diff --git a/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/device_details.json b/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/device_details.json
index f6d895f..ade5a39 100644
--- a/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/device_details.json
+++ b/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/device_details.json
@@ -250,13 +250,75 @@
       "title": "Device Type Tag Over Time",
       "type": "state-timeline"
     },
+    {
+      "datasource": {
+        "type": "influxdb",
+        "uid": "${datasource}"
+      },
+      "fieldConfig": {
+        "defaults": {
+          "color": {
+            "mode": "thresholds"
+          },
+          "mappings": [],
+          "thresholds": {
+            "mode": "absolute",
+            "steps": [
+              {
+                "color": "green"
+              },
+              {
+                "color": "red",
+                "value": 80
+              }
+            ]
+          }
+        },
+        "overrides": []
+      },
+      "gridPos": {
+        "h": 3,
+        "w": 24,
+        "x": 0,
+        "y": 16
+      },
+      "id": 14,
+      "options": {
+        "colorMode": "value",
+        "graphMode": "area",
+        "justifyMode": "auto",
+        "orientation": "auto",
+        "percentChangeColorMode": "standard",
+        "reduceOptions": {
+          "calcs": ["lastNotNull"],
+          "fields": "/.*/",
+          "values": false
+        },
+        "showPercentChange": false,
+        "textMode": "auto",
+        "wideLayout": true
+      },
+      "pluginVersion": "12.0.2",
+      "targets": [
+        {
+          "datasource": {
+            "type": "influxdb",
+            "uid": "${datasource}"
+          },
+          "query": "// Get latest architecture and SoC per device\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  // Use CPU measurement to access the tags\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  // Group by device\n  |> group(columns: [\"${unique_identifier}\"])\n  // Get the latest entry\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Keep only the relevant columns\n  |> keep(columns: [\"${unique_identifier}\", \"architecture\", \"soc\"])\n  // Rename for clarity\n  |> rename(columns: {\n    architecture: \"Architecture\",\n    soc: \"System on Chip\"\n  })",
+          "refId": "A"
+        }
+      ],
+      "title": "Device Architecture & SoC",
+      "type": "stat"
+    },
     {
       "collapsed": false,
       "gridPos": {
         "h": 1,
         "w": 24,
         "x": 0,
-        "y": 16
+        "y": 19
       },
       "id": 4,
       "panels": [],
@@ -298,7 +360,7 @@
         "h": 5,
         "w": 24,
         "x": 0,
-        "y": 17
+        "y": 20
       },
       "id": 3,
       "options": {
@@ -399,7 +461,7 @@
         "h": 8,
         "w": 12,
         "x": 0,
-        "y": 22
+        "y": 25
       },
       "id": 1,
       "options": {
@@ -498,7 +560,7 @@
         "h": 8,
         "w": 12,
         "x": 12,
-        "y": 22
+        "y": 25
       },
       "id": 2,
       "options": {
@@ -613,7 +675,7 @@
         "h": 8,
         "w": 12,
         "x": 0,
-        "y": 30
+        "y": 33
       },
       "id": 12,
       "options": {
@@ -728,7 +790,7 @@
         "h": 8,
         "w": 12,
         "x": 12,
-        "y": 30
+        "y": 33
       },
       "id": 13,
       "options": {
@@ -764,7 +826,7 @@
         "h": 1,
         "w": 24,
         "x": 0,
-        "y": 38
+        "y": 41
       },
       "id": 6,
       "panels": [],
@@ -801,7 +863,7 @@
         "h": 3,
         "w": 24,
         "x": 0,
-        "y": 39
+        "y": 42
       },
       "id": 7,
       "options": {
@@ -826,7 +888,7 @@
             "type": "influxdb",
             "uid": "${datasource}"
           },
-          "query": "  // Get latest local and external IP per device in one query\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  // Select both relevant measurements\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"local_ip_addresses\" or\n    r[\"_measurement\"] == \"external_ip\"\n  )\n  // Group by device and measurement\n  |> group(columns: [\"${unique_identifier}\", \"_measurement\"])\n  // Get the latest entry for each\n  |> last()\n  // Reshape for clarity\n  |> pivot(\n    rowKey: [\"${unique_identifier}\"],\n    columnKey: [\"_measurement\"],\n    valueColumn: \"_value\"\n  )\n  // Optional: Rename columns for clarity\n  |> rename(columns: {\n    local_ip_addresses: \"Local IPs\",\n    external_ip: \"External IP\"\n  })\n  |> keep(columns: [\"${unique_identifier}\", \"Local IPs\", \"External IP\"])",
+          "query": "  // Get latest local and external IP per device in one query\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  // Select both relevant measurements\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"local_ip_addresses\" or\n    r[\"_measurement\"] == \"external_ip\"\n  )\n  // Group by device and measurement\n  |> group(columns: [\"${unique_identifier}\", \"_measurement\"])\n  // Get the latest entry for each\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Reshape for clarity\n  |> pivot(\n    rowKey: [\"${unique_identifier}\"],\n    columnKey: [\"_measurement\"],\n    valueColumn: \"_value\"\n  )\n  // Optional: Rename columns for clarity\n  |> rename(columns: {\n    local_ip_addresses: \"Local IPs\",\n    external_ip: \"External IP\"\n  })\n  |> keep(columns: [\"${unique_identifier}\", \"Local IPs\", \"External IP\"])",
           "refId": "A"
         }
       ],
@@ -897,7 +959,7 @@
         "h": 10,
         "w": 24,
         "x": 0,
-        "y": 42
+        "y": 45
       },
       "id": 8,
       "options": {
@@ -991,7 +1053,7 @@
         "h": 7,
         "w": 24,
         "x": 0,
-        "y": 52
+        "y": 55
       },
       "id": 9,
       "options": {
@@ -1112,5 +1174,5 @@
   "timezone": "browser",
   "title": "Device Details",
   "uid": "bekds38txl1j4c",
-  "version": 36
+  "version": 37
 }
diff --git a/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/overview_of_devices.json b/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/overview_of_devices.json
index 80b9396..e680cd6 100644
--- a/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/overview_of_devices.json
+++ b/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/overview_of_devices.json
@@ -180,7 +180,7 @@
       "targets": [
         {
           "hide": false,
-          "query": "// Get devices with reported data in the selected interval\r\nfrom(bucket: \"${bucket}\")\r\n  // Filter on time\r\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\r\n  // Filter using variable selectors (supports All and multi-select)\r\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\r\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\r\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\r\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\r\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\r\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\r\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\r\n  // We cant flatten if the values are of different types, so we just\r\n  // filter for an arbitrary value that we know exists...\r\n  |> filter(fn: (r) =>\r\n    r[\"_measurement\"] == \"cpu\" and\r\n    r[\"cpu\"] == \"cpu-total\" and\r\n    r[\"_field\"] == \"usage_idle\"\r\n  )\r\n  // Group by device to merge to one time series per device\r\n  |> group(columns: [\"${unique_identifier}\"])\r\n  // Get the last data point for each device. Note that last() does not work after\r\n  // group, so we use sort+limit instead.\r\n  |> sort(columns: [\"_time\"], desc: true)\r\n  |> limit(n: 1)\r\n  // Ungroup to prepare a flat output\r\n  |> group()\r\n  // Keep only timestamp and device identifier\r\n  |> keep(columns: [\"_time\", \"${unique_identifier}\"])\r\n  // Rename _time to seen\r\n  |> rename(columns: {_time: \"seen\"})",
+          "query": "// Get devices with reported data in the selected interval\r\nfrom(bucket: \"${bucket}\")\r\n  // Filter on time\r\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\r\n  // Filter using variable selectors (supports All and multi-select)\r\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\r\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\r\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\r\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\r\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\r\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\r\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\r\n  // We cant flatten if the values are of different types, so we just\r\n  // filter for an arbitrary value that we know exists...\r\n  |> filter(fn: (r) =>\r\n    r[\"_measurement\"] == \"cpu\" and\r\n    r[\"cpu\"] == \"cpu-total\" and\r\n    r[\"_field\"] == \"usage_idle\"\r\n  )\r\n  // Group by device to merge to one time series per device\r\n  |> group(columns: [\"${unique_identifier}\"])\r\n  // Get the last data point for each device. Note that last() does not work after\r\n  // group, so we use sort+limit instead.\r\n  |> sort(columns: [\"_time\"], desc: true)\r\n  |> limit(n: 1)\r\n  // Ungroup to prepare a flat output\r\n  |> group()\r\n  // Keep only timestamp and device identifier\r\n  |> keep(columns: [\"_time\", \"${unique_identifier}\"])\r\n  // Rename _time to seen\r\n  |> rename(columns: {_time: \"seen\"})",
           "refId": "Get last time stamp"
         },
         {
@@ -189,7 +189,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "// Get latest external IP per device in the selected interval\nfrom(bucket: \"${bucket}\")\n  // Filter on time\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter using variable selectors (supports All and multi-select)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  // Filter on external IP measurement\n  |> filter(fn: (r) => r[\"_measurement\"] == \"external_ip\")\n  // Group by device to isolate each host\n  |> group(columns: [\"${unique_identifier}\"])\n  // Get the last reported external IP. Note that last() does not work after\n  // group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Ungroup to flatten result set\n  |> group()\n  // Rename the value column and keep only relevant fields\n  |> rename(columns: {_value: \"external ip\"})\n  |> keep(columns: [\"${unique_identifier}\", \"external ip\"])\n",
+          "query": "// Get latest external IP per device in the selected interval\nfrom(bucket: \"${bucket}\")\n  // Filter on time\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter using variable selectors (supports All and multi-select)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n  // Filter on external IP measurement\n  |> filter(fn: (r) => r[\"_measurement\"] == \"external_ip\")\n  // Group by device to isolate each host\n  |> group(columns: [\"${unique_identifier}\"])\n  // Get the last reported external IP. Note that last() does not work after\n  // group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Ungroup to flatten result set\n  |> group()\n  // Rename the value column and keep only relevant fields\n  |> rename(columns: {_value: \"external ip\"})\n  |> keep(columns: [\"${unique_identifier}\", \"external ip\"])\n",
           "refId": "Get external IPs"
         },
         {
@@ -198,7 +198,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "// Get latest local IP per device in the selected interval\nfrom(bucket: \"${bucket}\")\n  // Filter on time\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter using variable selectors (supports All and multi-select)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  // Filter on local IP measurement\n  |> filter(fn: (r) => r[\"_measurement\"] == \"local_ip_addresses\")\n  // Group by device to isolate each host\n  |> group(columns: [\"${unique_identifier}\"])\n  // Get the last reported local IP. Note that last() does not work after\n  // group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Ungroup to flatten result set\n  |> group()\n  // Rename the value column and keep only relevant fields\n  |> rename(columns: {_value: \"local ip\"})\n  |> keep(columns: [\"${unique_identifier}\", \"local ip\"])\n",
+          "query": "// Get latest local IP per device in the selected interval\nfrom(bucket: \"${bucket}\")\n  // Filter on time\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter using variable selectors (supports All and multi-select)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n  // Filter on local IP measurement\n  |> filter(fn: (r) => r[\"_measurement\"] == \"local_ip_addresses\")\n  // Group by device to isolate each host\n  |> group(columns: [\"${unique_identifier}\"])\n  // Get the last reported local IP. Note that last() does not work after\n  // group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Ungroup to flatten result set\n  |> group()\n  // Rename the value column and keep only relevant fields\n  |> rename(columns: {_value: \"local ip\"})\n  |> keep(columns: [\"${unique_identifier}\", \"local ip\"])\n",
           "refId": "Get internal IPs"
         },
         {
@@ -207,7 +207,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "// Get latest internet latency per device in the selected interval\nfrom(bucket: \"${bucket}\")\n  // Filter on time\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter using variable selectors (supports All and multi-select)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  // Filter on internet connectivity measurement and field\n  |> filter(fn: (r) => r[\"_measurement\"] == \"internet_connectivity\")\n  |> filter(fn: (r) => r[\"_field\"] == \"response_time\")\n  // Group by device to isolate each host\n  |> group(columns: [\"${unique_identifier}\"])\n  // Get the last reported response time. Note that last() does not work after\n  // group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Ungroup to flatten result set\n  |> group()\n  // Rename the value column and keep only relevant fields\n  |> rename(columns: {_value: \"internet latency\"})\n  |> keep(columns: [\"${unique_identifier}\", \"internet latency\"])\n",
+          "query": "// Get latest internet latency per device in the selected interval\nfrom(bucket: \"${bucket}\")\n  // Filter on time\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter using variable selectors (supports All and multi-select)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n  // Filter on internet connectivity measurement and field\n  |> filter(fn: (r) => r[\"_measurement\"] == \"internet_connectivity\")\n  |> filter(fn: (r) => r[\"_field\"] == \"response_time\")\n  // Group by device to isolate each host\n  |> group(columns: [\"${unique_identifier}\"])\n  // Get the last reported response time. Note that last() does not work after\n  // group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Ungroup to flatten result set\n  |> group()\n  // Rename the value column and keep only relevant fields\n  |> rename(columns: {_value: \"internet latency\"})\n  |> keep(columns: [\"${unique_identifier}\", \"internet latency\"])\n",
           "refId": "Internet response time"
         },
         {
@@ -216,7 +216,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "// Get latest device model per device in the selected interval\nfrom(bucket: \"${bucket}\")\n  // Filter on time\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter using variable selectors (supports All and multi-select)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  // Filter on a single meaurement to make the schema aligned\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  // Group by device to isolate each host\n  |> group(columns: [\"${unique_identifier}\"])\n  // Get the last report. Note that last() does not work after\n  // group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Ungroup to flatten result set\n  |> group()\n  // Keep only host and device model\n  |> keep(columns: [\"${unique_identifier}\", \"product_full_name\"])\n  |> rename(columns: {\n    product_full_name: \"product full name\"\n  })",
+          "query": "// Get latest device model per device in the selected interval\nfrom(bucket: \"${bucket}\")\n  // Filter on time\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter using variable selectors (supports All and multi-select)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n  // Filter on a single meaurement to make the schema aligned\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  // Group by device to isolate each host\n  |> group(columns: [\"${unique_identifier}\"])\n  // Get the last report. Note that last() does not work after\n  // group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  // Ungroup to flatten result set\n  |> group()\n  // Keep only host and device model\n  |> keep(columns: [\"${unique_identifier}\", \"product_full_name\"])\n  |> rename(columns: {\n    product_full_name: \"product full name\"\n  })",
           "refId": "Get camera model name"
         },
         {
@@ -225,7 +225,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  |> group(columns: [\"${unique_identifier}\"])\n  // Note that last() does not work after group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  |> group()\n  |> keep(columns: [\"${unique_identifier}\", \"firmware_version\"])\n  |> rename(columns: {\n    firmware_version: \"firmware version\"\n  })\n",
+          "query": "from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  |> group(columns: [\"${unique_identifier}\"])\n  // Note that last() does not work after group, so we use sort+limit instead.\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  |> group()\n  |> keep(columns: [\"${unique_identifier}\", \"firmware_version\"])\n  |> rename(columns: {\n    firmware_version: \"firmware version\"\n  })\n",
           "refId": "A"
         }
       ],
@@ -325,7 +325,7 @@
       "pluginVersion": "12.0.2",
       "targets": [
         {
-          "query": "from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // Generic measurement just to access the tags. To reduce number of points,\n  // we also filter to one single core and field.\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\" and\n\n    // Only show the ones that are reporting firmware_version\n    exists r[\"firmware_version\"] and\n\n    // Applied filters\n    (r[\"area\"] =~ /^${area:regex}$/) and\n    (r[\"geography\"] =~ /^${geography:regex}$/) and\n    (r[\"region\"] =~ /^${region:regex}$/) and\n    (r[\"site\"] =~ /^${site:regex}$/) and\n    (r[\"type\"] =~ /^${type:regex}$/) and\n    (r[\"${unique_identifier}\"] =~ /^${device:regex}$/) and\n    (r[\"product_full_name\"] =~ /^${model:regex}$/)\n  )\n\n  // Aggregate into time series windows to reduce number of returned data points\n  |> aggregateWindow(every: 1h, fn: last, createEmpty: false)\n\n  // Keep timestamp, device and firmware_version\n  |> keep(columns: [\"_time\", \"${unique_identifier}\", \"firmware_version\"])\n\n  // Rename and remap to Grafana-friendly _time, _field, _value,\n  // that gets rid of the \"firmware_version <host>\" prefix in the visualization.\n  |> map(fn: (r) => ({\n    _time: r._time,\n    _field: r[\"${unique_identifier}\"],\n    _value: r[\"firmware_version\"]\n  }))\n\n  // Group per device (now in _field)\n  |> group(columns: [\"_field\"])\n\n  // Sort by time\n  |> sort(columns: [\"_time\"])",
+          "query": "from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // Generic measurement just to access the tags. To reduce number of points,\n  // we also filter to one single core and field.\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\" and\n\n    // Only show the ones that are reporting firmware_version\n    exists r[\"firmware_version\"] and\n\n    // Applied filters\n    (r[\"area\"] =~ /^${area:regex}$/) and\n    (r[\"geography\"] =~ /^${geography:regex}$/) and\n    (r[\"region\"] =~ /^${region:regex}$/) and\n    (r[\"site\"] =~ /^${site:regex}$/) and\n    (r[\"type\"] =~ /^${type:regex}$/) and\n    (r[\"${unique_identifier}\"] =~ /^${device:regex}$/) and\n    (r[\"product_full_name\"] =~ /^${model:regex}$/) and\n    (r[\"architecture\"] =~ /^${architecture:regex}$/) and\n    (r[\"soc\"] =~ /^${soc:regex}$/)\n  )\n\n  // Aggregate into time series windows to reduce number of returned data points\n  |> aggregateWindow(every: 1h, fn: last, createEmpty: false)\n\n  // Keep timestamp, device and firmware_version\n  |> keep(columns: [\"_time\", \"${unique_identifier}\", \"firmware_version\"])\n\n  // Rename and remap to Grafana-friendly _time, _field, _value,\n  // that gets rid of the \"firmware_version <host>\" prefix in the visualization.\n  |> map(fn: (r) => ({\n    _time: r._time,\n    _field: r[\"${unique_identifier}\"],\n    _value: r[\"firmware_version\"]\n  }))\n\n  // Group per device (now in _field)\n  |> group(columns: [\"_field\"])\n\n  // Sort by time\n  |> sort(columns: [\"_time\"])",
           "refId": "A"
         }
       ],
@@ -457,7 +457,7 @@
             "type": "influxdb",
             "uid": "${datasource}"
           },
-          "query": "from(bucket: \"${bucket}\")\n  // Selected time span\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter based on drop-downs\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  // Filter out the fields we are interested in\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  |> filter(fn: (r) => r[\"cpu\"] == \"cpu-total\")\n  |> filter(fn: (r) => r[\"_field\"] == \"usage_idle\")\n  // One time series for each device\n  |> group(columns: [\"${unique_identifier}\"])\n  // Invert to CPU load instead of idle\n  |> map(fn: (r) => ({ r with _value: 100.0 - r._value }))\n  // Aggregate in blocks to reduce number of data points\n  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)",
+          "query": "from(bucket: \"${bucket}\")\n  // Selected time span\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter based on drop-downs\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n  // Filter out the fields we are interested in\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  |> filter(fn: (r) => r[\"cpu\"] == \"cpu-total\")\n  |> filter(fn: (r) => r[\"_field\"] == \"usage_idle\")\n  // One time series for each device\n  |> group(columns: [\"${unique_identifier}\"])\n  // Invert to CPU load instead of idle\n  |> map(fn: (r) => ({ r with _value: 100.0 - r._value }))\n  // Aggregate in blocks to reduce number of data points\n  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)",
           "refId": "cpu"
         },
         {
@@ -466,7 +466,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "from(bucket: \"${bucket}\")\n  // Selected time span\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter based on drop-downs\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  // Filter out the fields we are interested in\n  |> filter(fn: (r) => r[\"_measurement\"] == \"mem\")\n  |> filter(fn: (r) => r[\"_field\"] == \"used_percent\")\n  // One time series for each device\n  |> group(columns: [\"${unique_identifier}\"])\n  // Aggregate in blocks to reduce number of data points\n  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)",
+          "query": "from(bucket: \"${bucket}\")\n  // Selected time span\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  // Filter based on drop-downs\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n  // Filter out the fields we are interested in\n  |> filter(fn: (r) => r[\"_measurement\"] == \"mem\")\n  |> filter(fn: (r) => r[\"_field\"] == \"used_percent\")\n  // One time series for each device\n  |> group(columns: [\"${unique_identifier}\"])\n  // Aggregate in blocks to reduce number of data points\n  |> aggregateWindow(every: v.windowPeriod, fn: mean, createEmpty: false)",
           "refId": "ram"
         }
       ],
@@ -1183,6 +1183,58 @@
         "query": "bekds38txl1j4c",
         "skipUrlSync": true,
         "type": "constant"
+      },
+      {
+        "current": {
+          "selected": true,
+          "text": ["All"],
+          "value": ["$__all"]
+        },
+        "datasource": {
+          "type": "influxdb",
+          "uid": "${datasource}"
+        },
+        "definition": "import \"influxdata/influxdb/schema\"\n\nschema.tagValues(bucket: \"${bucket}\", tag: \"architecture\", start: 1970-01-01T00:00:00Z)",
+        "hide": 0,
+        "includeAll": true,
+        "label": "Architecture",
+        "multi": true,
+        "name": "architecture",
+        "options": [],
+        "query": {
+          "query": "import \"influxdata/influxdb/schema\"\n\nschema.tagValues(bucket: \"${bucket}\", tag: \"architecture\", start: 1970-01-01T00:00:00Z)"
+        },
+        "refresh": 1,
+        "regex": "",
+        "skipUrlSync": false,
+        "sort": 0,
+        "type": "query"
+      },
+      {
+        "current": {
+          "selected": true,
+          "text": ["All"],
+          "value": ["$__all"]
+        },
+        "datasource": {
+          "type": "influxdb",
+          "uid": "${datasource}"
+        },
+        "definition": "import \"influxdata/influxdb/schema\"\n\nschema.tagValues(bucket: \"${bucket}\", tag: \"soc\", start: 1970-01-01T00:00:00Z)",
+        "hide": 0,
+        "includeAll": true,
+        "label": "System on Chip",
+        "multi": true,
+        "name": "soc",
+        "options": [],
+        "query": {
+          "query": "import \"influxdata/influxdb/schema\"\n\nschema.tagValues(bucket: \"${bucket}\", tag: \"soc\", start: 1970-01-01T00:00:00Z)"
+        },
+        "refresh": 1,
+        "regex": "",
+        "skipUrlSync": false,
+        "sort": 0,
+        "type": "query"
       }
     ]
   },
@@ -1194,5 +1246,5 @@
   "timezone": "browser",
   "title": "Overview of Devices",
   "uid": "ceh7yyrnarj7kd",
-  "version": 32
+  "version": 33
 }
diff --git a/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/system_overview.json b/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/system_overview.json
index e87f504..6305391 100644
--- a/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/system_overview.json
+++ b/dashboard-deployments/system-monitoring-influxdb2-flux-grafana/provisioning/dashboards/system_overview.json
@@ -71,7 +71,7 @@
       "pluginVersion": "12.0.2",
       "targets": [
         {
-          "query": "from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  |> filter(fn: (r) => r[\"cpu\"] == \"cpu-total\")\n  |> keep(columns: [\"host\"])\n  |> group()\n  |> distinct(column: \"host\")\n  |> count(column: \"_value\")\n  |> rename(columns: {_value: \"total\"})\n  |> yield(name: \"all\")\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  |> filter(fn: (r) => r[\"cpu\"] == \"cpu-total\")\n  |> keep(columns: [\"host\"])\n  |> group()\n  |> distinct(column: \"host\")\n  |> count(column: \"_value\")\n  |> rename(columns: {_value: \"selected\"})\n  |> yield(name: \"filtered\")",
+          "query": "from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  |> filter(fn: (r) => r[\"cpu\"] == \"cpu-total\")\n  |> keep(columns: [\"host\"])\n  |> group()\n  |> distinct(column: \"host\")\n  |> count(column: \"_value\")\n  |> rename(columns: {_value: \"total\"})\n  |> yield(name: \"all\")\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n  |> filter(fn: (r) => r[\"_measurement\"] == \"cpu\")\n  |> filter(fn: (r) => r[\"cpu\"] == \"cpu-total\")\n  |> keep(columns: [\"host\"])\n  |> group()\n  |> distinct(column: \"host\")\n  |> count(column: \"_value\")\n  |> rename(columns: {_value: \"selected\"})\n  |> yield(name: \"filtered\")",
           "refId": "A"
         }
       ],
@@ -225,7 +225,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "import \"array\"\n\n// Get cameras with reported data in the selected interval\nreal_data = from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\" and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"type\"] =~ /^${type:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/\n  )\n  |> group(columns: [\"host\"])\n  |> last()\n  |> group()\n  |> keep(columns: [\"_time\", \"host\"])\n  |> rename(columns: {_time: \"seen\"})\n  |> map(fn: (r) => ({ r with in_interval: true })) // Add extra field for easier identification\n\n// Dummy fallback row (ensures structure exists even if real data is empty)\nfake_row = array.from(rows: [\n  {\n    host: \"dummy_device\",\n    seen: time(v: 0),\n    in_interval: true,\n    dummy: 1\n  }\n])\n\n// Combine real data with dummy row\nunion(tables: [real_data, fake_row])",
+          "query": "import \"array\"\n\n// Get cameras with reported data in the selected interval\nreal_data = from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\" and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"type\"] =~ /^${type:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/ and\n    r[\"architecture\"] =~ /^${architecture:regex}$/ and\n    r[\"soc\"] =~ /^${soc:regex}$/\n  )\n  |> group(columns: [\"host\"])\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  |> group()\n  |> keep(columns: [\"_time\", \"host\"])\n  |> rename(columns: {_time: \"seen\"})\n  |> map(fn: (r) => ({ r with in_interval: true })) // Add extra field for easier identification\n\n// Dummy fallback row (ensures structure exists even if real data is empty)\nfake_row = array.from(rows: [\n  {\n    host: \"dummy_device\",\n    seen: time(v: 0),\n    in_interval: true,\n    dummy: 1\n  }\n])\n\n// Combine real data with dummy row\nunion(tables: [real_data, fake_row])",
           "refId": "in-interval"
         },
         {
@@ -234,7 +234,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "import \"influxdata/influxdb/schema\"\n\n// Step 1: Get all known hosts\nhosts = schema.tagValues(\n  bucket: \"${bucket}\",\n  tag: \"host\"\n)\n  |> rename(columns: {_value: \"host\"})\n  |> map(fn: (r) => ({ r with known: true }))\n\n// Step 2: Get real data to apply tag-based filters\nfiltered_hosts = from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\" and\n    (exists r[\"area\"] and r[\"area\"] =~ /^${area:regex}$/) and\n    (exists r[\"geography\"] and r[\"geography\"] =~ /^${geography:regex}$/) and\n    (exists r[\"region\"] and r[\"region\"] =~ /^${region:regex}$/) and\n    (exists r[\"site\"] and r[\"site\"] =~ /^${site:regex}$/) and\n    (exists r[\"type\"] and r[\"type\"] =~ /^${type:regex}$/) and\n    (exists r[\"${unique_identifier}\"] and r[\"${unique_identifier}\"] =~ /^${device:regex}$/) and\n    (exists r[\"product_full_name\"] and r[\"product_full_name\"] =~ /^${model:regex}$/)\n  )\n  |> keep(columns: [\"host\"])\n  |> group()\n  |> distinct(column: \"host\")\n\n// Step 3: Join to retain only filtered hosts from schema list\njoin(\n  tables: {all: hosts, filtered: filtered_hosts},\n  on: [\"host\"]\n)\n",
+          "query": "import \"influxdata/influxdb/schema\"\n\n// Step 1: Get all known hosts\nhosts = schema.tagValues(\n  bucket: \"${bucket}\",\n  tag: \"host\"\n)\n  |> rename(columns: {_value: \"host\"})\n  |> map(fn: (r) => ({ r with known: true }))\n\n// Step 2: Get real data to apply tag-based filters\nfiltered_hosts = from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\" and\n    (exists r[\"area\"] and r[\"area\"] =~ /^${area:regex}$/) and\n    (exists r[\"geography\"] and r[\"geography\"] =~ /^${geography:regex}$/) and\n    (exists r[\"region\"] and r[\"region\"] =~ /^${region:regex}$/) and\n    (exists r[\"site\"] and r[\"site\"] =~ /^${site:regex}$/) and\n    (exists r[\"type\"] and r[\"type\"] =~ /^${type:regex}$/) and\n    (exists r[\"${unique_identifier}\"] and r[\"${unique_identifier}\"] =~ /^${device:regex}$/) and\n    (exists r[\"product_full_name\"] and r[\"product_full_name\"] =~ /^${model:regex}$/) and\n    (exists r[\"architecture\"] and r[\"architecture\"] =~ /^${architecture:regex}$/) and\n    (exists r[\"soc\"] and r[\"soc\"] =~ /^${soc:regex}$/)\n  )\n  |> keep(columns: [\"host\"])\n  |> group()\n  |> distinct(column: \"host\")\n\n// Step 3: Join to retain only filtered hosts from schema list\njoin(\n  tables: {all: hosts, filtered: filtered_hosts},\n  on: [\"host\"]\n)",
           "refId": "all_devices"
         },
         {
@@ -243,7 +243,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "// Get last timestamp from a host (check the last 3 months back)\nfrom(bucket: \"${bucket}\")\n  |> range(start: -90d)\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\" and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"type\"] =~ /^${type:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/\n  )\n  |> group(columns: [\"host\"])\n  |> last()\n  |> group()\n  |> keep(columns: [\"_time\", \"host\"])\n  |> rename(columns: {_time: \"last seen\"})\n  |> map(fn: (r) => ({ r with seen_earlier: true })) // Add extra field for easier identification",
+          "query": "// Get last timestamp from a host (check the last 3 months back)\nfrom(bucket: \"${bucket}\")\n  |> range(start: -90d)\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\" and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"type\"] =~ /^${type:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/ and\n    r[\"architecture\"] =~ /^${architecture:regex}$/ and\n    r[\"soc\"] =~ /^${soc:regex}$/\n  )\n  |> group(columns: [\"host\"])\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  |> group()\n  |> keep(columns: [\"_time\", \"host\"])\n  |> rename(columns: {_time: \"last seen\"})\n  |> map(fn: (r) => ({ r with seen_earlier: true })) // Add extra field for easier identification",
           "refId": "last-seen"
         },
         {
@@ -252,7 +252,7 @@
             "uid": "${datasource}"
           },
           "hide": true,
-          "query": "// NOTE: This does not work as expected...\nfrom(bucket: \"${bucket}\")\n  |> range(start: -90d)\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\"\n  )\n  |> group(columns: [\"host\"])\n  |> last()\n  |> group()\n  |> keep(columns: [\"host\", \"area\", \"geography\", \"region\", \"site\", \"type\", \"${unique_identifier}\", \"product_full_name\"])\n  |> map(fn: (r) => ({\n    host: r.host,\n    filter_applies:\n      (\n        (r[\"area\"] =~ /^${area:regex}$/) and\n        (r[\"geography\"] =~ /^${geography:regex}$/) and\n        (r[\"region\"] =~ /^${region:regex}$/) and\n        (r[\"site\"] =~ /^${site:regex}$/) and\n        (r[\"type\"] =~ /^${type:regex}$/) and\n        (r[\"${unique_identifier}\"] =~ /^${device:regex}$/) and\n        (r[\"product_full_name\"] =~ /^${model:regex}$/)\n      )\n  }))\n",
+          "query": "// NOTE: This does not work as expected...\nfrom(bucket: \"${bucket}\")\n  |> range(start: -90d)\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"cpu\" and\n    r[\"cpu\"] == \"cpu-total\" and\n    r[\"_field\"] == \"usage_idle\"\n  )\n  |> group(columns: [\"host\"])\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  |> group()\n  |> keep(columns: [\"host\", \"area\", \"geography\", \"region\", \"site\", \"type\", \"${unique_identifier}\", \"product_full_name\", \"architecture\", \"soc\"])\n  |> map(fn: (r) => ({\n    host: r.host,\n    filter_applies:\n      (\n        (r[\"area\"] =~ /^${area:regex}$/) and\n        (r[\"geography\"] =~ /^${geography:regex}$/) and\n        (r[\"region\"] =~ /^${region:regex}$/) and\n        (r[\"site\"] =~ /^${site:regex}$/) and\n        (r[\"type\"] =~ /^${type:regex}$/) and\n        (r[\"${unique_identifier}\"] =~ /^${device:regex}$/) and\n        (r[\"product_full_name\"] =~ /^${model:regex}$/) and\n        (r[\"architecture\"] =~ /^${architecture:regex}$/) and\n        (r[\"soc\"] =~ /^${soc:regex}$/)\n      )\n  }))",
           "refId": "filter applies"
         }
       ],
@@ -480,7 +480,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "// Get cameras with reported data in the selected interval\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => (\n    r[\"_measurement\"] == \"cpu\" and r[\"cpu\"] == \"cpu-total\" and r[\"_field\"] == \"usage_idle\"\n  ))\n  |> group(columns: [\"host\"])\n  |> first()\n  |> group()\n  |> keep(columns: [\"_time\", \"host\"])\n  |> rename(columns: {_time: \"first seen\"})\n  |> map(fn: (r) => ({ r with in_interval: true })) // Add extra field for easier identification",
+          "query": "// Get cameras with reported data in the selected interval\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) => (\n    r[\"_measurement\"] == \"cpu\" and r[\"cpu\"] == \"cpu-total\" and r[\"_field\"] == \"usage_idle\" and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"type\"] =~ /^${type:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/ and\n    r[\"architecture\"] =~ /^${architecture:regex}$/ and\n    r[\"soc\"] =~ /^${soc:regex}$/\n  ))\n  |> group(columns: [\"host\"])\n  |> first()\n  |> group()\n  |> keep(columns: [\"_time\", \"host\"])\n  |> rename(columns: {_time: \"first seen\"})\n  |> map(fn: (r) => ({ r with in_interval: true })) // Add extra field for easier identification",
           "refId": "in-interval"
         },
         {
@@ -489,7 +489,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "import \"array\"\nimport \"experimental\"\n\n// Make a query the last year before the selected interval starts,\n// that way we can find devices that was now known before the start of this\n// interval.\nbefore_data = from(bucket: \"${bucket}\")\n  |> range(start: experimental.subDuration(from: v.timeRangeStart, d: 365d), stop: v.timeRangeStart) // Before the interval starts\n  |> filter(fn: (r) => (\n    r[\"_measurement\"] == \"cpu\" and r[\"cpu\"] == \"cpu-total\" and r[\"_field\"] == \"usage_idle\"\n  ))\n  |> group(columns: [\"host\"])\n  |> last()\n  |> group()\n  |> keep(columns: [\"_time\", \"host\"])\n  |> map(fn: (r) => ({ r with seen_earlier: true })) // Add extra field for easier identification\n\n// Dummy fallback row to ensure structure\nbefore_dummy =\n  array.from(rows: [{\n    host: \"dummy_device\",\n    _time: time(v: 0),\n    seen_earlier: true,\n    dummy: 1\n  }])\n\n// Combine real before data with fallback\nunion(tables: [before_data, before_dummy])",
+          "query": "import \"array\"\nimport \"experimental\"\n\n// Make a query the last year before the selected interval starts,\n// that way we can find devices that was now known before the start of this\n// interval.\nbefore_data = from(bucket: \"${bucket}\")\n  |> range(start: experimental.subDuration(from: v.timeRangeStart, d: 365d), stop: v.timeRangeStart) // Before the interval starts\n  |> filter(fn: (r) => (\n    r[\"_measurement\"] == \"cpu\" and r[\"cpu\"] == \"cpu-total\" and r[\"_field\"] == \"usage_idle\" and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"type\"] =~ /^${type:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/ and\n    r[\"architecture\"] =~ /^${architecture:regex}$/ and\n    r[\"soc\"] =~ /^${soc:regex}$/\n  ))\n  |> group(columns: [\"host\"])\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1)\n  |> group()\n  |> keep(columns: [\"_time\", \"host\"])\n  |> map(fn: (r) => ({ r with seen_earlier: true })) // Add extra field for easier identification\n\n// Dummy fallback row to ensure structure\nbefore_dummy =\n  array.from(rows: [{\n    host: \"dummy_device\",\n    _time: time(v: 0),\n    seen_earlier: true,\n    dummy: 1\n  }])\n\n// Combine real before data with fallback\nunion(tables: [before_data, before_dummy])",
           "refId": "before-interval"
         }
       ],
@@ -682,7 +682,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "metric_to_use = \"load1\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Apply metadata filters first (only if fields exist)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n\n  // 2. Then filter for the metric of interest\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"system\" and\n    r[\"_field\"] == metric_to_use\n  )\n\n  // 3. Aggregate, format, and limit\n  |> group(columns: [\"host\"])\n  |> mean()\n  |> group()\n  |> rename(columns: {_value: metric_to_use})\n  |> keep(columns: [\"host\", metric_to_use])\n  |> sort(columns: [metric_to_use], desc: true)\n  |> limit(n: ${outlier_count})\n",
+          "query": "metric_to_use = \"load1\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Apply metadata filters first (only if fields exist)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n\n  // 2. Then filter for the metric of interest\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"system\" and\n    r[\"_field\"] == metric_to_use\n  )\n\n  // 3. Aggregate, format, and limit\n  |> group(columns: [\"host\"])\n  |> mean()\n  |> group()\n  |> rename(columns: {_value: metric_to_use})\n  |> keep(columns: [\"host\", metric_to_use])\n  |> sort(columns: [metric_to_use], desc: true)\n  |> limit(n: ${outlier_count})\n",
           "refId": "load1"
         },
         {
@@ -691,7 +691,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "metric_to_use = \"load15\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters (only if fields exist)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n\n  // 2. Metric filtering\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"system\" and\n    r[\"_field\"] == metric_to_use\n  )\n\n  // 3. Aggregation and formatting\n  |> group(columns: [\"host\"])\n  |> mean()\n  |> group()\n  |> rename(columns: {_value: metric_to_use})\n  |> keep(columns: [\"host\", metric_to_use])\n\n  // 4. Sort and limit\n  |> sort(columns: [metric_to_use], desc: true)\n  |> limit(n: ${outlier_count})\n",
+          "query": "metric_to_use = \"load15\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters (only if fields exist)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n\n  // 2. Metric filtering\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"system\" and\n    r[\"_field\"] == metric_to_use\n  )\n\n  // 3. Aggregation and formatting\n  |> group(columns: [\"host\"])\n  |> mean()\n  |> group()\n  |> rename(columns: {_value: metric_to_use})\n  |> keep(columns: [\"host\", metric_to_use])\n\n  // 4. Sort and limit\n  |> sort(columns: [metric_to_use], desc: true)\n  |> limit(n: ${outlier_count})\n",
           "refId": "load15"
         },
         {
@@ -700,7 +700,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "metric_to_use = \"uptime\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters (only apply if fields exist)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n\n  // 2. Metric filter for uptime\n  |> filter(fn: (r) => r[\"_measurement\"] == \"system\" and r[\"_field\"] == metric_to_use)\n\n  // 3. Aggregate and format\n  |> group(columns: [\"host\"])\n  |> last() // Last reported uptime during the selected time span\n  |> group()\n  |> rename(columns: {_value: metric_to_use})\n  |> keep(columns: [\"host\", metric_to_use])\n  |> sort(columns: [metric_to_use], desc: false) // Ascending = lowest uptime\n  |> limit(n: ${outlier_count})\n",
+          "query": "metric_to_use = \"uptime\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters (only apply if fields exist)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n\n  // 2. Metric filter for uptime\n  |> filter(fn: (r) => r[\"_measurement\"] == \"system\" and r[\"_field\"] == metric_to_use)\n\n  // 3. Aggregate and format\n  |> group(columns: [\"host\"])\n  |> sort(columns: [\"_time\"], desc: true)\n  |> limit(n: 1) // Last reported uptime during the selected time span\n  |> group()\n  |> rename(columns: {_value: metric_to_use})\n  |> keep(columns: [\"host\", metric_to_use])\n  |> sort(columns: [metric_to_use], desc: false) // Ascending = lowest uptime\n  |> limit(n: ${outlier_count})\n",
           "refId": "uptime"
         },
         {
@@ -709,7 +709,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters (safe if tag missing)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n\n  // 2. Metric filter\n  |> filter(fn: (r) => r[\"_measurement\"] == \"mem\" and r[\"_field\"] == \"used_percent\")\n\n  // 3. Aggregation and formatting\n  |> group(columns: [\"host\"])\n  |> mean()\n  |> group()\n  |> rename(columns: {_value: \"memory used\"})\n  |> keep(columns: [\"host\", \"memory used\"])\n\n  // 4. Sort by memory used (descending = highest usage)\n  |> sort(columns: [\"memory used\"], desc: true)\n  |> limit(n: ${outlier_count})\n",
+          "query": "from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters (safe if tag missing)\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n\n  // 2. Metric filter\n  |> filter(fn: (r) => r[\"_measurement\"] == \"mem\" and r[\"_field\"] == \"used_percent\")\n\n  // 3. Aggregation and formatting\n  |> group(columns: [\"host\"])\n  |> mean()\n  |> group()\n  |> rename(columns: {_value: \"memory used\"})\n  |> keep(columns: [\"host\", \"memory used\"])\n\n  // 4. Sort by memory used (descending = highest usage)\n  |> sort(columns: [\"memory used\"], desc: true)\n  |> limit(n: ${outlier_count})\n",
           "refId": "memory"
         },
         {
@@ -718,7 +718,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "metric_name = \"flash used\"\ndisk_path = \"/usr/local\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n\n  // 2. Metric and path filter\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"disk\" and\n    r[\"_field\"] == \"used_percent\" and\n    r[\"path\"] == disk_path\n  )\n\n  // 3. Aggregate and format\n  |> group(columns: [\"host\"])\n  |> mean() // Mean over the selected time span\n  |> group()\n  |> rename(columns: {_value: metric_name})\n  |> keep(columns: [\"host\", metric_name])\n\n  // 4. Sort and limit\n  |> sort(columns: [metric_name], desc: true)\n  |> limit(n: ${outlier_count})\n",
+          "query": "metric_name = \"flash used\"\ndisk_path = \"/usr/local\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n\n  // 2. Metric and path filter\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"disk\" and\n    r[\"_field\"] == \"used_percent\" and\n    r[\"path\"] == disk_path\n  )\n\n  // 3. Aggregate and format\n  |> group(columns: [\"host\"])\n  |> mean() // Mean over the selected time span\n  |> group()\n  |> rename(columns: {_value: metric_name})\n  |> keep(columns: [\"host\", metric_name])\n\n  // 4. Sort and limit\n  |> sort(columns: [metric_name], desc: true)\n  |> limit(n: ${outlier_count})\n",
           "refId": "flash"
         },
         {
@@ -727,7 +727,7 @@
             "uid": "${datasource}"
           },
           "hide": false,
-          "query": "metric_name = \"sd card used\"\ndisk_path = \"/var/spool/storage/SD_DISK\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n\n  // 2. Metric and path filter\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"disk\" and\n    r[\"_field\"] == \"used_percent\" and\n    r[\"path\"] == disk_path\n  )\n\n  // 3. Aggregate and format\n  |> group(columns: [\"host\"])\n  |> mean() // Mean over the selected time span\n  |> group()\n  |> rename(columns: {_value: metric_name})\n  |> keep(columns: [\"host\", metric_name])\n\n  // 4. Sort and limit\n  |> sort(columns: [metric_name], desc: true)\n  |> limit(n: ${outlier_count})\n",
+          "query": "metric_name = \"sd card used\"\ndisk_path = \"/var/spool/storage/SD_DISK\"\n\nfrom(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n\n  // 1. Metadata filters\n  |> filter(fn: (r) => r[\"area\"] =~ /^${area:regex}$/)\n  |> filter(fn: (r) => r[\"geography\"] =~ /^${geography:regex}$/)\n  |> filter(fn: (r) => r[\"region\"] =~ /^${region:regex}$/)\n  |> filter(fn: (r) => r[\"site\"] =~ /^${site:regex}$/)\n  |> filter(fn: (r) => r[\"type\"] =~ /^${type:regex}$/)\n  |> filter(fn: (r) => r[\"${unique_identifier}\"] =~ /^${device:regex}$/)\n  |> filter(fn: (r) => r[\"product_full_name\"] =~ /^${model:regex}$/)\n  |> filter(fn: (r) => r[\"architecture\"] =~ /^${architecture:regex}$/)\n  |> filter(fn: (r) => r[\"soc\"] =~ /^${soc:regex}$/)\n\n  // 2. Metric and path filter\n  |> filter(fn: (r) =>\n    r[\"_measurement\"] == \"disk\" and\n    r[\"_field\"] == \"used_percent\" and\n    r[\"path\"] == disk_path\n  )\n\n  // 3. Aggregate and format\n  |> group(columns: [\"host\"])\n  |> mean() // Mean over the selected time span\n  |> group()\n  |> rename(columns: {_value: metric_name})\n  |> keep(columns: [\"host\", metric_name])\n\n  // 4. Sort and limit\n  |> sort(columns: [metric_name], desc: true)\n  |> limit(n: ${outlier_count})\n",
           "refId": "SD card"
         }
       ],
@@ -843,7 +843,7 @@
       "pluginVersion": "12.0.2",
       "targets": [
         {
-          "query": "cpu = from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) =>\n    r._measurement == \"cpu\" and\n    r._field == \"usage_idle\" and\n    r.cpu == \"cpu-total\" and\n    exists r.type and\n    r.type =~ /^${type:regex}$/ and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/\n  )\n  |> map(fn: (r) => ({ r with _value: 100.0 - r._value }))\n  |> group(columns: [\"type\"])\n  |> mean()\n  |> map(fn: (r) => ({ r with metric: \"CPU Usage\" }))\n\nram = from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) =>\n    r._measurement == \"mem\" and\n    r._field == \"used_percent\" and\n    exists r.type and\n    r.type =~ /^${type:regex}$/ and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/\n  )\n  |> group(columns: [\"type\"])\n  |> mean()\n  |> map(fn: (r) => ({ r with metric: \"RAM Usage\" }))\n\ndisk_usr_local = from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) =>\n    r._measurement == \"disk\" and\n    r._field == \"used_percent\" and\n    r.path == \"/usr/local\" and\n    exists r.type and\n    r.type =~ /^${type:regex}$/ and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/\n  )\n  |> group(columns: [\"type\"])\n  |> mean()\n  |> map(fn: (r) => ({ r with metric: \"Disk /usr/local\" }))\n\ndisk_sd = from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) =>\n    r._measurement == \"disk\" and\n    r._field == \"used_percent\" and\n    r.path == \"/var/volatile/spool/storage/SD_DISK\" and\n    exists r.type and\n    r.type =~ /^${type:regex}$/ and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/\n  )\n  |> group(columns: [\"type\"])\n  |> mean()\n  |> map(fn: (r) => ({ r with metric: \"Disk /SD_DISK\" }))\n\nunion(tables: [cpu, ram, disk_usr_local, disk_sd])\n  |> group()\n  |> pivot(rowKey: [\"type\"], columnKey: [\"metric\"], valueColumn: \"_value\")\n",
+          "query": "// Base query with shared filters\nbase_data = from(bucket: \"${bucket}\")\n  |> range(start: v.timeRangeStart, stop: v.timeRangeStop)\n  |> filter(fn: (r) =>\n    exists r.type and\n    r.type =~ /^${type:regex}$/ and\n    r[\"area\"] =~ /^${area:regex}$/ and\n    r[\"geography\"] =~ /^${geography:regex}$/ and\n    r[\"region\"] =~ /^${region:regex}$/ and\n    r[\"site\"] =~ /^${site:regex}$/ and\n    r[\"product_full_name\"] =~ /^${model:regex}$/ and\n    r[\"${unique_identifier}\"] =~ /^${device:regex}$/ and\n    r[\"architecture\"] =~ /^${architecture:regex}$/ and\n    r[\"soc\"] =~ /^${soc:regex}$/\n  )\n\n// CPU usage per type\ncpu = base_data\n  |> filter(fn: (r) =>\n    r._measurement == \"cpu\" and\n    r._field == \"usage_idle\" and\n    r.cpu == \"cpu-total\"\n  )\n  |> map(fn: (r) => ({ r with _value: 100.0 - r._value }))\n  |> group(columns: [\"type\"])\n  |> mean()\n  |> map(fn: (r) => ({ r with metric: \"CPU Usage\" }))\n\n// RAM usage per type\nram = base_data\n  |> filter(fn: (r) =>\n    r._measurement == \"mem\" and\n    r._field == \"used_percent\"\n  )\n  |> group(columns: [\"type\"])\n  |> mean()\n  |> map(fn: (r) => ({ r with metric: \"RAM Usage\" }))\n\n// Built-in storage usage per type\ndisk_usr_local = base_data\n  |> filter(fn: (r) =>\n    r._measurement == \"disk\" and\n    r._field == \"used_percent\" and\n    r.path == \"/usr/local\"\n  )\n  |> group(columns: [\"type\"])\n  |> mean()\n  |> map(fn: (r) => ({ r with metric: \"Disk /usr/local\" }))\n\n// SD card storage usage per type\ndisk_sd = base_data\n  |> filter(fn: (r) =>\n    r._measurement == \"disk\" and\n    r._field == \"used_percent\" and\n    r.path == \"/var/volatile/spool/storage/SD_DISK\"\n  )\n  |> group(columns: [\"type\"])\n  |> mean()\n  |> map(fn: (r) => ({ r with metric: \"Disk /SD_DISK\" }))\n\n// Combine all metrics into a single table\nunion(tables: [cpu, ram, disk_usr_local, disk_sd])\n  |> group()\n  |> pivot(rowKey: [\"type\"], columnKey: [\"metric\"], valueColumn: \"_value\")",
           "refId": "A"
         }
       ],
@@ -1137,6 +1137,56 @@
         "query": "1,2,3,4,5,10,50",
         "type": "custom"
       },
+      {
+        "allValue": ".*",
+        "allowCustomValue": false,
+        "current": {
+          "text": "All",
+          "value": ["$__all"]
+        },
+        "datasource": {
+          "type": "influxdb",
+          "uid": "${datasource}"
+        },
+        "definition": "import \"influxdata/influxdb/schema\"\n\nschema.tagValues(bucket: \"${bucket}\", tag: \"architecture\", start: 1970-01-01T00:00:00Z)",
+        "includeAll": true,
+        "label": "Architecture",
+        "multi": true,
+        "name": "architecture",
+        "options": [],
+        "query": {
+          "query": "import \"influxdata/influxdb/schema\"\n\nschema.tagValues(bucket: \"${bucket}\", tag: \"architecture\", start: 1970-01-01T00:00:00Z)"
+        },
+        "refresh": 1,
+        "regex": "",
+        "sort": 1,
+        "type": "query"
+      },
+      {
+        "allValue": ".*",
+        "allowCustomValue": false,
+        "current": {
+          "text": "All",
+          "value": ["$__all"]
+        },
+        "datasource": {
+          "type": "influxdb",
+          "uid": "${datasource}"
+        },
+        "definition": "import \"influxdata/influxdb/schema\"\n\nschema.tagValues(bucket: \"${bucket}\", tag: \"soc\", start: 1970-01-01T00:00:00Z)",
+        "includeAll": true,
+        "label": "System on Chip",
+        "multi": true,
+        "name": "soc",
+        "options": [],
+        "query": {
+          "query": "import \"influxdata/influxdb/schema\"\n\nschema.tagValues(bucket: \"${bucket}\", tag: \"soc\", start: 1970-01-01T00:00:00Z)"
+        },
+        "refresh": 1,
+        "regex": "",
+        "sort": 1,
+        "type": "query"
+      },
       {
         "current": {
           "text": "bekds38txl1j4c",
@@ -1159,5 +1209,5 @@
   "timezone": "browser",
   "title": "System Overview",
   "uid": "dsdsadfg3t3t3",
-  "version": 28
+  "version": 29
 }