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@irfansharif
Last active September 2, 2023 05:01
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{
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{
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"uid": "localprom"
},
"enable": true,
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"name": "Annotations & Alerts",
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},
{
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"uid": "grafana"
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"uid": "localprom"
},
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"refId": "C"
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{
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},
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{
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},
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"hide": true,
"legendFormat": "__auto",
"range": true,
"refId": "E"
}
],
"title": "SQL statements",
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},
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{
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],
"title": "Export, AddSST requests sent",
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{
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"unit": "binBps"
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{
"__systemRef": "hideSeriesFrom",
"matcher": {
"id": "byNames",
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"names": [
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"-sum(rate(sql_bytesout[1m0s]))"
],
"prefix": "All except:",
"readOnly": true
}
},
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}
}
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},
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"expr": "sum(rate(sql_bytesin[$__rate_interval]))",
"hide": false,
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{
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"expr": "-sum(rate(sql_bytesout[$__rate_interval]))",
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"expr": "-rate(sql_bytesin[$__rate_interval])",
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"legendFormat": "__auto",
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],
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},
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},
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"expr": "sum(jobs_backup_currently_running)",
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"refId": "D"
},
{
"datasource": {
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"uid": "localprom"
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},
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"uid": "localprom"
},
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"expr": "sum(jobs_row_level_ttl_currently_running)",
"hide": false,
"legendFormat": "__auto",
"range": true,
"refId": "F"
},
{
"datasource": {
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"uid": "localprom"
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"range": true,
"refId": "E"
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{
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"uid": "localprom"
},
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"hide": true,
"legendFormat": "__auto",
"range": true,
"refId": "B"
},
{
"datasource": {
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"type": "__expr__",
"uid": "__expr__"
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"refId": "C",
"type": "math"
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{
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"uid": "localprom"
},
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"expr": "sum(rate(jobs_row_level_ttl_resume_completed[$__rate_interval]))",
"hide": true,
"legendFormat": "__auto",
"range": true,
"refId": "G"
}
],
"title": "Schema changes, TTL, or backups running (+ve), completed (-ve)",
"type": "timeseries"
},
{
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},
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"uid": "localprom"
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"editorMode": "code",
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"hide": true,
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"refId": "B"
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{
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"uid": "__expr__"
},
"expression": "ceil($B)",
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"refId": "Schema Change",
"type": "math"
},
{
"datasource": {
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"uid": "localprom"
},
"editorMode": "code",
"expr": "sum(rate(jobs_backup_resume_failed[$__rate_interval])) +\nsum(rate(jobs_backup_resume_retry_error[$__rate_interval])) +\nsum(rate(jobs_backup_fail_or_cancel_completed[$__rate_interval])) +\nsum(rate(jobs_backup_fail_or_cancel_failed[$__rate_interval])) +\nsum(rate(jobs_backup_fail_or_cancel_retry_error[$__rate_interval]))",
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"refId": "A"
},
{
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},
"expression": "ceil($A)",
"hide": false,
"refId": "Backups",
"type": "math"
},
{
"datasource": {
"name": "Expression",
"type": "__expr__",
"uid": "__expr__"
},
"expression": "ceil($D)",
"hide": false,
"refId": "Row Level TTL",
"type": "math"
},
{
"datasource": {
"type": "prometheus",
"uid": "localprom"
},
"editorMode": "code",
"expr": "sum(rate(jobs_row_level_ttl_resume_failed[$__rate_interval])) +\nsum(rate(jobs_row_level_ttl_resume_retry_error[$__rate_interval])) +\nsum(rate(jobs_row_level_ttl_fail_or_cancel_completed[$__rate_interval])) +\nsum(rate(jobs_row_level_ttl_fail_or_cancel_failed[$__rate_interval])) +\nsum(rate(jobs_row_level_ttl_fail_or_cancel_retry_error[$__rate_interval]))",
"hide": true,
"legendFormat": "__auto",
"range": true,
"refId": "D"
}
],
"title": "Schema change, TTL, backup failures/cancelations",
"type": "timeseries"
},
{
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{
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]
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"refId": "B"
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"uid": "localprom"
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"interval": "",
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"uid": "localprom"
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"editorMode": "code",
"expr": "histogram_quantile(0.75, sum(rate(admission_wait_durations_kv_stores_ttl_low_pri_bucket{node=~\"$node\"}[$__rate_interval])) by (le))",
"hide": false,
"interval": "",
"legendFormat": "TTLLow-p75",
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"interval": "",
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"datasource": {
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"refId": "A"
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"interval": "",
"legendFormat": "{{node}}-taken-wo-perm",
"range": true,
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"range": true,
"refId": "C"
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],
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"x": 0,
"y": 5
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},
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