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