99 lines
3.4 KiB
Python
99 lines
3.4 KiB
Python
from fastapi import APIRouter, Response
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from database import fetch_all
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from kubernetes import client, config
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import yaml
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import json
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import logging
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router = APIRouter()
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# Helper functions for conversions
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def convert_cpu_to_cores(cpu):
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"""
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Convert CPU usage to cores for human-readable format.
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Handles units: n (nano), u (micro), m (milli), or none (cores).
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Returns float values for cores, rounded appropriately.
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"""
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if "n" in cpu: # Nanocores to cores
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return round(int(cpu.replace("n", "")) / 1e9, 4)
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elif "u" in cpu: # Microcores to cores
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return round(int(cpu.replace("u", "")) / 1e6, 4)
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elif "m" in cpu: # Millicores to cores
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return round(int(cpu.replace("m", "")) / 1000, 4)
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return float(cpu) # Already in cores
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def convert_memory_to_mib(memory):
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"""
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Convert memory to MiB (mebibytes).
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Handles units: Ki (kibibytes), Mi (mebibytes), Gi (gibibytes).
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"""
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if "Ki" in memory:
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return int(memory.replace("Ki", "")) / 1024
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elif "Mi" in memory:
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return int(memory.replace("Mi", ""))
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elif "Gi" in memory:
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return int(memory.replace("Gi", "")) * 1024
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return float(memory)
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# Fetch Kubernetes data with namespace resource usage
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def fetch_k8s_data_with_usage():
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config.load_incluster_config()
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v1 = client.CoreV1Api()
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metrics_client = client.CustomObjectsApi()
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# Fetch nodes
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nodes = [{
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"node_name": node.metadata.name,
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"cpu": node.status.capacity.get("cpu"),
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"memory": round(convert_memory_to_mib(node.status.capacity.get("memory")), 2), # Convert to MiB
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"pods_allocatable": node.status.allocatable.get("pods"),
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} for node in v1.list_node().items]
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# Fetch namespaces
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namespaces = [ns.metadata.name for ns in v1.list_namespace().items]
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# Fetch pod metrics and calculate namespace resource usage
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namespace_usage = {}
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pod_metrics = metrics_client.list_cluster_custom_object(
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group="metrics.k8s.io", version="v1beta1", plural="pods"
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)
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for pod in pod_metrics["items"]:
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pod_namespace = pod["metadata"]["namespace"]
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if pod_namespace not in namespace_usage:
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namespace_usage[pod_namespace] = {"cpu": 0, "memory": 0}
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for container in pod["containers"]:
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cpu_usage = container["usage"]["cpu"]
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memory_usage = container["usage"]["memory"]
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# Convert CPU to cores and memory to MiB
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namespace_usage[pod_namespace]["cpu"] += convert_cpu_to_cores(cpu_usage)
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namespace_usage[pod_namespace]["memory"] += convert_memory_to_mib(memory_usage)
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# Round and format usage for readability
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namespace_usage = {
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ns: {
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"cpu": round(usage["cpu"], 4), # Round to 4 decimal places
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"memory": round(usage["memory"], 2), # Memory in MiB
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}
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for ns, usage in namespace_usage.items()
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}
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return {"nodes": nodes, "namespaces": namespaces, "namespace_usage": namespace_usage}
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# Export endpoint
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@router.get("/export")
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def export_data(format: str = "yaml"):
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data = {
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"metal_nodes": fetch_all("metal_nodes"),
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"virtual_machines": fetch_all("virtual_machines"),
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"kubernetes": fetch_k8s_data_with_usage(),
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}
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if format.lower() == "yaml":
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yaml_data = yaml.safe_dump(data, sort_keys=False)
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return Response(content=yaml_data, media_type="text/yaml")
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return Response(content=json.dumps(data, indent=2), media_type="application/json")
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