mirror of
https://github.com/prometheus-community/windows_exporter.git
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dashboard: factor Grafonnet builders into tab modules (#2595)
Signed-off-by: Jan-Otto Kröpke <mail@jkroepke.de>
This commit is contained in:
Jan-Otto Kröpke
@@ -0,0 +1,279 @@
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local b = import 'builders.libsonnet';
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b.tab(
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'GPU',
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b.grid([
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b.place(57, 0, 0, 24, 5),
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b.place(58, 0, 5, 12, 8),
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b.place(59, 12, 5, 12, 8),
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b.place(60, 0, 13, 12, 8),
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b.place(61, 12, 13, 12, 8),
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]),
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[
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b.panel.new(57, 'GPUs', 'table')
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+ b.panel.withDescription('Needs the gpu collector, which is not enabled by default. Utilization is the busiest engine of the GPU.')
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+ b.panel.withQueries([
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b.query.new('max by (luid, name) (windows_gpu_info{job=~"$job", instance="$instance"})', 'A')
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+ b.query.withInstant()
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+ b.query.withFormat('table'),
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b.query.new('clamp_max(max by (luid) (sum by (luid, eng, engtype) (rate(windows_gpu_engine_time_seconds{job=~"$job", instance="$instance"}[$__rate_interval]))), 1)', 'B')
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+ b.query.withInstant()
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+ b.query.withFormat('table'),
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b.query.new('max by (luid) (windows_gpu_adapter_memory_dedicated_bytes{job=~"$job", instance="$instance"})', 'C')
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+ b.query.withInstant()
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+ b.query.withFormat('table'),
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b.query.new('max by (luid) (windows_gpu_dedicated_video_memory_size_bytes{job=~"$job", instance="$instance"})', 'D')
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+ b.query.withInstant()
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+ b.query.withFormat('table'),
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b.query.new('max by (luid) (windows_gpu_adapter_memory_shared_bytes{job=~"$job", instance="$instance"})', 'E')
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+ b.query.withInstant()
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+ b.query.withFormat('table'),
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b.query.new('max by (luid) (windows_gpu_shared_system_memory_size_bytes{job=~"$job", instance="$instance"})', 'F')
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+ b.query.withInstant()
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+ b.query.withFormat('table'),
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])
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+ b.panel.withTransformations([
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{
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group: 'joinByField',
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kind: 'Transformation',
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spec: {
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options: {
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byField: 'luid',
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mode: 'outer',
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},
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},
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},
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{
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group: 'organize',
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kind: 'Transformation',
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spec: {
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options: {
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excludeByName: {
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Time: true,
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'Time 1': true,
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'Time 2': true,
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'Time 3': true,
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'Time 4': true,
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'Time 5': true,
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'Time 6': true,
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'Value #A': true,
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luid: true,
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},
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includeByName: {},
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indexByName: {
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'Value #B': 1,
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'Value #C': 2,
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'Value #D': 3,
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'Value #E': 4,
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'Value #F': 5,
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name: 0,
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},
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renameByName: {
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'Value #B': 'Utilization',
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'Value #C': 'Dedicated memory used',
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'Value #D': 'Dedicated memory',
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'Value #E': 'Shared memory used',
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'Value #F': 'Shared memory',
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name: 'GPU',
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},
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},
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},
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},
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])
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+ b.panel.withOptions({
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sortBy: [],
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})
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+ b.panel.withOverrides([
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{
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matcher: {
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id: 'byName',
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options: 'Value #B',
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},
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properties: [
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{
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id: 'unit',
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value: 'percentunit',
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},
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{
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id: 'min',
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value: 0,
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},
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{
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id: 'max',
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value: 1,
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},
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{
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id: 'thresholds',
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value: {
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mode: 'absolute',
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steps: [
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{
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color: 'green',
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},
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{
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color: 'orange',
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value: 80,
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},
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{
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color: 'red',
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value: 90,
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},
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],
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},
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},
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{
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id: 'color',
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value: {
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mode: 'continuous-GrYlRd',
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},
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},
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{
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id: 'custom.cellOptions',
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value: {
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mode: 'basic',
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type: 'gauge',
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valueDisplayMode: 'text',
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},
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},
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{
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id: 'decimals',
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value: 1,
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},
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],
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},
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{
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matcher: {
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id: 'byName',
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options: 'Value #C',
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},
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properties: [
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{
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id: 'unit',
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value: 'bytes',
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},
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],
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},
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{
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matcher: {
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id: 'byName',
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options: 'Value #D',
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},
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properties: [
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{
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id: 'unit',
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value: 'bytes',
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},
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],
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},
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{
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matcher: {
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id: 'byName',
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options: 'Value #E',
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},
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properties: [
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{
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id: 'unit',
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value: 'bytes',
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},
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],
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},
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{
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matcher: {
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id: 'byName',
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options: 'Value #F',
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},
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properties: [
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{
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id: 'unit',
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value: 'bytes',
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},
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],
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},
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]),
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b.panel.new(58, 'GPU utilization by engine type', 'timeseries')
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+ b.panel.withDescription('Busiest engine of each engine type, as in Task Manager.')
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+ b.panel.withQueries([
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b.query.new('clamp_max(max by (luid, engtype) (sum by (luid, eng, engtype) (rate(windows_gpu_engine_time_seconds{job=~"$job", instance="$instance"}[$__rate_interval]))), 1) * on (luid) group_left (name) max by (luid, name) (windows_gpu_info{job=~"$job", instance="$instance"})', 'A')
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+ b.query.withLegendFormat('{{name}} {{engtype}}'),
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])
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+ b.panel.withDefaults({
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max: 1,
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min: 0,
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}),
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b.panel.new(59, 'GPU memory', 'timeseries')
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+ b.panel.withDescription('Dedicated (video) and shared (system) memory in use, against the size of each pool.')
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+ b.panel.withQueries([
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b.query.new('max by (luid) (windows_gpu_adapter_memory_dedicated_bytes{job=~"$job", instance="$instance"}) * on (luid) group_left (name) max by (luid, name) (windows_gpu_info{job=~"$job", instance="$instance"})', 'A')
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+ b.query.withLegendFormat('{{name}} dedicated used'),
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b.query.new('max by (luid) (windows_gpu_dedicated_video_memory_size_bytes{job=~"$job", instance="$instance"}) * on (luid) group_left (name) max by (luid, name) (windows_gpu_info{job=~"$job", instance="$instance"})', 'B')
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+ b.query.withLegendFormat('{{name}} dedicated size'),
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b.query.new('max by (luid) (windows_gpu_adapter_memory_shared_bytes{job=~"$job", instance="$instance"}) * on (luid) group_left (name) max by (luid, name) (windows_gpu_info{job=~"$job", instance="$instance"})', 'C')
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+ b.query.withLegendFormat('{{name}} shared used'),
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b.query.new('max by (luid) (windows_gpu_shared_system_memory_size_bytes{job=~"$job", instance="$instance"}) * on (luid) group_left (name) max by (luid, name) (windows_gpu_info{job=~"$job", instance="$instance"})', 'D')
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+ b.query.withLegendFormat('{{name}} shared size'),
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])
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+ b.panel.withDefaults({
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min: 0,
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unit: 'bytes',
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})
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+ b.panel.withOverrides([
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{
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matcher: {
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id: 'byRegexp',
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options: '.* size',
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},
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properties: [
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{
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id: 'custom.fillOpacity',
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value: 0,
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},
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{
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id: 'custom.lineStyle',
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value: {
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dash: [
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10,
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10,
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],
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fill: 'dash',
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},
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},
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],
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},
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]),
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b.panel.new(60, 'Top 10 processes by GPU utilization', 'timeseries')
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+ b.panel.withDescription('Busiest GPU engine used by each process. Process names need the process collector; otherwise only the PID is shown.')
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+ b.panel.withQueries([
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b.query.new('topk(10, (max by (process_id) (sum by (process_id, luid, eng) (rate(windows_gpu_engine_time_seconds{job=~"$job", instance="$instance"}[$__rate_interval]))) * on (process_id) group_left (process) max by (process_id, process) (windows_process_info{job=~"$job", instance="$instance"})) or on (process_id) max by (process_id) (sum by (process_id, luid, eng) (rate(windows_gpu_engine_time_seconds{job=~"$job", instance="$instance"}[$__rate_interval]))))', 'A')
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+ b.query.withLegendFormat('{{process}} ({{process_id}})'),
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])
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+ b.panel.withDefaults({
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min: 0,
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})
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+ b.panel.withOptions({
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legend: {
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sortBy: 'Mean',
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sortDesc: true,
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},
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}),
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b.panel.new(61, 'Top 10 processes by dedicated GPU memory', 'timeseries')
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+ b.panel.withDescription('Process names need the process collector; otherwise only the PID is shown.')
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+ b.panel.withQueries([
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b.query.new('topk(10, (sum by (process_id) (windows_gpu_process_memory_dedicated_bytes{job=~"$job", instance="$instance"}) * on (process_id) group_left (process) max by (process_id, process) (windows_process_info{job=~"$job", instance="$instance"})) or on (process_id) sum by (process_id) (windows_gpu_process_memory_dedicated_bytes{job=~"$job", instance="$instance"}))', 'A')
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+ b.query.withLegendFormat('{{process}} ({{process_id}})'),
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])
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+ b.panel.withDefaults({
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min: 0,
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unit: 'bytes',
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})
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+ b.panel.withOptions({
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legend: {
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sortBy: 'Mean',
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sortDesc: true,
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},
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}),
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]
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)
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