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276 lines
10 KiB
276 lines
10 KiB
local g = import 'github.com/grafana/jsonnet-libs/grafana-builder/grafana.libsonnet';
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{
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grafanaDashboards+:: {
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'node-cluster-rsrc-use.json':
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local legendLink = '%s/dashboard/file/node-rsrc-use.json' % $._config.grafana_prefix;
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g.dashboard('USE Method / Cluster')
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.addRow(
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g.row('CPU')
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.addPanel(
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g.panel('CPU Utilisation') +
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g.queryPanel(|||
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(
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instance:node_cpu_utilisation:rate1m{%(nodeExporterSelector)s}
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*
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instance:node_num_cpu:sum{%(nodeExporterSelector)s}
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)
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/ scalar(sum(instance:node_num_cpu:sum{%(nodeExporterSelector)s}))
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||| % $._config, '{{instance}}', legendLink) +
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g.stack +
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{ yaxes: g.yaxes({ format: 'percentunit', max: 1 }) },
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)
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.addPanel(
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// TODO: Is this a useful panel? At least there should be some explanation how load
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// average relates to the "CPU saturation" in the title.
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g.panel('CPU Saturation (load1 per CPU)') +
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g.queryPanel(|||
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instance:node_load1_per_cpu:ratio{%(nodeExporterSelector)s}
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/ scalar(count(instance:node_load1_per_cpu:ratio{%(nodeExporterSelector)s}))
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||| % $._config, '{{instance}}', legendLink) +
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g.stack +
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// TODO: Does `max: 1` make sense? The stack can go over 1 in high-load scenarios.
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{ yaxes: g.yaxes({ format: 'percentunit', max: 1 }) },
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)
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)
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.addRow(
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g.row('Memory')
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.addPanel(
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g.panel('Memory Utilisation') +
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g.queryPanel(|||
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instance:node_memory_utilisation:ratio{%(nodeExporterSelector)s}
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/ scalar(count(instance:node_memory_utilisation:ratio{%(nodeExporterSelector)s}))
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||| % $._config, '{{instance}}', legendLink) +
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g.stack +
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{ yaxes: g.yaxes({ format: 'percentunit', max: 1 }) },
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)
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.addPanel(
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g.panel('Memory Saturation (Major Page Faults)') +
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g.queryPanel('instance:node_vmstat_pgmajfault:rate1m{%(nodeExporterSelector)s}' % $._config, '{{instance}}', legendLink) +
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g.stack +
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{ yaxes: g.yaxes('rps') },
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)
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)
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.addRow(
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g.row('Network')
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.addPanel(
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g.panel('Net Utilisation (Bytes Receive/Transmit)') +
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g.queryPanel(
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[
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'instance:node_network_receive_bytes_excluding_lo:rate1m{%(nodeExporterSelector)s}' % $._config,
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'instance:node_network_transmit_bytes_excluding_lo:rate1m{%(nodeExporterSelector)s}' % $._config,
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],
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['{{instance}} Receive', '{{instance}} Transmit'],
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legendLink,
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) +
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g.stack +
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{
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yaxes: g.yaxes({ format: 'Bps', min: null }),
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seriesOverrides: [
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{
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alias: '/ Receive/',
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stack: 'A',
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},
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{
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alias: '/ Transmit/',
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stack: 'B',
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transform: 'negative-Y',
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},
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],
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},
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)
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.addPanel(
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g.panel('Net Saturation (Drops Receive/Transmit)') +
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g.queryPanel(
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[
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'instance:node_network_receive_drop_excluding_lo:rate1m{%(nodeExporterSelector)s}' % $._config,
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'instance:node_network_transmit_drop_excluding_lo:rate1m{%(nodeExporterSelector)s}' % $._config,
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],
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['{{instance}} Receive', '{{instance}} Transmit'],
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legendLink,
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) +
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g.stack +
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{
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yaxes: g.yaxes({ format: 'rps', min: null }),
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seriesOverrides: [
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{
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alias: '/ Receive/',
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stack: 'A',
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},
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{
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alias: '/ Transmit/',
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stack: 'B',
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transform: 'negative-Y',
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},
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],
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},
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)
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)
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.addRow(
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g.row('Disk IO')
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.addPanel(
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g.panel('Disk IO Utilisation') +
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// Full utilisation would be all disks on each node spending an average of
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// 1 second per second doing I/O, normalize by metric cardinality for stacked charts.
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// TODO: Does the partition by device make sense? Using the most utilized device per
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// instance might make more sense.
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g.queryPanel(|||
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instance_device:node_disk_io_time_seconds:rate1m{%(nodeExporterSelector)s}
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/ scalar(count(instance_device:node_disk_io_time_seconds:rate1m{%(nodeExporterSelector)s}))
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||| % $._config, '{{instance}} {{device}}', legendLink) +
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g.stack +
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{ yaxes: g.yaxes({ format: 'percentunit', max: 1 }) },
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)
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.addPanel(
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g.panel('Disk IO Saturation') +
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g.queryPanel(|||
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instance_device:node_disk_io_time_weighted_seconds:rate1m{%(nodeExporterSelector)s}
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/ scalar(count(instance_device:node_disk_io_time_weighted_seconds:rate1m{%(nodeExporterSelector)s}))
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||| % $._config, '{{instance}} {{device}}', legendLink) +
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g.stack +
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{ yaxes: g.yaxes({ format: 'percentunit', max: 1 }) },
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)
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)
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.addRow(
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g.row('Disk Space')
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.addPanel(
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g.panel('Disk Space Utilisation') +
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g.queryPanel(|||
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sum without (device) (
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max without (fstype, mountpoint) (
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node_filesystem_size_bytes{%(nodeExporterSelector)s, %(fsSelector)s} - node_filesystem_avail_bytes{%(nodeExporterSelector)s, %(fsSelector)s}
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)
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)
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/ scalar(sum(max without (fstype, mountpoint) (node_filesystem_size_bytes{%(nodeExporterSelector)s, %(fsSelector)s})))
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||| % $._config, '{{instance}}', legendLink) +
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g.stack +
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{ yaxes: g.yaxes({ format: 'percentunit', max: 1 }) },
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),
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),
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'node-rsrc-use.json':
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g.dashboard('USE Method / Node')
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.addTemplate('instance', 'up{%(nodeExporterSelector)s}' % $._config, 'instance')
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.addRow(
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g.row('CPU')
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.addPanel(
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g.panel('CPU Utilisation') +
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g.queryPanel('instance:node_cpu_utilisation:rate1m{%(nodeExporterSelector)s, instance="$instance"}' % $._config, 'Utilisation') +
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{
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yaxes: g.yaxes('percentunit'),
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legend+: { show: false },
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},
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)
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.addPanel(
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// TODO: Is this a useful panel? At least there should be some explanation how load
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// average relates to the "CPU saturation" in the title.
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g.panel('CPU Saturation (Load1 per CPU)') +
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g.queryPanel('instance:node_load1_per_cpu:ratio{%(nodeExporterSelector)s, instance="$instance"}' % $._config, 'Saturation') +
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{
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yaxes: g.yaxes('percentunit'),
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legend+: { show: false },
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},
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)
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)
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.addRow(
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g.row('Memory')
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.addPanel(
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g.panel('Memory Utilisation') +
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g.queryPanel('instance:node_memory_utilisation:ratio{%(nodeExporterSelector)s, %(nodeExporterSelector)s, instance="$instance"}' % $._config, 'Memory') +
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{ yaxes: g.yaxes('percentunit') },
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)
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.addPanel(
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g.panel('Memory Saturation (Major Page Faults)') +
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g.queryPanel('instance:node_vmstat_pgmajfault:rate1m{%(nodeExporterSelector)s, instance="$instance"}' % $._config, 'Major page faults') +
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{
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yaxes: g.yaxes('short'),
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legend+: { show: false },
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},
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)
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)
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.addRow(
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g.row('Net')
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.addPanel(
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g.panel('Net Utilisation (Bytes Receive/Transmit)') +
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g.queryPanel(
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[
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'instance:node_network_receive_bytes_excluding_lo:rate1m{%(nodeExporterSelector)s, instance="$instance"}' % $._config,
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'instance:node_network_transmit_bytes_excluding_lo:rate1m{%(nodeExporterSelector)s, instance="$instance"}' % $._config,
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],
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['Receive', 'Transmit'],
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) +
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{
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yaxes: g.yaxes({ format: 'Bps', min: null }),
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seriesOverrides: [
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{
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alias: '/Receive/',
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stack: 'A',
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},
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{
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alias: '/Transmit/',
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stack: 'B',
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transform: 'negative-Y',
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},
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],
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},
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)
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.addPanel(
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g.panel('Net Saturation (Drops Receive/Transmit)') +
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g.queryPanel(
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[
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'instance:node_network_receive_drop_excluding_lo:rate1m{%(nodeExporterSelector)s, instance="$instance"}' % $._config,
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'instance:node_network_transmit_drop_excluding_lo:rate1m{%(nodeExporterSelector)s, instance="$instance"}' % $._config,
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],
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['Receive drops', 'Transmit drops'],
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) +
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{
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yaxes: g.yaxes({ format: 'rps', min: null }),
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seriesOverrides: [
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{
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alias: '/Receive/',
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stack: 'A',
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},
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{
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alias: '/Transmit/',
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stack: 'B',
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transform: 'negative-Y',
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},
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],
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},
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)
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)
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.addRow(
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g.row('Disk IO')
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.addPanel(
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g.panel('Disk IO Utilisation') +
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g.queryPanel('instance_device:node_disk_io_time_seconds:rate1m{%(nodeExporterSelector)s, instance="$instance"}' % $._config, '{{device}}') +
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{ yaxes: g.yaxes('percentunit') },
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)
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.addPanel(
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g.panel('Disk IO Saturation') +
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g.queryPanel('instance_device:node_disk_io_time_weighted_seconds:rate1m{%(nodeExporterSelector)s, instance="$instance"}' % $._config, '{{device}}') +
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{ yaxes: g.yaxes('percentunit') },
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)
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)
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.addRow(
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g.row('Disk Space')
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.addPanel(
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g.panel('Disk Space Utilisation') +
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g.queryPanel(|||
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1 -
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(
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max without (mountpoint, fstype) (node_filesystem_avail_bytes{%(nodeExporterSelector)s, %(fsSelector)s, instance="$instance"})
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/
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max without (mountpoint, fstype) (node_filesystem_size_bytes{%(nodeExporterSelector)s, %(fsSelector)s, instance="$instance"})
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)
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||| % $._config, '{{device}}') +
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{
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yaxes: g.yaxes('percentunit'),
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legend+: { show: false },
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},
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),
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),
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},
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}
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