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apiVersion : v1
kind : ConfigMap
metadata :
name : victoria-metrics-grafana-dashboard
namespace : monitoring
labels :
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data :
victoria-metrics.json : |-
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2023-05-04 20:17:01 +00:00
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2023-05-04 20:17:01 +00:00
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2023-05-04 20:17:01 +00:00
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2023-05-04 20:17:01 +00:00
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2023-10-21 01:03:39 +00:00
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2023-10-21 01:03:39 +00:00
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2023-05-04 20:17:01 +00:00
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2023-05-04 20:17:01 +00:00
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2023-05-04 20:17:01 +00:00
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2023-05-04 20:17:01 +00:00
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"type": "prometheus" ,
"uid": "$ds"
},
"editorMode": "code" ,
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"expr": "sum(vm_tcplistener_conns{job=~\"$job\", instance=~\"$instance\"}) by(instance)" ,
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"format": "time_series" ,
"hide": false ,
"intervalFactor": 1 ,
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"legendFormat": "{{instance}}" ,
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"range": true ,
"refId": "A"
}
] ,
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"title": "TCP connections ($instance)" ,
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"type": "timeseries"
}
] ,
"targets": [
{
"datasource": {
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"title": "Resource usage" ,
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{
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"description": "Shows the rate and total number of new series created over last 24h.\n\nHigh churn rate tightly connected with database performance and may result in unexpected OOM's or slow queries. It is recommended to always keep an eye on this metric to avoid unexpected cardinality \"explosions\".\n\nThe higher churn rate is, the more resources required to handle it. Consider to keep the churn rate as low as possible.\n\nGood references to read:\n* https://www.robustperception.io/cardinality-is-key\n* https://www.robustperception.io/using-tsdb-analyze-to-investigate-churn-and-cardinality" ,
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},
"id": 66 ,
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},
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"expr": "sum(rate(vm_new_timeseries_created_total{job=~\"$job\", instance=~\"$instance\"}[$__rate_interval]))" ,
"interval": "" ,
"legendFormat": "churn rate" ,
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{
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"expr": "sum(increase(vm_new_timeseries_created_total{job=~\"$job\", instance=~\"$instance\"}[24h]))" ,
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},
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"description": "The percentage of slow inserts comparing to total insertion rate during the last 5 minutes. \n\nThe less value is better. If percentage remains high (>10%) during extended periods of time, then it is likely more RAM is needed for optimal handling of the current number of active time series. \n\nIn general, VictoriaMetrics requires ~1KB or RAM per active time series, so it should be easy calculating the required amounts of RAM for the current workload according to capacity planning docs. But the resulting number may be far from the real number because the required amounts of memory depends on many other factors such as the number of labels per time series and the length of label values. See also https://github.com/VictoriaMetrics/VictoriaMetrics/issues/3976#issuecomment-1476883183" ,
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},
"id": 68 ,
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"expr": "max(\n rate(vm_slow_row_inserts_total{job=~\"$job\"}[$__rate_interval]) \n / rate(vm_rows_added_to_storage_total{job=~\"$job\"}[$__rate_interval])\n)" ,
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"description": "Merge assist happens when storage can't keep up with merging parts. This is usually a sign of overload for storage." ,
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},
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"expr": "sum(increase(vm_assisted_merges_total{job=~\"$job\", instance=~\"$instance\"}[$__rate_interval])) by(type) > 0" ,
"format": "time_series" ,
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{
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"description": "Slow queries rate according to `search.logSlowQueryDuration` flag, which is `5s` by default." ,
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},
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},
"description": "Shows the percentage of used cache size from the allowed size by type. \nValues close to 100% show the maximum potential utilization.\nValues close to 0% show that cache is underutilized." ,
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"y": 24
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},
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2023-10-21 01:03:39 +00:00
"y": 24
2023-05-04 20:17:01 +00:00
},
"id": 118 ,
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] ,
"title": "Cache miss ratio ($instance)" ,
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},
{
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2023-10-21 01:03:39 +00:00
"y": 33
2023-05-04 20:17:01 +00:00
},
"id": 120 ,
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},
2023-10-21 01:03:39 +00:00
"pluginVersion": "9.1.0" ,
2023-05-04 20:17:01 +00:00
"targets": [
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"format": "table" ,
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"description": "VictoriaMetrics limits the number of labels per each metric with `-maxLabelsPerTimeseries` command-line flag.\n\nThis prevents from ingesting metrics with too many labels. The value of `maxLabelsPerTimeseries` must be adjusted for your workload.\n\nWhen limit is exceeded (graph is > 0) - extra labels are dropped, which could result in unexpected identical time series." ,
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2023-10-21 01:03:39 +00:00
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2023-05-04 20:17:01 +00:00
},
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"hide": false ,
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"x": 0 ,
"y": 33
},
"id": 10 ,
"links": [ ] ,
"options": {
"legend": {
"calcs": [
"mean" ,
"lastNotNull" ,
"max"
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"showLegend": true ,
"sortBy": "Last *" ,
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},
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}
},
"pluginVersion": "9.1.0" ,
"targets": [
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"editorMode": "code" ,
"expr": "sum(rate(vm_rows_inserted_total{job=~\"$job\", instance=~\"$instance\"}[$__rate_interval])) by (type) > 0" ,
"format": "time_series" ,
"hide": false ,
"intervalFactor": 1 ,
"legendFormat": "{{type}}" ,
"range": true ,
"refId": "A"
}
] ,
"title": "Datapoints ingestion rate ($instance)" ,
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},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"description": "Shows the time needed to reach the 100% of disk capacity based on the following params:\n* free disk space;\n* row ingestion rate;\n* dedup rate;\n* compression.\n\nUse this panel for capacity planning in order to estimate the time remaining for running out of the disk space.\n\n" ,
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"custom": {
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"axisLabel": "" ,
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"fillOpacity": 0 ,
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"pointSize": 5 ,
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"showPoints": "never" ,
"spanNulls": false ,
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"mode": "none"
},
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"mode": "off"
}
},
"links": [ ] ,
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"min": 0 ,
"thresholds": {
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"steps": [
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"color": "green"
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{
"color": "red" ,
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}
]
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"unit": "s"
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},
"gridPos": {
"h": 8 ,
"w": 12 ,
"x": 12 ,
"y": 33
},
"id": 73 ,
"links": [ ] ,
"options": {
"legend": {
"calcs": [
"mean" ,
"lastNotNull" ,
"min"
] ,
"displayMode": "table" ,
"placement": "bottom" ,
"showLegend": true ,
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"sortDesc": true
},
"tooltip": {
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},
"pluginVersion": "9.1.0" ,
"targets": [
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"editorMode": "code" ,
"expr": "vm_free_disk_space_bytes{job=~\"$job\", instance=~\"$instance\"} \n/ ignoring(path) (\n (\n rate(vm_rows_added_to_storage_total{job=~\"$job\", instance=~\"$instance\"}[1d]) \n - ignoring(type) rate(vm_deduplicated_samples_total{job=~\"$job\", instance=~\"$instance\", type=\"merge\"}[1d])\n ) * scalar(\n sum(vm_data_size_bytes{job=~\"$job\", instance=~\"$instance\", type!~\"indexdb.*\"}) \n / sum(vm_rows{job=~\"$job\", instance=~\"$instance\", type!~\"indexdb.*\"})\n )\n )" ,
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"hide": false ,
"interval": "" ,
"intervalFactor": 1 ,
"legendFormat": "{{instance}}" ,
"range": true ,
"refId": "A"
}
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"title": "Storage full ETA ($instance)" ,
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"description": "Shows amount of on-disk space occupied by data points and the remaining disk space at `-storageDataPath`" ,
"fieldConfig": {
"defaults": {
"color": {
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"custom": {
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"axisColorMode": "text" ,
"axisLabel": "" ,
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"barAlignment": 0 ,
"drawStyle": "line" ,
"fillOpacity": 0 ,
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"hideFrom": {
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"tooltip": false ,
"viz": false
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"lineInterpolation": "linear" ,
"lineWidth": 1 ,
"pointSize": 5 ,
"scaleDistribution": {
"type": "linear"
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"showPoints": "never" ,
"spanNulls": false ,
"stacking": {
"group": "A" ,
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"links": [ ] ,
"mappings": [ ] ,
"min": 0 ,
"thresholds": {
"mode": "absolute" ,
"steps": [
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"color": "green"
},
{
"color": "red" ,
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}
]
},
"unit": "bytes"
},
"overrides": [ ]
},
"gridPos": {
"h": 8 ,
"w": 12 ,
"x": 0 ,
"y": 41
},
"id": 53 ,
"links": [ ] ,
"options": {
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"calcs": [
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"lastNotNull" ,
"max"
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"displayMode": "table" ,
"placement": "bottom" ,
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"sortBy": "Last *" ,
"sortDesc": true
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"tooltip": {
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},
"pluginVersion": "9.1.0" ,
"targets": [
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"uid": "$ds"
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"editorMode": "code" ,
"expr": "sum(vm_data_size_bytes{job=~\"$job\", instance=~\"$instance\", type!~\"indexdb.*\"})" ,
"format": "time_series" ,
"interval": "" ,
"intervalFactor": 1 ,
"legendFormat": "Used (datapoints)" ,
"range": true ,
"refId": "A"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"expr": "vm_free_disk_space_bytes{job=~\"$job\", instance=~\"$instance\"}" ,
"format": "time_series" ,
"interval": "" ,
"intervalFactor": 1 ,
"legendFormat": "Free" ,
"refId": "B"
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{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"editorMode": "code" ,
"expr": "sum(vm_data_size_bytes{job=~\"$job\", instance=~\"$instance\", type=~\"indexdb.*\"})" ,
"format": "time_series" ,
"hide": false ,
"interval": "" ,
"intervalFactor": 1 ,
"legendFormat": "Used (index)" ,
"range": true ,
"refId": "C"
}
] ,
"title": "Disk space usage - datapoints ($instance)" ,
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"description": "How many datapoints are in RAM queue waiting to be written into storage. The number of pending data points should be in the range from 0 to `2*<ingestion_rate>`, since VictoriaMetrics pushes pending data to persistent storage every second." ,
"fieldConfig": {
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"color": {
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},
"custom": {
"axisCenteredZero": false ,
"axisColorMode": "text" ,
"axisLabel": "" ,
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"barAlignment": 0 ,
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"fillOpacity": 10 ,
"gradientMode": "none" ,
"hideFrom": {
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},
"lineInterpolation": "linear" ,
"lineWidth": 1 ,
"pointSize": 5 ,
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"spanNulls": false ,
"stacking": {
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"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
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"links": [ ] ,
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"min": 0 ,
"thresholds": {
"mode": "absolute" ,
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"color": "green"
},
{
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}
]
},
"unit": "short"
},
"overrides": [
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"options": "pending index entries"
},
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{
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"w": 12 ,
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"y": 41
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"displayMode": "table" ,
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"pluginVersion": "9.1.0" ,
"targets": [
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"expr": "vm_pending_rows{job=~\"$job\", instance=~\"$instance\", type=\"storage\"}" ,
"format": "time_series" ,
"hide": false ,
"intervalFactor": 1 ,
"legendFormat": "pending datapoints" ,
"refId": "A"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"expr": "vm_pending_rows{job=~\"$job\", instance=~\"$instance\", type=\"indexdb\"}" ,
"format": "time_series" ,
"hide": false ,
"intervalFactor": 1 ,
"legendFormat": "pending index entries" ,
"refId": "B"
}
] ,
"title": "Pending datapoints ($instance)" ,
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"description": "Shows how many datapoints are in the storage and what is average disk usage per datapoint." ,
"fieldConfig": {
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"mode": "palette-classic"
},
"custom": {
"axisCenteredZero": false ,
"axisColorMode": "text" ,
"axisLabel": "" ,
"axisPlacement": "auto" ,
"barAlignment": 0 ,
"drawStyle": "line" ,
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"lineInterpolation": "linear" ,
"lineWidth": 1 ,
"pointSize": 5 ,
"scaleDistribution": {
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"showPoints": "never" ,
"spanNulls": false ,
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"mode": "none"
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"thresholdsStyle": {
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"mappings": [ ] ,
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"thresholds": {
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},
{
"color": "red" ,
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}
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},
"unit": "short"
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"overrides": [
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"id": "byName" ,
"options": "bytes-per-datapoint"
},
"properties": [
{
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},
{
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"value": 2
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}
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},
"gridPos": {
"h": 8 ,
"w": 12 ,
"x": 0 ,
"y": 49
},
"id": 30 ,
"links": [ ] ,
"options": {
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"displayMode": "table" ,
"placement": "bottom" ,
"showLegend": true ,
"sortBy": "Last *" ,
"sortDesc": true
},
"tooltip": {
"mode": "multi" ,
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},
"pluginVersion": "9.1.0" ,
"targets": [
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"expr": "sum(vm_rows{job=~\"$job\", instance=~\"$instance\", type!~\"indexdb.*\"})" ,
"format": "time_series" ,
"interval": "" ,
"intervalFactor": 1 ,
"legendFormat": "total datapoints" ,
"refId": "A"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"editorMode": "code" ,
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"expr": "sum(vm_data_size_bytes{job=~\"$job\", instance=~\"$instance\"}) \n/ sum(vm_rows{job=~\"$job\", instance=~\"$instance\", type!~\"indexdb.*\"})" ,
2023-05-04 20:17:01 +00:00
"format": "time_series" ,
"interval": "" ,
"intervalFactor": 1 ,
"legendFormat": "bytes-per-datapoint" ,
"range": true ,
"refId": "B"
}
] ,
"title": "Datapoints ($instance)" ,
"type": "timeseries"
},
{
"datasource": {
"uid": "$ds"
},
"description": "Data parts of LSM tree.\nHigh number of parts could be an evidence of slow merge performance - check the resource utilization.\n* `indexdb` - inverted index\n* `storage/small` - recently added parts of data ingested into storage(hot data)\n* `storage/big` - small parts gradually merged into big parts (cold data)" ,
"fieldConfig": {
"defaults": {
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},
"custom": {
"axisCenteredZero": false ,
"axisColorMode": "text" ,
"axisLabel": "" ,
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"barAlignment": 0 ,
"drawStyle": "line" ,
"fillOpacity": 0 ,
"gradientMode": "none" ,
"hideFrom": {
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"tooltip": false ,
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"pointSize": 5 ,
"scaleDistribution": {
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},
"showPoints": "never" ,
"spanNulls": false ,
"stacking": {
"group": "A" ,
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"links": [ ] ,
"mappings": [ ] ,
"min": 0 ,
"thresholds": {
"mode": "absolute" ,
"steps": [
{
"color": "green"
},
{
"color": "red" ,
"value": 80
}
]
},
"unit": "short"
},
"overrides": [ ]
},
"gridPos": {
"h": 8 ,
"w": 12 ,
"x": 12 ,
"y": 49
},
"id": 36 ,
"links": [ ] ,
"options": {
"legend": {
"calcs": [
"mean" ,
"lastNotNull" ,
"max"
] ,
"displayMode": "table" ,
"placement": "bottom" ,
"showLegend": true ,
"sortBy": "Last *" ,
"sortDesc": true
},
"tooltip": {
"mode": "multi" ,
"sort": "desc"
}
},
"pluginVersion": "9.1.0" ,
"targets": [
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"expr": "sum(vm_parts{job=~\"$job\", instance=~\"$instance\"}) by (type)" ,
"format": "time_series" ,
"intervalFactor": 1 ,
"legendFormat": "{{type}}" ,
"refId": "A"
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] ,
"title": "LSM parts ($instance)" ,
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"description": "Shows how many rows were ignored on insertion due to corrupted or out of retention timestamps." ,
"fieldConfig": {
"defaults": {
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"fillOpacity": 10 ,
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"showPoints": "never" ,
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"stacking": {
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"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
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},
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"steps": [
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},
"unit": "short"
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},
"gridPos": {
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"w": 12 ,
"x": 0 ,
"y": 57
},
"id": 58 ,
"links": [ ] ,
"options": {
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"calcs": [
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"lastNotNull" ,
"max"
] ,
"displayMode": "table" ,
"placement": "bottom" ,
"showLegend": true
},
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},
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"targets": [
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"editorMode": "code" ,
"exemplar": false ,
"expr": "sum(increase(vm_rows_ignored_total{job=~\"$job\", instance=~\"$instance\"}[1h])) by (reason)" ,
"format": "time_series" ,
"hide": false ,
"interval": "" ,
"intervalFactor": 1 ,
"legendFormat": "{{reason}}" ,
"range": true ,
"refId": "A"
}
] ,
"title": "Rows ignored for last 1h ($instance)" ,
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"description": "The number of on-going merges in storage nodes. It is expected to have high numbers for `storage/small` metric." ,
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"custom": {
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"x": 12 ,
"y": 57
},
"id": 62 ,
"options": {
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"displayMode": "table" ,
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"showLegend": true
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},
"pluginVersion": "9.1.0" ,
"targets": [
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"expr": "sum(vm_active_merges{job=~\"$job\", instance=~\"$instance\"}) by(type)" ,
"legendFormat": "{{type}}" ,
"refId": "A"
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] ,
"title": "Active merges ($instance)" ,
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"description": "Shows how many ongoing insertions (not API /write calls) on disk are taking place, where:\n* `max` - equal to number of CPUs;\n* `current` - current number of goroutines busy with inserting rows into underlying storage.\n\nEvery successful API /write call results into flush on disk. However, these two actions are separated and controlled via different concurrency limiters. The `max` on this panel can't be changed and always equal to number of CPUs. \n\nWhen `current` hits `max` constantly, it means storage is overloaded and requires more CPU.\n\n" ,
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{
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},
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"id": "color" ,
"value": {
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"mode": "fixed"
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}
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}
]
},
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"x": 0 ,
"y": 65
},
"id": 59 ,
"links": [ ] ,
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},
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},
"editorMode": "code" ,
2023-10-21 01:03:39 +00:00
"expr": "max_over_time(vm_concurrent_insert_capacity{job=~\"$job\", instance=~\"$instance\"}[$__rate_interval])" ,
2023-05-04 20:17:01 +00:00
"format": "time_series" ,
"interval": "" ,
"intervalFactor": 1 ,
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"refId": "A"
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{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
2023-10-21 01:03:39 +00:00
"expr": "sum(vm_concurrent_insert_current{job=~\"$job\", instance=~\"$instance\"})" ,
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"format": "time_series" ,
"intervalFactor": 1 ,
"legendFormat": "current" ,
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}
] ,
"title": "Concurrent flushes on disk ($instance)" ,
"type": "timeseries"
},
{
"datasource": {
"type": "prometheus" ,
"uid": "$ds"
},
"description": "The number of rows merged per second by storage nodes." ,
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"custom": {
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"axisColorMode": "text" ,
"axisLabel": "" ,
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"drawStyle": "line" ,
"fillOpacity": 0 ,
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"tooltip": false ,
"viz": false
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