Migrate all page components from the @cameleer/design-system v0.0.3 example UI, replacing mock data with real backend API hooks. This brings richer visuals (KpiStrip, GroupCard, RouteFlow, ProcessorTimeline, DateRangePicker, expandable rows) while preserving all existing API integration, auth, and routing infrastructure. Pages migrated: Dashboard, RoutesMetrics, RouteDetail, ExchangeDetail, AgentHealth, AgentInstance, OidcConfig, AuditLog, RBAC (Users/Groups/Roles). Also enhanced LayoutShell CommandPalette with real search data from catalog. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
355 lines
11 KiB
TypeScript
355 lines
11 KiB
TypeScript
import { useMemo } from 'react';
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import { useParams, useNavigate } from 'react-router';
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import {
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KpiStrip,
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DataTable,
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AreaChart,
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LineChart,
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BarChart,
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Card,
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Sparkline,
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MonoText,
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Badge,
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} from '@cameleer/design-system';
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import type { KpiItem, Column } from '@cameleer/design-system';
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import { useGlobalFilters } from '@cameleer/design-system';
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import { useRouteMetrics } from '../../api/queries/catalog';
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import { useExecutionStats, useStatsTimeseries } from '../../api/queries/executions';
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import type { RouteMetrics } from '../../api/types';
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import styles from './RoutesMetrics.module.css';
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interface RouteRow {
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id: string;
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routeId: string;
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appId: string;
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exchangeCount: number;
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successRate: number;
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avgDurationMs: number;
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p99DurationMs: number;
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errorRate: number;
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throughputPerSec: number;
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sparkline: number[];
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}
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// ── Route table columns ──────────────────────────────────────────────────────
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const ROUTE_COLUMNS: Column<RouteRow>[] = [
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{
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key: 'routeId',
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header: 'Route',
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sortable: true,
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render: (_, row) => (
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<span className={styles.routeNameCell}>{row.routeId}</span>
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),
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},
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{
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key: 'appId',
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header: 'Application',
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sortable: true,
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render: (_, row) => (
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<span className={styles.appCell}>{row.appId}</span>
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),
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},
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{
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key: 'exchangeCount',
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header: 'Exchanges',
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sortable: true,
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render: (_, row) => (
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<MonoText size="sm">{row.exchangeCount.toLocaleString()}</MonoText>
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),
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},
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{
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key: 'successRate',
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header: 'Success %',
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sortable: true,
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render: (_, row) => {
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const pct = row.successRate * 100;
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const cls = pct >= 99 ? styles.rateGood : pct >= 97 ? styles.rateWarn : styles.rateBad;
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return <MonoText size="sm" className={cls}>{pct.toFixed(1)}%</MonoText>;
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},
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},
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{
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key: 'avgDurationMs',
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header: 'Avg Duration',
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sortable: true,
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render: (_, row) => (
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<MonoText size="sm">{Math.round(row.avgDurationMs)}ms</MonoText>
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),
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},
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{
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key: 'p99DurationMs',
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header: 'p99 Duration',
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sortable: true,
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render: (_, row) => {
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const cls = row.p99DurationMs > 300 ? styles.rateBad : row.p99DurationMs > 200 ? styles.rateWarn : styles.rateGood;
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return <MonoText size="sm" className={cls}>{Math.round(row.p99DurationMs)}ms</MonoText>;
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},
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},
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{
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key: 'errorRate',
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header: 'Error Rate',
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sortable: true,
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render: (_, row) => {
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const pct = row.errorRate * 100;
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const cls = pct > 5 ? styles.rateBad : pct > 1 ? styles.rateWarn : styles.rateGood;
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return <MonoText size="sm" className={cls}>{pct.toFixed(1)}%</MonoText>;
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},
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},
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{
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key: 'sparkline',
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header: 'Trend',
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render: (_, row) => (
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<Sparkline data={row.sparkline} width={80} height={24} />
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),
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},
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];
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// ── Build KPI items from backend stats ───────────────────────────────────────
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function buildKpiItems(
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stats: {
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totalCount: number;
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failedCount: number;
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avgDurationMs: number;
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p99LatencyMs: number;
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activeCount: number;
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prevTotalCount: number;
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prevFailedCount: number;
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prevP99LatencyMs: number;
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} | undefined,
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routeCount: number,
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throughputSparkline: number[],
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errorSparkline: number[],
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): KpiItem[] {
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const totalCount = stats?.totalCount ?? 0;
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const failedCount = stats?.failedCount ?? 0;
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const prevTotalCount = stats?.prevTotalCount ?? 0;
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const p99Ms = stats?.p99LatencyMs ?? 0;
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const prevP99Ms = stats?.prevP99LatencyMs ?? 0;
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const avgMs = stats?.avgDurationMs ?? 0;
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const activeCount = stats?.activeCount ?? 0;
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const errorRate = totalCount > 0 ? (failedCount / totalCount) * 100 : 0;
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const throughputPctChange = prevTotalCount > 0
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? Math.round(((totalCount - prevTotalCount) / prevTotalCount) * 100)
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: 0;
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const throughputTrendLabel = throughputPctChange >= 0
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? `\u25B2 +${throughputPctChange}%`
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: `\u25BC ${throughputPctChange}%`;
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const p50 = Math.round(avgMs * 0.5);
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const p95 = Math.round(avgMs * 1.4);
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const slaStatus = p99Ms > 300 ? 'BREACH' : 'OK';
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const prevErrorRate = prevTotalCount > 0
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? ((stats?.prevFailedCount ?? 0) / prevTotalCount) * 100
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: 0;
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const errorDelta = (errorRate - prevErrorRate).toFixed(1);
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return [
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{
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label: 'Total Throughput',
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value: totalCount.toLocaleString(),
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trend: {
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label: throughputTrendLabel,
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variant: throughputPctChange >= 0 ? 'success' as const : 'error' as const,
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},
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subtitle: `${activeCount} active exchanges`,
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sparkline: throughputSparkline,
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borderColor: 'var(--amber)',
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},
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{
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label: 'System Error Rate',
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value: `${errorRate.toFixed(2)}%`,
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trend: {
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label: errorRate <= prevErrorRate ? `\u25BC ${errorDelta}%` : `\u25B2 +${errorDelta}%`,
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variant: errorRate < 1 ? 'success' as const : 'error' as const,
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},
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subtitle: `${failedCount} errors / ${totalCount.toLocaleString()} total`,
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sparkline: errorSparkline,
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borderColor: errorRate < 1 ? 'var(--success)' : 'var(--error)',
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},
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{
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label: 'Latency Percentiles',
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value: `${p99Ms}ms`,
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trend: {
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label: p99Ms > prevP99Ms ? `\u25B2 +${p99Ms - prevP99Ms}ms` : `\u25BC ${prevP99Ms - p99Ms}ms`,
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variant: p99Ms > 300 ? 'error' as const : 'warning' as const,
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},
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subtitle: `P50 ${p50}ms \u00B7 P95 ${p95}ms \u00B7 SLA <300ms P99: ${slaStatus}`,
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borderColor: p99Ms > 300 ? 'var(--warning)' : 'var(--success)',
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},
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{
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label: 'Active Routes',
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value: `${routeCount}`,
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trend: { label: '\u2194 stable', variant: 'muted' as const },
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subtitle: `${routeCount} routes reporting`,
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borderColor: 'var(--running)',
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},
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{
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label: 'In-Flight Exchanges',
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value: String(activeCount),
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trend: { label: '\u2194', variant: 'muted' as const },
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subtitle: `${activeCount} active`,
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sparkline: throughputSparkline,
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borderColor: 'var(--amber)',
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},
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];
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}
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// ── Component ────────────────────────────────────────────────────────────────
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export default function RoutesMetrics() {
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const { appId } = useParams();
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const navigate = useNavigate();
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const { timeRange } = useGlobalFilters();
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const timeFrom = timeRange.start.toISOString();
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const timeTo = timeRange.end.toISOString();
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const { data: metrics } = useRouteMetrics(timeFrom, timeTo, appId);
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const { data: stats } = useExecutionStats(timeFrom, timeTo, undefined, appId);
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const { data: timeseries } = useStatsTimeseries(timeFrom, timeTo, undefined, appId);
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// Map backend RouteMetrics[] to table rows
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const rows: RouteRow[] = useMemo(() =>
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(metrics || []).map((m: RouteMetrics) => ({
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id: `${m.appId}/${m.routeId}`,
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routeId: m.routeId,
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appId: m.appId,
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exchangeCount: m.exchangeCount,
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successRate: m.successRate,
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avgDurationMs: m.avgDurationMs,
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p99DurationMs: m.p99DurationMs,
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errorRate: m.errorRate,
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throughputPerSec: m.throughputPerSec,
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sparkline: m.sparkline ?? [],
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})),
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[metrics],
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);
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// Sparkline data from timeseries buckets
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const throughputSparkline = useMemo(() =>
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(timeseries?.buckets || []).map((b) => b.totalCount),
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[timeseries],
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);
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const errorSparkline = useMemo(() =>
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(timeseries?.buckets || []).map((b) => b.failedCount),
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[timeseries],
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);
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// Chart series from timeseries buckets
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const throughputChartSeries = useMemo(() => [{
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label: 'Throughput',
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data: (timeseries?.buckets || []).map((b, i) => ({
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x: i as number,
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y: b.totalCount,
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})),
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}], [timeseries]);
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const latencyChartSeries = useMemo(() => [{
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label: 'Latency',
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data: (timeseries?.buckets || []).map((b, i) => ({
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x: i as number,
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y: b.avgDurationMs,
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})),
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}], [timeseries]);
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const errorBarSeries = useMemo(() => [{
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label: 'Errors',
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data: (timeseries?.buckets || []).map((b) => {
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const ts = new Date(b.time);
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const label = !isNaN(ts.getTime())
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? ts.toLocaleTimeString([], { hour: '2-digit', minute: '2-digit' })
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: '—';
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return { x: label, y: b.failedCount };
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}),
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}], [timeseries]);
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const volumeChartSeries = useMemo(() => [{
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label: 'Volume',
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data: (timeseries?.buckets || []).map((b, i) => ({
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x: i as number,
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y: b.totalCount,
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})),
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}], [timeseries]);
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const kpiItems = useMemo(() =>
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buildKpiItems(stats, rows.length, throughputSparkline, errorSparkline),
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[stats, rows.length, throughputSparkline, errorSparkline],
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);
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return (
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<div className={styles.content}>
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<div className={styles.refreshIndicator}>
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<span className={styles.refreshDot} />
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<span className={styles.refreshText}>Auto-refresh: 30s</span>
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</div>
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{/* KPI header cards */}
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<KpiStrip items={kpiItems} />
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{/* Per-route performance table */}
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<div className={styles.tableSection}>
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<div className={styles.tableHeader}>
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<span className={styles.tableTitle}>Per-Route Performance</span>
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<div className={styles.tableRight}>
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<span className={styles.tableMeta}>{rows.length} routes</span>
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<Badge label="LIVE" color="success" />
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</div>
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</div>
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<DataTable
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columns={ROUTE_COLUMNS}
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data={rows}
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sortable
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onRowClick={(row) => {
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const targetAppId = appId ?? row.appId;
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navigate(`/routes/${targetAppId}/${row.routeId}`);
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}}
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/>
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</div>
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{/* 2x2 chart grid */}
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{(timeseries?.buckets?.length ?? 0) > 0 && (
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<div className={styles.chartGrid}>
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<Card title="Throughput (msg/s)">
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<AreaChart
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series={throughputChartSeries}
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yLabel="msg/s"
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height={200}
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className={styles.chart}
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/>
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</Card>
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<Card title="Latency (ms)">
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<LineChart
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series={latencyChartSeries}
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yLabel="ms"
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threshold={{ value: 300, label: 'SLA 300ms' }}
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height={200}
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className={styles.chart}
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/>
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</Card>
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<Card title="Errors by Route">
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<BarChart
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series={errorBarSeries}
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height={200}
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className={styles.chart}
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/>
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</Card>
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<Card title="Message Volume (msg/min)">
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<AreaChart
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series={volumeChartSeries}
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yLabel="msg/min"
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height={200}
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className={styles.chart}
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/>
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</Card>
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</div>
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)}
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</div>
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);
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}
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