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fix: available ops in headroom dashboard should be displayed as per confidence factor #1628

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merged 2 commits into from
Dec 16, 2022
Merged

fix: available ops in headroom dashboard should be displayed as per confidence factor #1628

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cc89ec7
fix: available ops in headroom dashboard should be displayed as per c…
rahulguptajss Dec 16, 2022
4c11f74
fix: address review comments
rahulguptajss Dec 16, 2022
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68 changes: 53 additions & 15 deletions grafana/dashboards/cmode/headroom.json
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Original file line number Diff line number Diff line change
Expand Up @@ -53,7 +53,7 @@
"gnetId": null,
"graphTooltip": 1,
"id": null,
"iteration": 1664471319262,
"iteration": 1671195638372,
"links": [
{
"asDropdown": true,
Expand Down Expand Up @@ -87,7 +87,7 @@
},
{
"datasource": "${DS_PROMETHEUS}",
"description": "A projection of the amount of available IOP/s each aggregate has with the current workloads before increased hockey stick style latencies are encountered.<br/><br/>This graph displays the difference between Aggregate Utilization and Peak Performance (Optimal Point) as Available Ops (aka Headroom). If the current Available utilization is very low or negative for an extended time, a performance remediation plan might be appropriate. A performance remediation plan might include setting QoS workload limits, moving volumes or LUNs to another storage controller, or expanding the storage cluster.",
"description": "A projection of the amount of available IOP/s each aggregate has with the current workloads before increased hockey stick style latencies are encountered.<br/><br/>This graph displays the difference between Aggregate Utilization and Peak Performance (Optimal Point) as Available Ops (aka Headroom). If the current Available utilization is very low or negative for an extended time, a performance remediation plan might be appropriate. A performance remediation plan might include setting QoS workload limits, moving volumes or LUNs to another storage controller, or expanding the storage cluster.<br/><br/>This graph displays aggregate with confidence factor greater than 1. The confidence factor is used to guage the accuracy of the optimal point for the given resource.Denoted by the following values:<br/>\n1 - Low - Seed value is used for optimal point. There's not enough data to predict optimal point.<br/>\n2 - Medium - Some data to extrapolate optimal point.<br/>\n3 - High - Substantial data which reaches or exceeds optimal point, thereby the \"optimal point\" is known. <br/>\n0 - Unknown - The resource is not available or is not in use, or there's an internal error such that the data cannot be retrieved. <br/>\nFor more details see \nhttps://kb.netapp.com/Advice_and_Troubleshooting/Data_Storage_Software/ONTAP_OS/Is_my_controller_overloaded%3F",
"fieldConfig": {
"defaults": {
"color": {
Expand Down Expand Up @@ -128,10 +128,6 @@
{
"color": "green",
"value": null
},
{
"color": "red",
"value": 80
}
]
},
Expand Down Expand Up @@ -163,7 +159,7 @@
"targets": [
{
"exemplar": true,
"expr": "headroom_aggr_optimal_point_ops{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\"} - headroom_aggr_current_ops{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\"}",
"expr": "headroom_aggr_optimal_point_ops{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\",aggr=~\"$OptimalPointAggr\"} - headroom_aggr_current_ops{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\",aggr=~\"$OptimalPointAggr\"}",
"interval": "",
"legendFormat": "{{node}} - {{aggr}}",
"refId": "A"
Expand All @@ -174,7 +170,7 @@
},
{
"datasource": "${DS_PROMETHEUS}",
"description": "A projection of the amount of available IOP/s each node has with the current workloads before increased hockey stick style latencies are encountered.<br/><br/>This graph displays the difference between CPU Utilization and Peak Performance (Optimal Point) as Available Ops (aka Headroom). If the current Available utilization is very low or negative for an extended time, a performance remediation plan might be appropriate. A performance remediation plan might include setting QoS workload limits, moving volumes or LUNs to another storage controller, or expanding the storage cluster.",
"description": "A projection of the amount of available IOP/s each node has with the current workloads before increased hockey stick style latencies are encountered.<br/><br/>This graph displays the difference between CPU Utilization and Peak Performance (Optimal Point) as Available Ops (aka Headroom). If the current Available utilization is very low or negative for an extended time, a performance remediation plan might be appropriate. A performance remediation plan might include setting QoS workload limits, moving volumes or LUNs to another storage controller, or expanding the storage cluster.<br/><br/>This graph displays node with confidence factor greater than 1. The confidence factor is used to guage the accuracy of the optimal point for the given resource.Denoted by the following values:<br/>\n1 - Low - Seed value is used for optimal point. There's not enough data to predict optimal point.<br/>\n2 - Medium - Some data to extrapolate optimal point.<br/>\n3 - High - Substantial data which reaches or exceeds optimal point, thereby the \"optimal point\" is known. <br/>\n0 - Unknown - The resource is not available or is not in use, or there's an internal error such that the data cannot be retrieved. <br/>\nFor more details see\nhttps://kb.netapp.com/Advice_and_Troubleshooting/Data_Storage_Software/ONTAP_OS/Is_my_controller_overloaded%3F",
"fieldConfig": {
"defaults": {
"color": {
Expand Down Expand Up @@ -215,10 +211,6 @@
{
"color": "green",
"value": null
},
{
"color": "red",
"value": 80
}
]
},
Expand Down Expand Up @@ -250,7 +242,7 @@
"targets": [
{
"exemplar": true,
"expr": "headroom_cpu_optimal_point_ops{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\"} - headroom_cpu_current_ops{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\"}",
"expr": "headroom_cpu_optimal_point_ops{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\",node=~\"$OptimalPointCPU\"} - headroom_cpu_current_ops{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\",node=~\"$OptimalPointCPU\"}",
"interval": "",
"legendFormat": "{{node}}",
"refId": "A"
Expand Down Expand Up @@ -2534,6 +2526,52 @@
"queryValue": "",
"skipUrlSync": false,
"type": "custom"
},
{
"allValue": null,
"current": {},
"datasource": "${DS_PROMETHEUS}",
"definition": "query_result(headroom_aggr_optimal_point_confidence_factor{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\"} > 1)",
"description": null,
"error": null,
"hide": 2,
"includeAll": true,
"label": null,
"multi": true,
"name": "OptimalPointAggr",
"options": [],
"query": {
"query": "query_result(headroom_aggr_optimal_point_confidence_factor{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\"} > 1)",
"refId": "StandardVariableQuery"
},
"refresh": 1,
"regex": ".*aggr=\\\"(.*?)\\\".*",
"skipUrlSync": false,
"sort": 0,
"type": "query"
},
{
"allValue": null,
"current": {},
"datasource": "${DS_PROMETHEUS}",
"definition": "query_result(headroom_cpu_optimal_point_confidence_factor{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\"} > 1)",
"description": null,
"error": null,
"hide": 2,
"includeAll": true,
"label": null,
"multi": true,
"name": "OptimalPointCPU",
"options": [],
"query": {
"query": "query_result(headroom_cpu_optimal_point_confidence_factor{datacenter=~\"$Datacenter\",cluster=~\"$Cluster\"} > 1)",
"refId": "StandardVariableQuery"
},
"refresh": 1,
"regex": ".*node=\\\"(.*?)\\\".*",
"skipUrlSync": false,
"sort": 0,
"type": "query"
}
]
},
Expand All @@ -2545,5 +2583,5 @@
"timezone": "",
"title": "ONTAP: Headroom",
"uid": "",
"version": 6
}
"version": 7
}