103 lines
4.5 KiB
Plaintext
103 lines
4.5 KiB
Plaintext
async def get_available_resources(ns={}):
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# 创建 API 实例
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v1 = client.CoreV1Api()
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# 获取所有节点
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nodes = v1.list_node()
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# 获取所有 Pod
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pods = v1.list_pod_for_all_namespaces()
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# 存储节点资源信息
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node_resources = {}
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total_allocatable = {
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'cpu': 0,
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'memory': 0,
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'gpu': 0,
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'storage': 0
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}
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total_used = {
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'cpu': 0,
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'memory': 0,
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'gpu': 0,
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'storage': 0
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}
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for node in nodes.items:
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name = node.metadata.name
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allocatable = node.status.allocatable
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node_resources[name] = {
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'cpu_allocatable': int(allocatable.get('cpu', '0').rstrip('m')) / 1000 if 'm' in allocatable.get('cpu', '0') else int(allocatable.get('cpu', '0')),
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'memory_allocatable': int(allocatable.get('memory', '0').rstrip('Ki')) / 1024 / 1024,
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'gpu_allocatable': int(allocatable.get('nvidia.com/gpu', '0')),
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'storage_allocatable': int(allocatable.get('ephemeral-storage', '0').rstrip('Ki')) / 1024 / 1024
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}
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# 累加总可分配资源
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total_allocatable['cpu'] += node_resources[name]['cpu_allocatable']
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total_allocatable['memory'] += node_resources[name]['memory_allocatable']
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total_allocatable['gpu'] += node_resources[name]['gpu_allocatable']
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total_allocatable['storage'] += node_resources[name]['storage_allocatable']
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# 初始化已分配
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node_resources[name].update({
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'cpu_used': 0,
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'memory_used': 0,
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'gpu_used': 0,
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'storage_used': 0
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})
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# 遍历所有 Pod，统计每个节点的已分配资源
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for pod in pods.items:
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if pod.spec.node_name: # 确保 Pod 已被调度到节点
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node_name = pod.spec.node_name
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for container in pod.spec.containers:
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reque = container.resources.requests or {}
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node_resources[node_name]['cpu_used'] += float(reque.get('cpu', '0').rstrip('m')) / 1000 if 'm' in reque.get('cpu', '0') else float(reque.get('cpu', '0'))
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node_resources[node_name]['memory_used'] += int(reque.get('memory', '0').rstrip('Mi')) if 'Mi' in reque.get('memory', '0') else int(reque.get('memory', '0').rstrip('Gi')) * 1024
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node_resources[node_name]['gpu_used'] += int(reque.get('nvidia.com/gpu', '0'))
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node_resources[node_name]['storage_used'] += int(reque.get('ephemeral-storage', '0').rstrip('Mi')) if 'Mi' in reque.get('ephemeral-storage', '0') else 0
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# 计算总已使用资源
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for node_name, resources in node_resources.items():
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total_used['cpu'] += resources['cpu_used']
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total_used['memory'] += resources['memory_used']
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total_used['gpu'] += resources['gpu_used']
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total_used['storage'] += resources['storage_used']
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# 计算节点的资源占用情况
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print(f"Node: {node_name}")
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print(f" CPU Remaining: {resources['cpu_allocatable'] - resources['cpu_used']} cores")
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print(f" Memory Remaining: {resources['memory_allocatable'] - resources['memory_used']} Mi")
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print(f" GPU Remaining: {resources['gpu_allocatable'] - resources['gpu_used']} GPUs")
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print(f" Storage Remaining: {resources['storage_allocatable'] - resources['storage_used']} Mi")
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print()
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# 计算总剩余资源和使用百分比
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total_remaining = {key: total_allocatable[key] - total_used[key] for key in total_allocatable}
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usage_percentage = {key: (total_used[key] / total_allocatable[key] * 100 if total_allocatable[key] > 0 else 0) for key in total_allocatable}
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# 输出总资源和使用情况
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print("Cluster Resource Summary:")
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print(f" Total Allocatable CPU: {total_allocatable['cpu']} cores")
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print(f" Total Allocatable Memory: {total_allocatable['memory']} Mi")
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print(f" Total Allocatable GPU: {total_allocatable['gpu']} GPUs")
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print(f" Total Allocatable Storage: {total_allocatable['storage']} Mi")
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print()
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print(f" CPU Usage Percentage: {usage_percentage['cpu']:.2f}%")
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print(f" Memory Usage Percentage: {usage_percentage['memory']:.2f}%")
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print(f" GPU Usage Percentage: {usage_percentage['gpu']:.2f}%")
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print(f" Storage Usage Percentage: {usage_percentage['storage']:.2f}%")
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print()
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# 返回数据
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return {
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"total_allocatable": total_allocatable,
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"total_used": total_used,
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"total_remaining": total_remaining,
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"usage_percentage": usage_percentage
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}
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ret = await get_available_resources(params_kw)
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return ret
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