easylinux/kube-prometheus
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Use grafanalib to generate Grafana dashboards

Browse Source
This commit is contained in:
Arve Knudsen
2017-09-15 08:05:12 +02:00
parent 8bf449907c
commit d04cccc526
25 changed files with 3504 additions and 6831 deletions
Download Patch File Download Diff File Expand all files Collapse all files

200
assets/grafana/kubernetes-resource-requests.dashboard.py Normal file
View File

@@ -0,0 +1,200 @@
from grafanalib.core import *
dashboard = Dashboard(
title='Kubernetes Resource Requests',
version=2,
graphTooltip=0,
refresh=False,
schemaVersion=14,
time=Time(start='now-3h'),
timezone='browser',
inputs=[
{
'name': 'DS_PROMETHEUS',
'label': 'prometheus',
'description': '',
'type': 'datasource',
'pluginId': 'prometheus',
'pluginName': 'Prometheus'
},
],
rows=[
Row(
height=300, title='CPU Cores', showTitle=False,
titleSize='h6', panels=[
Graph(
title='CPU Cores',
description='This represents the total [CPU resource '
'requests](https://kubernetes.io/docs/concepts/configu'
'ration/manage-compute-resources-container/#meaning-of-'
'cpu) in the cluster.\nFor comparison the total '
'[allocatable CPU cores](https://github.com/kubernetes/'
'community/blob/master/contributors/design-proposals/'
'node-allocatable.md) is also shown.',
id=1,
dataSource='${DS_PROMETHEUS}',
dashLength=10,
dashes=False,
isNew=False,
lineWidth=1,
spaceLength=10,
nullPointMode='null',
span=9,
tooltip=Tooltip(
msResolution=False, valueType='individual'
),
yAxes=YAxes(
YAxis(format='short', label='CPU Cores', min=None,),
YAxis(format='short', min=None),
),
targets=[
{
'expr': 'min(sum(kube_node_status_allocatable_'
'cpu_cores) by (instance))',
'hide': False,
'intervalFactor': 2,
'legendFormat': 'Allocatable CPU Cores',
'refId': 'A',
'step': 20,
},
{
'expr': 'max(sum(kube_pod_container_resource_'
'requests_cpu_cores) by (instance))',
'hide': False,
'intervalFactor': 2,
'legendFormat': 'Requested CPU Cores',
'refId': 'B',
'step': 20,
},
],
),
SingleStat(
title='CPU Cores',
dataSource='${DS_PROMETHEUS}',
id=2,
format='percent',
span=3,
gauge=Gauge(show=True),
sparkline=SparkLine(show=True),
valueFontSize='110%',
thresholds='80, 90',
valueMaps=[
{
'op': '=',
'text': 'N/A',
'value': 'null',
},
],
rangeMaps=[
{
'from': 'null',
'text': 'N/A',
'to': 'null',
},
],
targets=[
{
'expr': 'max(sum(kube_pod_container_resource_'
'requests_cpu_cores) by (instance)) / min(sum'
'(kube_node_status_allocatable_cpu_cores) by '
'(instance)) * 100',
'intervalFactor': 2,
'legendFormat': '',
'refId': 'A',
'step': 240,
},
],
),
],
),
Row(
height=300, title='Memory', showTitle=False,
titleSize='h6', panels=[
Graph(
title='Memory',
id=3,
dataSource='${DS_PROMETHEUS}',
description='This represents the total [memory resource '
'requests](https://kubernetes.io/docs/concepts/'
'configuration/manage-compute-resources-container/'
'#meaning-of-memory) in the cluster.\nFor comparison '
'the total [allocatable memory](https://github.com/'
'kubernetes/community/blob/master/contributors/'
'design-proposals/node-allocatable.md) is also shown.',
dashLength=10,
dashes=False,
lineWidth=1,
isNew=False,
spaceLength=10,
span=9,
nullPointMode='null',
tooltip=Tooltip(
msResolution=False, valueType='individual'
),
yAxes=YAxes(
YAxis(format='bytes', label='Memory', min=None),
YAxis(format='short', min=None),
),
targets=[
{
'expr': 'min(sum(kube_node_status_allocatable_'
'memory_bytes) by (instance))',
'hide': False,
'intervalFactor': 2,
'legendFormat': 'Allocatable Memory',
'refId': 'A',
'step': 20,
},
{
'expr': 'max(sum(kube_pod_container_resource_'
'requests_memory_bytes) by (instance))',
'hide': False,
'intervalFactor': 2,
'legendFormat': 'Requested Memory',
'refId': 'B',
'step': 20,
},
],
),
SingleStat(
title='Memory',
dataSource='${DS_PROMETHEUS}',
id=4,
format='percent',
span=3,
gauge=Gauge(show=True),
sparkline=SparkLine(show=True),
valueFontSize='110%',
thresholds='80, 90',
valueMaps=[
{
'op': '=',
'text': 'N/A',
'value': 'null',
},
],
rangeMaps=[
{
'from': 'null',
'text': 'N/A',
'to': 'null',
},
],
targets=[
{
'expr': 'max(sum(kube_pod_container_resource_'
'requests_memory_bytes) by (instance)) / '
'min(sum(kube_node_status_allocatable_memory_'
'bytes) by (instance)) * 100',
'intervalFactor': 2,
'legendFormat': '',
'refId': 'A',
'step': 240,
},
],
),
],
),
],
)