mirror of
https://github.com/prometheus-community/windows_exporter.git
synced 2026-10-17 10:09:05 +02:00
Co-authored-by: Claude Opus 5.5 <noreply@anthropic.com> Signed-off-by: Jan-Otto Kröpke <mail@jkroepke.de>
324 lines
12 KiB
Jsonnet
324 lines
12 KiB
Jsonnet
local b = import 'builders.libsonnet';
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function(on)
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b.tab(
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'Hyper-V',
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b.rows([
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if on('hyperv') then b.summary([63, 64, 65, 66, 67, 68]),
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if on('hyperv') then b.row('CPU', b.flow([[69, 12, 8], [70, 12, 8]])),
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if on('hyperv') then b.row('Memory', b.flow([[72, 8, 8], [73, 8, 8], [74, 8, 8]])),
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if on('hyperv') then b.row('Storage', b.flow([[76, 8, 8], [77, 8, 8], [78, 8, 8]])),
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if on('hyperv') then b.row('Network', b.flow([[80, 8, 8], [81, 8, 8], [82, 8, 8]])),
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]),
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[
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b.stat(63, 'Virtual machines', 'Needs the hyperv collector, which is not enabled by default.', 'sum(windows_hyperv_virtual_machine_health_total_count{job=~"$job", instance="$instance"})', 'short'),
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b.stat(64, 'VMs in critical health', 'Number of Hyper-V virtual machines reporting critical health. Inspect the affected VM and Hyper-V event logs; this requires the optional hyperv collector.', 'sum(windows_hyperv_virtual_machine_health_total_count{job=~"$job", instance="$instance", state="critical"})', steps=[{ color: 'green', value: null }, { color: 'red', value: 1 }]),
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b.panel.new(65, 'Hyper-V WMI', 'stat')
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+ b.panel.withDescription('Whether the Hyper-V WMI namespace answers. When it stops answering, Hyper-V Manager and Failover Cluster Manager usually cannot manage the host.')
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+ b.panel.withQueries([
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b.query.new('windows_hyperv_wmi_health{job=~"$job", instance="$instance"}', 'A')
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+ b.query.withInstant(),
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])
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+ b.panel.withDefaults({
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mappings: [
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{
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options: {
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'0': {
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index: 0,
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text: 'not responding',
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},
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'1': {
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index: 1,
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text: 'ok',
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},
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},
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type: 'value',
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},
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],
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thresholds: {
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steps: [
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{
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color: 'red',
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value: null,
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},
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{
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color: 'green',
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value: 1,
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},
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],
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},
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unit: '',
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}),
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b.stat(66, 'Logical processors', 'Number of host logical processors reported by Hyper-V. Use this as capacity context for host and virtual processor load; this requires the optional hyperv collector.', 'windows_hyperv_host_logical_processor_count{job=~"$job", instance="$instance"}', 'short'),
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b.stat(67, 'Virtual processors', 'Virtual processors assigned to all VMs.', 'windows_hyperv_total_vm_processor_count{job=~"$job", instance="$instance"}', 'short'),
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b.stat(68, 'vCPU per logical CPU', 'Virtual processors assigned to VMs per logical processor of the host.', 'windows_hyperv_total_vm_processor_count{job=~"$job", instance="$instance"} / windows_hyperv_host_logical_processor_count{job=~"$job", instance="$instance"}', 'short')
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+ b.panel.withDefaults({ decimals: 2 }),
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b.panel.new(69, 'Host CPU time by state', 'timeseries')
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+ b.panel.withDescription('Share of all logical processors spent running guest code (VMs and the root partition) and in the hypervisor. With Hyper-V enabled, the CPU tab only sees the root partition.')
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+ b.panel.withQueries([
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b.query.new('sum by (state) (rate(windows_hyperv_hypervisor_logical_processor_time_total{job=~"$job", instance="$instance", state!="idle"}[$__rate_interval])) / scalar(count(windows_hyperv_hypervisor_logical_processor_time_total{job=~"$job", instance="$instance", state="idle"}))', 'A')
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+ b.query.withLegendFormat('{{state}}'),
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])
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+ b.panel.withDefaults({
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custom: {
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fillOpacity: 40,
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stacking: {
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mode: 'normal',
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},
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},
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max: 1,
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min: 0,
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}),
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b.panel.new(70, 'CPU usage per VM', 'timeseries')
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+ b.panel.withDescription('Virtual processor run time of each VM as a share of all logical processors of the host.')
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+ b.panel.withQueries([
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b.query.new('sum by (vm) (rate(windows_hyperv_hypervisor_virtual_processor_run_time_total{job=~"$job", instance="$instance"}[$__rate_interval])) / scalar(max(windows_hyperv_host_logical_processor_count{job=~"$job", instance="$instance"}))', 'A')
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+ b.query.withLegendFormat('{{vm}}'),
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])
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+ b.panel.withDefaults({
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custom: {
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fillOpacity: 40,
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stacking: {
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mode: 'normal',
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},
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},
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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(72, 'Memory assigned to VMs', 'timeseries')
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+ b.panel.withDescription('Physical memory currently assigned to each VM with dynamic memory.')
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+ b.panel.withQueries([
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b.query.new('windows_hyperv_dynamic_memory_vm_physical_bytes{job=~"$job", instance="$instance"}', 'A')
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+ b.query.withLegendFormat('{{vm}}'),
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])
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+ b.panel.withDefaults({
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custom: {
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fillOpacity: 40,
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stacking: {
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mode: 'normal',
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},
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},
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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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b.panel.new(73, 'VM memory pressure', 'timeseries')
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+ b.panel.withDescription('Memory a VM needs as a share of the memory it has. Above 100% the VM needs more memory than it is assigned.')
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+ b.panel.withQueries([
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b.query.new('windows_hyperv_dynamic_memory_vm_pressure_current_ratio{job=~"$job", instance="$instance"}', 'A')
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+ b.query.withLegendFormat('{{vm}}'),
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])
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+ b.panel.withDefaults({
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custom: {
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thresholdsStyle: {
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mode: 'dashed',
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},
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},
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min: 0,
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thresholds: {
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steps: [
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{
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color: 'green',
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value: null,
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},
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{
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color: 'red',
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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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b.panel.new(74, 'Memory available for VMs', 'timeseries')
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+ b.panel.withDescription('Memory the dynamic memory balancer can still hand out to VMs.')
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+ b.panel.withQueries([
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b.query.new('windows_hyperv_dynamic_memory_balancer_available_memory_bytes{job=~"$job", instance="$instance"}', 'A')
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+ b.query.withLegendFormat('{{balancer}}'),
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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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calcs: [],
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displayMode: 'list',
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},
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}),
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b.panel.new(76, 'Virtual disk throughput', 'timeseries')
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+ b.panel.withDescription('Reads are drawn below the axis.')
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+ b.panel.withQueries([
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b.query.new('rate(windows_hyperv_virtual_storage_device_bytes_written{job=~"$job", instance="$instance"}[$__rate_interval])', 'A')
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+ b.query.withLegendFormat('{{device}} write'),
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b.query.new('rate(windows_hyperv_virtual_storage_device_bytes_read{job=~"$job", instance="$instance"}[$__rate_interval])', 'B')
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+ b.query.withLegendFormat('{{device}} read'),
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])
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+ b.panel.withDefaults({
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unit: 'Bps',
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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: '.* read$',
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},
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properties: [
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{
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id: 'custom.transform',
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value: 'negative-Y',
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},
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],
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},
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]),
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b.panel.new(77, 'Virtual disk IOPS', 'timeseries')
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+ b.panel.withDescription('Reads are drawn below the axis.')
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+ b.panel.withQueries([
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b.query.new('rate(windows_hyperv_virtual_storage_device_operations_written_total{job=~"$job", instance="$instance"}[$__rate_interval])', 'A')
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+ b.query.withLegendFormat('{{device}} write'),
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b.query.new('rate(windows_hyperv_virtual_storage_device_operations_read_total{job=~"$job", instance="$instance"}[$__rate_interval])', 'B')
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+ b.query.withLegendFormat('{{device}} read'),
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])
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+ b.panel.withDefaults({
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unit: 'iops',
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})
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+ b.panel.withOverrides([
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{
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matcher: {
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id: 'byRegexp',
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options: '.* read$',
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},
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properties: [
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{
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id: 'custom.transform',
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value: 'negative-Y',
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},
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],
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},
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]),
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b.panel.new(78, 'Virtual disk latency and errors', 'timeseries')
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+ b.panel.withDescription('Average I/O latency of each virtual disk: the total I/O latency divided by the number of completed I/O transfers. Errors use the right axis.')
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+ b.panel.withQueries([
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b.query.new('rate(windows_hyperv_virtual_storage_device_io_latency_seconds_total{job=~"$job", instance="$instance"}[$__rate_interval]) / rate(windows_hyperv_virtual_storage_device_throughput_total{job=~"$job", instance="$instance"}[$__rate_interval])', 'A')
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+ b.query.withLegendFormat('{{device}} latency'),
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b.query.new('rate(windows_hyperv_virtual_storage_device_error_count_total{job=~"$job", instance="$instance"}[$__rate_interval]) > 0', 'B')
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+ b.query.withLegendFormat('{{device}} errors'),
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])
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+ b.panel.withDefaults({
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min: 0,
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unit: 's',
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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: '.* errors',
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},
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properties: [
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{
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id: 'unit',
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value: 'ops',
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},
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{
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id: 'custom.axisPlacement',
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value: 'right',
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},
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{
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id: 'color',
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value: {
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fixedColor: 'red',
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mode: 'fixed',
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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(80, 'Virtual switch throughput', 'timeseries')
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+ b.panel.withDescription('Received traffic is drawn below the axis.')
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+ b.panel.withQueries([
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b.query.new('rate(windows_hyperv_vswitch_bytes_sent_total{job=~"$job", instance="$instance"}[$__rate_interval]) * 8', 'A')
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+ b.query.withLegendFormat('{{vswitch}} sent'),
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b.query.new('rate(windows_hyperv_vswitch_bytes_received_total{job=~"$job", instance="$instance"}[$__rate_interval]) * 8', 'B')
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+ b.query.withLegendFormat('{{vswitch}} received'),
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])
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+ b.panel.withDefaults({
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unit: 'bps',
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})
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+ b.panel.withOverrides([
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{
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matcher: {
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id: 'byRegexp',
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options: '.* received$',
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},
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properties: [
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{
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id: 'custom.transform',
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value: 'negative-Y',
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},
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],
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},
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]),
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b.panel.new(81, 'Virtual switch dropped packets', 'timeseries')
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+ b.panel.withDescription('Incoming and outgoing packets dropped per second by each Hyper-V virtual switch. Correlate sustained drops with network load, resource pressure and switch policies; this requires the optional hyperv collector.')
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+ b.panel.withQueries([
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b.query.new('rate(windows_hyperv_vswitch_dropped_packets_incoming_total{job=~"$job", instance="$instance"}[$__rate_interval])', 'A')
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+ b.query.withLegendFormat('{{vswitch}} incoming'),
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b.query.new('rate(windows_hyperv_vswitch_dropped_packets_outcoming_total{job=~"$job", instance="$instance"}[$__rate_interval])', 'B')
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+ b.query.withLegendFormat('{{vswitch}} outgoing'),
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])
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+ b.panel.withDefaults({
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min: 0,
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unit: 'pps',
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}),
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b.panel.new(82, 'VM network adapter throughput', 'timeseries')
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+ b.panel.withDescription('Received traffic is drawn below the axis.')
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+ b.panel.withQueries([
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b.query.new('rate(windows_hyperv_virtual_network_adapter_sent_bytes_total{job=~"$job", instance="$instance"}[$__rate_interval]) * 8', 'A')
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+ b.query.withLegendFormat('{{adapter}} sent'),
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b.query.new('rate(windows_hyperv_virtual_network_adapter_received_bytes_total{job=~"$job", instance="$instance"}[$__rate_interval]) * 8', 'B')
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+ b.query.withLegendFormat('{{adapter}} received'),
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])
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+ b.panel.withDefaults({
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unit: 'bps',
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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: '.* received$',
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},
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properties: [
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{
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id: 'custom.transform',
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value: '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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)
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