/nodestore/backend/NuDBFactory.cpp)\n\n###### Function:\n`Database::getFetchDurationUs / NuDB backend read path`",
       "type": "timeseries",
       "gridPos": {
         "h": 8,
diff --git a/docker/telemetry/grafana/dashboards/node-health.json b/docker/telemetry/grafana/dashboards/node-health.json
index 2564a7195d..61379e639e 100644
--- a/docker/telemetry/grafana/dashboards/node-health.json
+++ b/docker/telemetry/grafana/dashboards/node-health.json
@@ -485,7 +485,7 @@
     },
     {
       "title": "NodeStore Throughput",
-      "description": "###### What this is:\n*Cumulative object-store read, cache-hit, and write operation counts.*\n\n###### How it's computed:\n*Current values of the read, cache-hit, and write counters, plotted as lines.*\n\n###### Reading it:\n*Steadily rising lines are normal; the slope reflects store activity.*\n\n###### Healthy range:\n*Reads and writes rising smoothly, with cache-hits tracking a good fraction of reads.*\n\n###### Watch for:\n*A sudden surge in reads or writes signals heavy back-end I/O, from sync, replay, or query load.*\n\n###### Source:\n[MetricsRegistry.cpp](https://github.com/XRPLF/rippled/blob/develop/src/xrpld/telemetry/MetricsRegistry.cpp)\n\n###### Function:\n`registerNodeStoreGauge`",
+      "description": "###### What this is:\n*Object-store read, found and write operation rates. The found series is `node_reads_hit`, which counts fetches that returned an object whatever served them, so it is not a cache-hit count.*\n\n###### How it's computed:\n*Per-second rates of the read, found and write counters, plotted as lines.*\n\n###### Reading it:\n*Steadily rising lines are normal; the slope reflects store activity.*\n\n###### Healthy range:\n*Reads and writes rising smoothly, with found tracking almost all reads on a node that has the data.*\n\n###### Watch for:\n*A sudden surge in reads or writes signals heavy back-end I/O, from sync, replay, or query load.*\n\n###### Source:\n[MetricsRegistry.cpp](https://github.com/XRPLF/rippled/blob/develop/src/xrpld/telemetry/MetricsRegistry.cpp)\n\n###### Function:\n`registerNodeStoreGauge`",
       "type": "timeseries",
       "gridPos": {
         "x": 0,
@@ -512,7 +512,7 @@
           "datasource": {
             "type": "prometheus"
           },
-          "expr": "label_replace(rate(nodestore_state{service_instance_id=~\"$node\", deployment_environment=~\"$deployment_environment\", xrpl_network_type=~\"$xrpl_network_type\", service_name=~\"$service_name\", xrpl_work_item=~\"$xrpl_work_item\", xrpl_branch=~\"$xrpl_branch\", xrpl_node_role=~\"$xrpl_node_role\", metric=\"node_reads_hit\"}[$__rate_interval]), \"series\", \"Reads Hit (cache)\", \"\", \"\")",
+          "expr": "label_replace(rate(nodestore_state{service_instance_id=~\"$node\", deployment_environment=~\"$deployment_environment\", xrpl_network_type=~\"$xrpl_network_type\", service_name=~\"$service_name\", xrpl_work_item=~\"$xrpl_work_item\", xrpl_branch=~\"$xrpl_branch\", xrpl_node_role=~\"$xrpl_node_role\", metric=\"node_reads_hit\"}[$__rate_interval]), \"series\", \"Reads Found\", \"\", \"\")",
           "refId": "B"
         },
         {
@@ -542,8 +542,8 @@
       }
     },
     {
-      "title": "NodeStore Cache Hit Ratio",
-      "description": "###### What this is:\n*Cumulative object-store read, cache-hit, and write operation counts.*\n\n###### How it's computed:\n*Current values of the read, cache-hit, and write counters, plotted as lines.*\n\n###### Reading it:\n*Steadily rising lines are normal; the slope reflects store activity.*\n\n###### Healthy range:\n*Reads and writes rising smoothly, with cache-hits tracking a good fraction of reads.*\n\n###### Watch for:\n*A sudden surge in reads or writes signals heavy back-end I/O, from sync, replay, or query load.*\n\n###### Source:\n[MetricsRegistry.cpp](https://github.com/XRPLF/rippled/blob/develop/src/xrpld/telemetry/MetricsRegistry.cpp)\n\n###### Function:\n`registerNodeStoreGauge`",
+      "title": "NodeStore Read Found Ratio",
+      "description": "###### What this is:\n*Fraction of object-store fetches that found the object they asked for. This is not a cache hit ratio: `node_reads_hit` counts every fetch that returned an object, whatever served it, so a fetch that went all the way to disk still counts here.*\n\n###### How it's computed:\n*Rate of node_reads_hit divided by rate of node_reads_total over the panel interval.*\n\n###### Reading it:\n*Normally sits near 1.0 (100%) on any node that has the data, warm or cold. It does not fall when the page cache goes cold.*\n\n###### Healthy range:\n*Near 1.0. A ratio well below 1.0 means fetches are missing, which points at a gap in local history rather than at cache pressure.*\n\n###### Watch for:\n*Never read this panel on its own. A ~100% found ratio at over 100 microseconds per read is the cold-read signature, not a healthy cache: the data is found every time and paid for every time. Pair it with read latency.*\n\n###### Source:\n[nodestore/Database.cpp](https://github.com/XRPLF/rippled/blob/develop/src/libxrpl/nodestore/Database.cpp)\n\n###### Function:\n`Database::fetchNodeObject`",
       "type": "timeseries",
       "gridPos": {
         "x": 12,
@@ -564,7 +564,7 @@
             "type": "prometheus",
             "uid": "${DS_PROMETHEUS}"
           },
-          "expr": "label_replace(rate(nodestore_state{service_instance_id=~\"$node\", deployment_environment=~\"$deployment_environment\", xrpl_network_type=~\"$xrpl_network_type\", service_name=~\"$service_name\", xrpl_work_item=~\"$xrpl_work_item\", xrpl_branch=~\"$xrpl_branch\", xrpl_node_role=~\"$xrpl_node_role\", metric=\"node_reads_hit\"}[$__rate_interval]) / ignoring(metric) rate(nodestore_state{service_instance_id=~\"$node\", deployment_environment=~\"$deployment_environment\", xrpl_network_type=~\"$xrpl_network_type\", service_name=~\"$service_name\", xrpl_work_item=~\"$xrpl_work_item\", xrpl_branch=~\"$xrpl_branch\", xrpl_node_role=~\"$xrpl_node_role\", metric=\"node_reads_total\"}[$__rate_interval]), \"series\", \"Cache Hit Ratio\", \"\", \"\")",
+          "expr": "label_replace(rate(nodestore_state{service_instance_id=~\"$node\", deployment_environment=~\"$deployment_environment\", xrpl_network_type=~\"$xrpl_network_type\", service_name=~\"$service_name\", xrpl_work_item=~\"$xrpl_work_item\", xrpl_branch=~\"$xrpl_branch\", xrpl_node_role=~\"$xrpl_node_role\", metric=\"node_reads_hit\"}[$__rate_interval]) / ignoring(metric) rate(nodestore_state{service_instance_id=~\"$node\", deployment_environment=~\"$deployment_environment\", xrpl_network_type=~\"$xrpl_network_type\", service_name=~\"$service_name\", xrpl_work_item=~\"$xrpl_work_item\", xrpl_branch=~\"$xrpl_branch\", xrpl_node_role=~\"$xrpl_node_role\", metric=\"node_reads_total\"}[$__rate_interval]), \"series\", \"Found Ratio\", \"\", \"\")",
           "refId": "A"
         }
       ],
@@ -573,7 +573,7 @@
           "displayName": "${__field.labels.series} [${__field.labels.service_instance_id} ${__field.labels.xrpl_branch} ${__field.labels.xrpl_node_role} ${__field.labels.xrpl_work_item}]",
           "unit": "percentunit",
           "custom": {
-            "axisLabel": "Operations / Sec",
+            "axisLabel": "Found Ratio",
             "drawStyle": "line",
             "lineWidth": 2,
             "fillOpacity": 10,
@@ -1347,8 +1347,8 @@
       }
     },
     {
-      "title": "NuDB Storage Size",
-      "description": "###### What this is:\n*On-disk size of the NuDB object-store back end, in bytes.*\n\n###### How it's computed:\n*Current value of the NuDB storage-size gauge, plotted over time.*\n\n###### Reading it:\n*A smoothly growing line is normal; the slope is the data growth rate.*\n\n###### Healthy range:\n*Gradual growth consistent with retained ledger history.*\n\n###### Watch for:\n*A sudden jump in growth rate can indicate runaway storage or an unexpected back-fill.*\n\n###### Source:\n[MetricsRegistry.cpp](https://github.com/XRPLF/rippled/blob/develop/src/xrpld/telemetry/MetricsRegistry.cpp)\n\n###### Function:\n`registerStorageDetailGauge`",
+      "title": "NuDB Stored Bytes",
+      "description": "###### What this is:\n*Cumulative object-payload bytes this process has written to the NuDB object-store back end. Despite the metric name, this is not the size of the store on disk.*\n\n###### How it's computed:\n*Current value of the nudb_bytes gauge, plotted over time. It observes getStoreSize(), the same accessor node_written_bytes uses, so the two series are equal and their ratio is a constant 1.0 rather than a write-amplification measure.*\n\n###### Reading it:\n*A smoothly growing line is normal; the slope is the write rate. It excludes NuDB's keys, bucket padding and log, and it restarts from zero with the process while the files on disk do not.*\n\n###### Healthy range:\n*Gradual growth consistent with ledger data being stored.*\n\n###### Watch for:\n*A sudden jump in growth rate can indicate runaway storage or an unexpected back-fill. Do not use this panel to size the store on disk or to plan disk capacity; no metric reports on-disk size today, so check the filesystem directly.*\n\n###### Source:\n[MetricsRegistry.cpp](https://github.com/XRPLF/rippled/blob/develop/src/xrpld/telemetry/MetricsRegistry.cpp)\n\n###### Function:\n`registerStorageDetailGauge`",
       "type": "timeseries",
       "gridPos": {
         "h": 8,
@@ -1368,7 +1368,7 @@
           "datasource": {
             "type": "prometheus"
           },
-          "expr": "label_replace(storage_detail{service_instance_id=~\"$node\", deployment_environment=~\"$deployment_environment\", xrpl_network_type=~\"$xrpl_network_type\", service_name=~\"$service_name\", xrpl_work_item=~\"$xrpl_work_item\", xrpl_branch=~\"$xrpl_branch\", xrpl_node_role=~\"$xrpl_node_role\", metric=\"nudb_bytes\"}, \"series\", \"NuDB Size\", \"\", \"\")"
+          "expr": "label_replace(storage_detail{service_instance_id=~\"$node\", deployment_environment=~\"$deployment_environment\", xrpl_network_type=~\"$xrpl_network_type\", service_name=~\"$service_name\", xrpl_work_item=~\"$xrpl_work_item\", xrpl_branch=~\"$xrpl_branch\", xrpl_node_role=~\"$xrpl_node_role\", metric=\"nudb_bytes\"}, \"series\", \"NuDB Stored Bytes\", \"\", \"\")"
         }
       ],
       "fieldConfig": {
@@ -1376,7 +1376,7 @@
           "displayName": "${__field.labels.series} [${__field.labels.service_instance_id} ${__field.labels.xrpl_branch} ${__field.labels.xrpl_node_role} ${__field.labels.xrpl_work_item}]",
           "unit": "decbytes",
           "custom": {
-            "axisLabel": "Size",
+            "axisLabel": "Stored Bytes",
             "drawStyle": "line",
             "lineWidth": 2,
             "fillOpacity": 10,