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