Files
docker-images/_scripts/get_resources.py

73 lines
2.5 KiB
Python
Executable File

#!/usr/bin/python3
import kubernetes as k8s
from pint import UnitRegistry
from collections import defaultdict
__all__ = ["compute_allocated_resources"]
def compute_allocated_resources():
ureg = UnitRegistry()
ureg.load_definitions('kubernetes_units.txt')
Q_ = ureg.Quantity
data = {}
# doing this computation within a k8s cluster
k8s.config.load_kube_config()
core_v1 = k8s.client.CoreV1Api()
# print("Listing pods with their IPs:")
# ret = core_v1.list_pod_for_all_namespaces(watch=False)
# for i in ret.items:
# print("%s\t%s\t%s" % (i.status.pod_ip, i.metadata.namespace, i.metadata.name))
for node in core_v1.list_node().items:
stats = {}
node_name = node.metadata.name
allocatable = node.status.allocatable
max_pods = int(int(allocatable["pods"]) * 1.5)
# print("{} ALLOC: {} MAX_PODS: {}".format(node_name,allocatable,max_pods))
field_selector = ("status.phase!=Succeeded,status.phase!=Failed," +
"spec.nodeName=" + node_name)
stats["cpu_alloc"] = Q_(allocatable["cpu"])
stats["mem_alloc"] = Q_(allocatable["memory"])
pods = core_v1.list_pod_for_all_namespaces(limit=max_pods,
field_selector=field_selector).items
# compute the allocated resources
cpureqs, cpulmts, memreqs, memlmts = [], [], [], []
for pod in pods:
for container in pod.spec.containers:
res = container.resources
reqs = defaultdict(lambda: 0, res.requests or {})
lmts = defaultdict(lambda: 0, res.limits or {})
cpureqs.append(Q_(reqs["cpu"]))
memreqs.append(Q_(reqs["memory"]))
cpulmts.append(Q_(lmts["cpu"]))
memlmts.append(Q_(lmts["memory"]))
stats["cpu_req"] = sum(cpureqs)
stats["cpu_lmt"] = sum(cpulmts)
stats["cpu_req_per"] = (stats["cpu_req"] / stats["cpu_alloc"] * 100)
stats["cpu_lmt_per"] = (stats["cpu_lmt"] / stats["cpu_alloc"] * 100)
stats["mem_req"] = sum(memreqs)
stats["mem_lmt"] = sum(memlmts)
stats["mem_req_per"] = (stats["mem_req"] / stats["mem_alloc"] * 100)
stats["mem_lmt_per"] = (stats["mem_lmt"] / stats["mem_alloc"] * 100)
data[node_name] = stats
return data
if __name__ == "__main__":
# execute only if run as a script
print(compute_allocated_resources())