Files
cameleer-server/ui/src/pages/Routes/RoutesMetrics.tsx
hsiegeln 81f85aa82d
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feat: replace UI with design system example pages wired to real API
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>
2026-03-24 16:42:16 +01:00

355 lines
11 KiB
TypeScript

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