This is a simple python script to get actual utilization of kubernetes nodes (worker and master)
./nodeutilization.py
Kubernetes Node Utilization..........
+------------------------------------------------+--------+--------+
| NodeName | CPU | Memory |
+------------------------------------------------+--------+--------+
| ip-176-35-32-139.eu-central-1.compute.internal | 13.49% | 60.87% |
| ip-176-35-26-21.eu-central-1.compute.internal | 5.89% | 15.10% |
| ip-176-35-28-29.eu-central-1.compute.internal | 22.79% | 30.34% |
| ip-176-35-4-167.eu-central-1.compute.internal | 11.63% | 39.49% |
| ip-176-35-17-237.eu-central-1.compute.internal | 8.32% | 25.69% |
| ip-176-35-8-237.eu-central-1.compute.internal | 5.15% | 28.78% |
| ip-176-35-8-237.eu-central-1.compute.internal | 6.91% | 46.01% |
| ip-176-35-0-89.eu-central-1.compute.internal | 3.59% | 11.49% |
| ip-176-35-10-120.eu-central-1.compute.internal | 21.19% | 44.44% |
| ip-176-35-7-90.eu-central-1.compute.internal | 5.53% | 20.84% |
| ip-176-35-6-117.eu-central-1.compute.internal | 6.21% | 19.59% |
| ip-176-35-18-150.eu-central-1.compute.internal | 2.68% | 11.10% |
| ip-176-35-4-128.eu-central-1.compute.internal | 4.44% | 17.46% |
| ip-176-35-9-122.eu-central-1.compute.internal | 8.08% | 65.51% |
| ip-176-35-22-243.eu-central-1.compute.internal | 6.29% | 19.28% |
| ip-176-35-4-216.eu-central-1.compute.internal | 68.89% | 56.30% |
| ip-176-35-13-48.eu-central-1.compute.internal | 7.03% | 53.98% |
| ip-176-35-19-57.eu-central-1.compute.internal | 3.77% | 9.28% |
| ip-176-35-7-121.eu-central-1.compute.internal | 3.82% | 11.81% |
| ip-176-35-8-59.eu-central-1.compute.internal | 12.47% | 60.03% |
| ip-176-35-12-135.eu-central-1.compute.internal | 12.18% | 63.57% |
| ip-176-35-16-203.eu-central-1.compute.internal | 3.49% | 28.76% |
| ip-176-35-7-197.eu-central-1.compute.internal | 4.83% | 14.87% |
+------------------------------------------------+--------+--------+If you need the utilization based on requests and limits
└─ $ ▶ kubectl describe node | grep -A5 "Allocated"
Allocated resources:
(Total limits may be over 100 percent, i.e., overcommitted.)
Resource Requests Limits
-------- -------- ------
cpu 15794m (99%) 29932m (189%)
memory 28216Mi (92%) 29140Mi (95%)
--
Allocated resources:
(Total limits may be over 100 percent, i.e., overcommitted.)
Resource Requests Limits
-------- -------- ------
cpu 15402m (97%) 16512m (104%)
memory 27805Mi (90%) 28825Mi (94%)
--
Allocated resources:
(Total limits may be over 100 percent, i.e., overcommitted.)
Resource Requests Limits
-------- -------- ------
cpu 15827m (100%) 26702m (169%)
memory 29186Mi (95%) 32234Mi (105%)
--
Allocated resources:
(Total limits may be over 100 percent, i.e., overcommitted.)
Resource Requests Limits
-------- -------- ------
cpu 15232m (96%) 15232m (96%)
memory 31114185932 (96%) 31114185932 (96%)
--
Allocated resources:
(Total limits may be over 100 percent, i.e., overcommitted.)
Resource Requests Limits
-------- -------- ------
cpu 15816m (100%) 35436m (224%)
memory 29900Mi (97%) 29900Mi (97%)
--
Allocated resources:
(Total limits may be over 100 percent, i.e., overcommitted.)
Resource Requests Limits
-------- -------- ------
cpu 15349m (97%) 21174m (134%)
memory 27099085728 (84%) 28709698464 (89%)