import { Badge } from '@/components/ui';
import { AmaruWiringPanel } from '@/components/AmaruLive';
import {
Cpu,
Layers,
MonitorDot,
Network,
Server,
Workflow,
Zap,
} from 'lucide-react';
import {
ResponsiveContainer,
AreaChart,
Area,
XAxis,
YAxis,
Tooltip,
} from 'recharts';
interface ClusterNode {
id: string;
name: string;
type: 'gpu' | 'cpu' | 'tpu';
hardware: string;
status: 'active' | 'draining' | 'offline';
utilization: number;
memory: string;
jobs: number;
uptime: string;
}
const CLUSTER_NODES: ClusterNode[] = [
{ id: 'n1', name: 'lambda-h100-0', type: 'gpu', hardware: 'NVIDIA H100 SXM', status: 'active', utilization: 87, memory: '72/80 GB', jobs: 4, uptime: '14d 6h' },
{ id: 'n2', name: 'lambda-h100-1', type: 'gpu', hardware: 'NVIDIA H100 SXM', status: 'active', utilization: 93, memory: '76/80 GB', jobs: 5, uptime: '14d 6h' },
{ id: 'n3', name: 'lambda-a100-0', type: 'gpu', hardware: 'NVIDIA A100 80G', status: 'active', utilization: 62, memory: '48/80 GB', jobs: 3, uptime: '31d 2h' },
{ id: 'n4', name: 'lambda-a100-1', type: 'gpu', hardware: 'NVIDIA A100 80G', status: 'draining', utilization: 34, memory: '22/80 GB', jobs: 1, uptime: '31d 2h' },
{ id: 'n5', name: 'k8s-worker-0', type: 'cpu', hardware: 'AMD EPYC 9654', status: 'active', utilization: 41, memory: '128/256 GB', jobs: 12, uptime: '62d 18h' },
{ id: 'n6', name: 'k8s-worker-1', type: 'cpu', hardware: 'AMD EPYC 9654', status: 'active', utilization: 58, memory: '164/256 GB', jobs: 9, uptime: '62d 18h' },
{ id: 'n7', name: 'slurm-batch-0', type: 'cpu', hardware: 'Intel Xeon w9-3595X', status: 'active', utilization: 78, memory: '384/512 GB', jobs: 24, uptime: '7d 4h' },
{ id: 'n8', name: 'dstack-spot-0', type: 'gpu', hardware: 'NVIDIA H200 141G', status: 'active', utilization: 96, memory: '134/141 GB', jobs: 2, uptime: '0d 8h' },
];
const ORCHESTRATORS = [
{ name: 'Kubernetes', status: 'active', nodes: 4, icon:
AMARU · COMPUTE · ORCHESTRATION
GPU/CPU cluster management across Kubernetes, Slurm, dstack, and Lambda Cloud. Inspired by Lambda AI's flexible orchestration architecture.
{o.name}
{o.desc}
{o.nodes} node{o.nodes > 1 ? 's' : ''}
{totalGpu}
GPU Nodes
{totalCpu}
CPU Nodes
{avgUtil}%
Avg Util
{totalJobs}
Active Jobs
{label}
GPU: {payload[0]?.value}%
CPU: {payload[1]?.value}%
MEM: {payload[2]?.value}%
| Node | Hardware | Status | Util | Memory | Jobs | Uptime |
|---|---|---|---|---|---|---|
|
|
{n.hardware} |
|
80 ? '#fb923c' : n.utilization > 60 ? '#facc15' : '#4ade80' }}> {n.utilization}% | {n.memory} | {n.jobs} | {n.uptime} |