feat: progressive drill-down dashboard with RED metrics and SLA compliance (#94)
Three-level dashboard driven by sidebar selection: - L1 (no selection): all-apps overview with health table, per-app charts - L2 (app selected): route performance table, error velocity, top errors - L3 (route selected): processor table, latency heatmap data, bottleneck KPI Backend: 3 new endpoints (timeseries/by-app, timeseries/by-route, errors/top), per-app SLA settings (app_settings table, V12 migration), exact SLA compliance from executions hypertable, error velocity with acceleration detection. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
hsiegeln
142
ui/src/api/queries/dashboard.ts
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142
ui/src/api/queries/dashboard.ts
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@@ -0,0 +1,142 @@
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import { useQuery, useMutation, useQueryClient } from '@tanstack/react-query';
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import { config } from '../../config';
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import { useAuthStore } from '../../auth/auth-store';
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import { useRefreshInterval } from './use-refresh-interval';
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function authHeaders() {
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const token = useAuthStore.getState().accessToken;
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return {
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Authorization: `Bearer ${token}`,
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'X-Cameleer-Protocol-Version': '1',
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};
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}
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async function fetchJson<T>(path: string, params?: Record<string, string | undefined>): Promise<T> {
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const qs = new URLSearchParams();
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if (params) {
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for (const [k, v] of Object.entries(params)) {
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if (v != null) qs.set(k, v);
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}
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}
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const url = `${config.apiBaseUrl}${path}${qs.toString() ? `?${qs}` : ''}`;
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const res = await fetch(url, { headers: authHeaders() });
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if (!res.ok) throw new Error(`Failed to fetch ${path}`);
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return res.json();
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}
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// ── Timeseries by app (L1 charts) ─────────────────────────────────────
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export interface TimeseriesBucket {
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time: string;
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totalCount: number;
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failedCount: number;
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avgDurationMs: number;
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p99DurationMs: number;
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activeCount: number;
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}
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export interface GroupedTimeseries {
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[key: string]: { buckets: TimeseriesBucket[] };
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}
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export function useTimeseriesByApp(from?: string, to?: string) {
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const refetchInterval = useRefreshInterval(30_000);
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return useQuery({
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queryKey: ['dashboard', 'timeseries-by-app', from, to],
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queryFn: () => fetchJson<GroupedTimeseries>('/search/stats/timeseries/by-app', {
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from, to, buckets: '24',
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}),
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enabled: !!from,
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placeholderData: (prev: GroupedTimeseries | undefined) => prev,
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refetchInterval,
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});
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}
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// ── Timeseries by route (L2 charts) ───────────────────────────────────
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export function useTimeseriesByRoute(from?: string, to?: string, application?: string) {
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const refetchInterval = useRefreshInterval(30_000);
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return useQuery({
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queryKey: ['dashboard', 'timeseries-by-route', from, to, application],
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queryFn: () => fetchJson<GroupedTimeseries>('/search/stats/timeseries/by-route', {
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from, to, application, buckets: '24',
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}),
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enabled: !!from && !!application,
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placeholderData: (prev: GroupedTimeseries | undefined) => prev,
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refetchInterval,
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});
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}
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// ── Top errors (L2/L3) ────────────────────────────────────────────────
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export interface TopError {
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errorType: string;
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routeId: string | null;
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processorId: string | null;
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count: number;
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velocity: number;
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trend: 'accelerating' | 'stable' | 'decelerating';
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lastSeen: string;
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}
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export function useTopErrors(from?: string, to?: string, application?: string, routeId?: string) {
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const refetchInterval = useRefreshInterval(10_000);
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return useQuery({
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queryKey: ['dashboard', 'top-errors', from, to, application, routeId],
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queryFn: () => fetchJson<TopError[]>('/search/errors/top', {
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from, to, application, routeId, limit: '5',
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}),
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enabled: !!from,
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placeholderData: (prev: TopError[] | undefined) => prev,
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refetchInterval,
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});
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}
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// ── App settings ──────────────────────────────────────────────────────
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export interface AppSettings {
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appId: string;
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slaThresholdMs: number;
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healthErrorWarn: number;
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healthErrorCrit: number;
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healthSlaWarn: number;
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healthSlaCrit: number;
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createdAt: string;
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updatedAt: string;
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}
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export function useAppSettings(appId?: string) {
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return useQuery({
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queryKey: ['app-settings', appId],
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queryFn: () => fetchJson<AppSettings>(`/admin/app-settings/${appId}`),
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enabled: !!appId,
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staleTime: 60_000,
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});
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}
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export function useAllAppSettings() {
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return useQuery({
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queryKey: ['app-settings', 'all'],
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queryFn: () => fetchJson<AppSettings[]>('/admin/app-settings'),
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staleTime: 60_000,
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});
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}
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export function useUpdateAppSettings() {
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const queryClient = useQueryClient();
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return useMutation({
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mutationFn: async ({ appId, settings }: { appId: string; settings: Omit<AppSettings, 'appId' | 'createdAt' | 'updatedAt'> }) => {
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const token = useAuthStore.getState().accessToken;
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const res = await fetch(`${config.apiBaseUrl}/admin/app-settings/${appId}`, {
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method: 'PUT',
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headers: { ...authHeaders(), 'Content-Type': 'application/json' },
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body: JSON.stringify(settings),
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});
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if (!res.ok) throw new Error('Failed to update app settings');
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return res.json();
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},
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onSuccess: () => {
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queryClient.invalidateQueries({ queryKey: ['app-settings'] });
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},
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});
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}
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442
ui/src/pages/DashboardTab/DashboardL1.tsx
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442
ui/src/pages/DashboardTab/DashboardL1.tsx
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@@ -0,0 +1,442 @@
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import { useMemo } from 'react';
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import { 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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Card,
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Sparkline,
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MonoText,
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StatusDot,
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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 { useTimeseriesByApp, useTopErrors, useAllAppSettings } from '../../api/queries/dashboard';
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import type { AppSettings } from '../../api/queries/dashboard';
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import type { RouteMetrics } from '../../api/types';
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import {
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computeHealthDot,
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formatThroughput,
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formatSlaCompliance,
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trendIndicator,
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type HealthStatus,
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} from './dashboard-utils';
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import styles from './DashboardTab.module.css';
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// ── Row type for application health table ───────────────────────────────────
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interface AppRow {
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id: string;
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appId: string;
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health: HealthStatus;
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throughput: number;
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throughputLabel: string;
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successRate: number;
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p99DurationMs: number;
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slaCompliance: number;
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errorCount: number;
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sparkline: number[];
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}
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// ── Table columns ───────────────────────────────────────────────────────────
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const APP_COLUMNS: Column<AppRow>[] = [
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{
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key: 'health',
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header: '',
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render: (_, row) => <StatusDot status={row.health} />,
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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.appNameCell}>{row.appId}</span>
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),
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},
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{
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key: 'throughput',
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header: 'Throughput',
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sortable: true,
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render: (_, row) => (
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<MonoText size="sm">{row.throughputLabel}</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;
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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: 'p99DurationMs',
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header: 'P99',
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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: 'slaCompliance',
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header: 'SLA %',
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sortable: true,
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render: (_, row) => {
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const cls = row.slaCompliance >= 99 ? styles.rateGood : row.slaCompliance >= 95 ? styles.rateWarn : styles.rateBad;
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return <MonoText size="sm" className={cls}>{formatSlaCompliance(row.slaCompliance)}</MonoText>;
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},
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},
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{
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key: 'errorCount',
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header: 'Errors',
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sortable: true,
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render: (_, row) => {
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const cls = row.errorCount > 10 ? styles.rateBad : row.errorCount > 0 ? styles.rateWarn : styles.rateGood;
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return <MonoText size="sm" className={cls}>{row.errorCount.toLocaleString()}</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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// ── Aggregate RouteMetrics by appId ─────────────────────────────────────────
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function aggregateByApp(
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metrics: RouteMetrics[],
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windowSeconds: number,
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settingsMap: Map<string, AppSettings>,
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): AppRow[] {
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const grouped = new Map<string, RouteMetrics[]>();
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for (const m of metrics) {
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const list = grouped.get(m.appId) ?? [];
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list.push(m);
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grouped.set(m.appId, list);
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}
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const rows: AppRow[] = [];
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for (const [appId, routes] of grouped) {
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const totalExchanges = routes.reduce((s, r) => s + r.exchangeCount, 0);
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const totalFailed = routes.reduce((s, r) => s + r.exchangeCount * r.errorRate, 0);
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const successRate = totalExchanges > 0 ? ((totalExchanges - totalFailed) / totalExchanges) * 100 : 100;
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const errorRate = totalExchanges > 0 ? totalFailed / totalExchanges : 0;
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// Weighted average p99 by exchange count
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const p99Sum = routes.reduce((s, r) => s + r.p99DurationMs * r.exchangeCount, 0);
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const p99DurationMs = totalExchanges > 0 ? p99Sum / totalExchanges : 0;
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// SLA compliance: weighted average of per-route slaCompliance from backend
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const appSettings = settingsMap.get(appId);
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const slaWeightedSum = routes.reduce((s, r) => s + (r.slaCompliance ?? 100) * r.exchangeCount, 0);
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const slaCompliance = totalExchanges > 0 ? slaWeightedSum / totalExchanges : 100;
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const errorCount = Math.round(totalFailed);
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// Merge sparklines: sum across routes per bucket position
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const maxLen = Math.max(...routes.map((r) => (r.sparkline ?? []).length), 0);
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const sparkline: number[] = [];
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for (let i = 0; i < maxLen; i++) {
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sparkline.push(routes.reduce((s, r) => s + ((r.sparkline ?? [])[i] ?? 0), 0));
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}
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rows.push({
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id: appId,
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appId,
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health: computeHealthDot(errorRate, slaCompliance, appSettings),
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throughput: totalExchanges,
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throughputLabel: formatThroughput(totalExchanges, windowSeconds),
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successRate,
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p99DurationMs,
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slaCompliance,
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errorCount,
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sparkline,
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});
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}
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return rows.sort((a, b) => {
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const order: Record<HealthStatus, number> = { error: 0, warning: 1, success: 2 };
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return order[a.health] - order[b.health];
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});
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}
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// ── Build KPI items ─────────────────────────────────────────────────────────
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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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p99LatencyMs: 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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windowSeconds: number,
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slaCompliance: number,
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activeErrorCount: number,
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throughputSparkline: number[],
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successSparkline: number[],
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latencySparkline: number[],
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slaSparkline: 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 prevFailedCount = stats?.prevFailedCount ?? 0;
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const p99Ms = stats?.p99LatencyMs ?? 0;
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const prevP99Ms = stats?.prevP99LatencyMs ?? 0;
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// Throughput
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const throughput = windowSeconds > 0 ? totalCount / windowSeconds : 0;
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const prevThroughput = windowSeconds > 0 ? prevTotalCount / windowSeconds : 0;
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const throughputTrend = trendIndicator(throughput, prevThroughput);
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// Success Rate
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const successPct = totalCount > 0 ? ((totalCount - failedCount) / totalCount) * 100 : 100;
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const prevSuccessPct = prevTotalCount > 0
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? ((prevTotalCount - prevFailedCount) / prevTotalCount) * 100
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: 100;
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const successTrend = trendIndicator(successPct, prevSuccessPct);
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// P99 Latency
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const p99Trend = trendIndicator(p99Ms, prevP99Ms);
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// SLA compliance trend — higher is better, so invert the variant
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const slaTrend = trendIndicator(slaCompliance, 100);
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// Active Errors
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const prevErrorRate = prevTotalCount > 0 ? (prevFailedCount / prevTotalCount) * 100 : 0;
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const currentErrorRate = totalCount > 0 ? (failedCount / totalCount) * 100 : 0;
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const errorTrend = trendIndicator(currentErrorRate, prevErrorRate);
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return [
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{
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label: 'Throughput',
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value: formatThroughput(totalCount, windowSeconds),
|
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trend: {
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label: throughputTrend.label,
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variant: throughputTrend.direction === 'up' ? 'success' as const : throughputTrend.direction === 'down' ? 'error' as const : 'muted' as const,
|
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},
|
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subtitle: `${totalCount.toLocaleString()} msg total`,
|
||||
sparkline: throughputSparkline,
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borderColor: 'var(--amber)',
|
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},
|
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{
|
||||
label: 'Success Rate',
|
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value: `${successPct.toFixed(1)}%`,
|
||||
trend: {
|
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label: successTrend.label,
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variant: successPct >= 99 ? 'success' as const : successPct >= 97 ? 'warning' as const : 'error' as const,
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},
|
||||
subtitle: `${(totalCount - failedCount).toLocaleString()} succeeded`,
|
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sparkline: successSparkline,
|
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borderColor: successPct >= 99 ? 'var(--success)' : 'var(--error)',
|
||||
},
|
||||
{
|
||||
label: 'P99 Latency',
|
||||
value: `${Math.round(p99Ms)}ms`,
|
||||
trend: {
|
||||
label: p99Trend.label,
|
||||
variant: p99Ms > 300 ? 'error' as const : p99Ms > 200 ? 'warning' as const : 'success' as const,
|
||||
},
|
||||
subtitle: `prev ${Math.round(prevP99Ms)}ms`,
|
||||
sparkline: latencySparkline,
|
||||
borderColor: p99Ms > 300 ? 'var(--warning)' : 'var(--success)',
|
||||
},
|
||||
{
|
||||
label: 'SLA Compliance',
|
||||
value: formatSlaCompliance(slaCompliance),
|
||||
trend: {
|
||||
label: slaTrend.label,
|
||||
variant: slaCompliance >= 99 ? 'success' as const : slaCompliance >= 95 ? 'warning' as const : 'error' as const,
|
||||
},
|
||||
subtitle: 'P99 within threshold',
|
||||
sparkline: slaSparkline,
|
||||
borderColor: slaCompliance >= 99 ? 'var(--success)' : 'var(--warning)',
|
||||
},
|
||||
{
|
||||
label: 'Active Errors',
|
||||
value: String(activeErrorCount),
|
||||
trend: {
|
||||
label: errorTrend.label,
|
||||
variant: activeErrorCount === 0 ? 'success' as const : 'error' as const,
|
||||
},
|
||||
subtitle: `${failedCount.toLocaleString()} failures total`,
|
||||
sparkline: errorSparkline,
|
||||
borderColor: activeErrorCount === 0 ? 'var(--success)' : 'var(--error)',
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
// ── Component ───────────────────────────────────────────────────────────────
|
||||
|
||||
export default function DashboardL1() {
|
||||
const navigate = useNavigate();
|
||||
const { timeRange } = useGlobalFilters();
|
||||
const timeFrom = timeRange.start.toISOString();
|
||||
const timeTo = timeRange.end.toISOString();
|
||||
const windowSeconds = (timeRange.end.getTime() - timeRange.start.getTime()) / 1000;
|
||||
|
||||
const { data: metrics } = useRouteMetrics(timeFrom, timeTo);
|
||||
const { data: stats } = useExecutionStats(timeFrom, timeTo);
|
||||
const { data: timeseries } = useStatsTimeseries(timeFrom, timeTo);
|
||||
const { data: timeseriesByApp } = useTimeseriesByApp(timeFrom, timeTo);
|
||||
const { data: topErrors } = useTopErrors(timeFrom, timeTo);
|
||||
const { data: allAppSettings } = useAllAppSettings();
|
||||
|
||||
// Build settings lookup map
|
||||
const settingsMap = useMemo(() => {
|
||||
const map = new Map<string, AppSettings>();
|
||||
for (const s of allAppSettings ?? []) {
|
||||
map.set(s.appId, s);
|
||||
}
|
||||
return map;
|
||||
}, [allAppSettings]);
|
||||
|
||||
// Aggregate route metrics by appId for the table
|
||||
const appRows = useMemo(
|
||||
() => aggregateByApp(metrics ?? [], windowSeconds, settingsMap),
|
||||
[metrics, windowSeconds, settingsMap],
|
||||
);
|
||||
|
||||
// Global SLA compliance from backend stats (exact calculation from executions table)
|
||||
const globalSlaCompliance = (stats as Record<string, unknown>)?.slaCompliance as number ?? -1;
|
||||
const effectiveSlaCompliance = globalSlaCompliance >= 0 ? globalSlaCompliance : 100;
|
||||
|
||||
// Active error count = distinct error types
|
||||
const activeErrorCount = useMemo(
|
||||
() => (topErrors ?? []).length,
|
||||
[topErrors],
|
||||
);
|
||||
|
||||
// KPI sparklines from timeseries buckets
|
||||
const throughputSparkline = useMemo(
|
||||
() => (timeseries?.buckets ?? []).map((b) => b.totalCount),
|
||||
[timeseries],
|
||||
);
|
||||
const successSparkline = useMemo(
|
||||
() => (timeseries?.buckets ?? []).map((b) =>
|
||||
b.totalCount > 0 ? ((b.totalCount - b.failedCount) / b.totalCount) * 100 : 100,
|
||||
),
|
||||
[timeseries],
|
||||
);
|
||||
const latencySparkline = useMemo(
|
||||
() => (timeseries?.buckets ?? []).map((b) => b.p99DurationMs),
|
||||
[timeseries],
|
||||
);
|
||||
const slaSparkline = useMemo(
|
||||
() => (timeseries?.buckets ?? []).map((b) =>
|
||||
b.p99DurationMs <= 300 ? 100 : 0,
|
||||
),
|
||||
[timeseries],
|
||||
);
|
||||
const errorSparkline = useMemo(
|
||||
() => (timeseries?.buckets ?? []).map((b) => b.failedCount),
|
||||
[timeseries],
|
||||
);
|
||||
|
||||
const kpiItems = useMemo(
|
||||
() => buildKpiItems(
|
||||
stats,
|
||||
windowSeconds,
|
||||
effectiveSlaCompliance,
|
||||
activeErrorCount,
|
||||
throughputSparkline,
|
||||
successSparkline,
|
||||
latencySparkline,
|
||||
slaSparkline,
|
||||
errorSparkline,
|
||||
),
|
||||
[stats, windowSeconds, effectiveSlaCompliance, activeErrorCount,
|
||||
throughputSparkline, successSparkline, latencySparkline, slaSparkline, errorSparkline],
|
||||
);
|
||||
|
||||
// ── Per-app chart series (throughput stacked area) ──────────────────────
|
||||
const throughputByAppSeries = useMemo(() => {
|
||||
if (!timeseriesByApp) return [];
|
||||
return Object.entries(timeseriesByApp).map(([appId, { buckets }]) => ({
|
||||
label: appId,
|
||||
data: buckets.map((b, i) => ({
|
||||
x: i as number,
|
||||
y: b.totalCount,
|
||||
})),
|
||||
}));
|
||||
}, [timeseriesByApp]);
|
||||
|
||||
// ── Per-app chart series (error rate line) ─────────────────────────────
|
||||
const errorRateByAppSeries = useMemo(() => {
|
||||
if (!timeseriesByApp) return [];
|
||||
return Object.entries(timeseriesByApp).map(([appId, { buckets }]) => ({
|
||||
label: appId,
|
||||
data: buckets.map((b, i) => ({
|
||||
x: i as number,
|
||||
y: b.totalCount > 0 ? (b.failedCount / b.totalCount) * 100 : 0,
|
||||
})),
|
||||
}));
|
||||
}, [timeseriesByApp]);
|
||||
|
||||
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} />
|
||||
|
||||
{/* Application Health table */}
|
||||
<div className={styles.tableSection}>
|
||||
<div className={styles.tableHeader}>
|
||||
<span className={styles.tableTitle}>Application Health</span>
|
||||
<div className={styles.tableRight}>
|
||||
<span className={styles.tableMeta}>{appRows.length} applications</span>
|
||||
<Badge label="ALL" color="muted" />
|
||||
</div>
|
||||
</div>
|
||||
<DataTable
|
||||
columns={APP_COLUMNS}
|
||||
data={appRows}
|
||||
sortable
|
||||
onRowClick={(row) => navigate(`/dashboard/${row.appId}`)}
|
||||
/>
|
||||
</div>
|
||||
|
||||
{/* Side-by-side charts */}
|
||||
{throughputByAppSeries.length > 0 && (
|
||||
<div className={styles.chartGrid}>
|
||||
<Card title="Throughput by Application (msg/s)">
|
||||
<AreaChart
|
||||
series={throughputByAppSeries}
|
||||
yLabel="msg/s"
|
||||
stacked
|
||||
height={200}
|
||||
className={styles.chart}
|
||||
/>
|
||||
</Card>
|
||||
|
||||
<Card title="Error Rate by Application (%)">
|
||||
<LineChart
|
||||
series={errorRateByAppSeries}
|
||||
yLabel="%"
|
||||
height={200}
|
||||
className={styles.chart}
|
||||
/>
|
||||
</Card>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
421
ui/src/pages/DashboardTab/DashboardL2.tsx
Normal file
421
ui/src/pages/DashboardTab/DashboardL2.tsx
Normal file
@@ -0,0 +1,421 @@
|
||||
import { useMemo } from 'react';
|
||||
import { useParams, useNavigate } from 'react-router';
|
||||
import {
|
||||
KpiStrip,
|
||||
DataTable,
|
||||
AreaChart,
|
||||
LineChart,
|
||||
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 {
|
||||
useTimeseriesByRoute,
|
||||
useTopErrors,
|
||||
useAppSettings,
|
||||
} from '../../api/queries/dashboard';
|
||||
import type { TopError } from '../../api/queries/dashboard';
|
||||
import type { RouteMetrics } from '../../api/types';
|
||||
import {
|
||||
trendArrow,
|
||||
trendIndicator,
|
||||
formatThroughput,
|
||||
formatSlaCompliance,
|
||||
formatRelativeTime,
|
||||
} from './dashboard-utils';
|
||||
import styles from './DashboardTab.module.css';
|
||||
|
||||
// ── Route table row type ────────────────────────────────────────────────────
|
||||
|
||||
interface RouteRow {
|
||||
id: string;
|
||||
routeId: string;
|
||||
exchangeCount: number;
|
||||
successRate: number;
|
||||
avgDurationMs: number;
|
||||
p99DurationMs: number;
|
||||
slaCompliance: number;
|
||||
sparkline: number[];
|
||||
}
|
||||
|
||||
// ── Route performance columns ───────────────────────────────────────────────
|
||||
|
||||
const ROUTE_COLUMNS: Column<RouteRow>[] = [
|
||||
{
|
||||
key: 'routeId',
|
||||
header: 'Route ID',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{row.routeId}</MonoText>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'exchangeCount',
|
||||
header: 'Throughput',
|
||||
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(ms)',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{Math.round(row.avgDurationMs)}</MonoText>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'p99DurationMs',
|
||||
header: 'P99(ms)',
|
||||
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)}</MonoText>;
|
||||
},
|
||||
},
|
||||
{
|
||||
key: 'slaCompliance',
|
||||
header: 'SLA%',
|
||||
sortable: true,
|
||||
render: (_, row) => {
|
||||
const cls = row.slaCompliance >= 99 ? styles.rateGood : row.slaCompliance >= 95 ? styles.rateWarn : styles.rateBad;
|
||||
return <MonoText size="sm" className={cls}>{formatSlaCompliance(row.slaCompliance)}</MonoText>;
|
||||
},
|
||||
},
|
||||
{
|
||||
key: 'sparkline',
|
||||
header: 'Sparkline',
|
||||
render: (_, row) => (
|
||||
<Sparkline data={row.sparkline} width={80} height={24} />
|
||||
),
|
||||
},
|
||||
];
|
||||
|
||||
// ── Top errors columns ──────────────────────────────────────────────────────
|
||||
|
||||
const ERROR_COLUMNS: Column<TopError>[] = [
|
||||
{
|
||||
key: 'errorType',
|
||||
header: 'Error Type',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{row.errorType}</MonoText>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'routeId',
|
||||
header: 'Route',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{row.routeId ?? '\u2014'}</MonoText>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'count',
|
||||
header: 'Count',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{row.count.toLocaleString()}</MonoText>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'velocity',
|
||||
header: 'Velocity',
|
||||
sortable: true,
|
||||
render: (_, row) => {
|
||||
const arrow = trendArrow(row.trend);
|
||||
const cls = row.trend === 'accelerating' ? styles.rateBad
|
||||
: row.trend === 'decelerating' ? styles.rateGood
|
||||
: styles.rateNeutral;
|
||||
return <MonoText size="sm" className={cls}>{row.velocity.toFixed(1)}/min {arrow}</MonoText>;
|
||||
},
|
||||
},
|
||||
{
|
||||
key: 'lastSeen',
|
||||
header: 'Last Seen',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{formatRelativeTime(row.lastSeen)}</MonoText>
|
||||
),
|
||||
},
|
||||
];
|
||||
|
||||
// ── Build KPI items ─────────────────────────────────────────────────────────
|
||||
|
||||
function buildKpiItems(
|
||||
stats: {
|
||||
totalCount: number;
|
||||
failedCount: number;
|
||||
p99LatencyMs: number;
|
||||
prevTotalCount: number;
|
||||
prevFailedCount: number;
|
||||
prevP99LatencyMs: number;
|
||||
} | undefined,
|
||||
slaThresholdMs: number,
|
||||
throughputSparkline: number[],
|
||||
latencySparkline: number[],
|
||||
errors: TopError[] | undefined,
|
||||
windowSeconds: number,
|
||||
): KpiItem[] {
|
||||
const totalCount = stats?.totalCount ?? 0;
|
||||
const failedCount = stats?.failedCount ?? 0;
|
||||
const prevTotalCount = stats?.prevTotalCount ?? 0;
|
||||
const prevFailedCount = stats?.prevFailedCount ?? 0;
|
||||
const p99Ms = stats?.p99LatencyMs ?? 0;
|
||||
const prevP99Ms = stats?.prevP99LatencyMs ?? 0;
|
||||
|
||||
// Throughput
|
||||
const throughputTrend = trendIndicator(totalCount, prevTotalCount);
|
||||
|
||||
// Success Rate
|
||||
const successRate = totalCount > 0 ? ((totalCount - failedCount) / totalCount) * 100 : 100;
|
||||
const prevSuccessRate = prevTotalCount > 0 ? ((prevTotalCount - prevFailedCount) / prevTotalCount) * 100 : 100;
|
||||
const successTrend = trendIndicator(successRate, prevSuccessRate);
|
||||
|
||||
// P99 Latency
|
||||
const latencyTrend = trendIndicator(p99Ms, prevP99Ms);
|
||||
|
||||
// SLA Compliance — percentage of exchanges under threshold
|
||||
// Approximate from p99: if p99 < threshold, ~99%+ are compliant
|
||||
const slaCompliance = p99Ms <= slaThresholdMs ? 99.9 : Math.max(0, 100 - ((p99Ms - slaThresholdMs) / slaThresholdMs) * 10);
|
||||
|
||||
// Error Velocity — aggregate from top errors
|
||||
const errorList = errors ?? [];
|
||||
const totalVelocity = errorList.reduce((sum, e) => sum + e.velocity, 0);
|
||||
const hasAccelerating = errorList.some((e) => e.trend === 'accelerating');
|
||||
const allDecelerating = errorList.length > 0 && errorList.every((e) => e.trend === 'decelerating');
|
||||
const velocityTrendLabel = hasAccelerating ? '\u25B2' : allDecelerating ? '\u25BC' : '\u2500\u2500';
|
||||
const velocityVariant = hasAccelerating ? 'error' as const : allDecelerating ? 'success' as const : 'muted' as const;
|
||||
|
||||
return [
|
||||
{
|
||||
label: 'Throughput',
|
||||
value: formatThroughput(totalCount, windowSeconds),
|
||||
trend: {
|
||||
label: throughputTrend.label,
|
||||
variant: throughputTrend.direction === 'up' ? 'success' as const : throughputTrend.direction === 'down' ? 'error' as const : 'muted' as const,
|
||||
},
|
||||
sparkline: throughputSparkline,
|
||||
borderColor: 'var(--amber)',
|
||||
},
|
||||
{
|
||||
label: 'Success Rate',
|
||||
value: `${successRate.toFixed(2)}%`,
|
||||
trend: {
|
||||
label: successTrend.label,
|
||||
variant: successTrend.direction === 'up' ? 'success' as const : successTrend.direction === 'down' ? 'error' as const : 'muted' as const,
|
||||
},
|
||||
borderColor: successRate >= 99 ? 'var(--success)' : successRate >= 95 ? 'var(--warning)' : 'var(--error)',
|
||||
},
|
||||
{
|
||||
label: 'P99 Latency',
|
||||
value: `${Math.round(p99Ms)}ms`,
|
||||
trend: {
|
||||
label: latencyTrend.label,
|
||||
variant: latencyTrend.direction === 'up' ? 'error' as const : latencyTrend.direction === 'down' ? 'success' as const : 'muted' as const,
|
||||
},
|
||||
sparkline: latencySparkline,
|
||||
borderColor: p99Ms > slaThresholdMs ? 'var(--error)' : 'var(--success)',
|
||||
},
|
||||
{
|
||||
label: 'SLA Compliance',
|
||||
value: formatSlaCompliance(slaCompliance),
|
||||
trend: {
|
||||
label: slaCompliance >= 99 ? 'OK' : 'BREACH',
|
||||
variant: slaCompliance >= 99 ? 'success' as const : 'error' as const,
|
||||
},
|
||||
subtitle: `Threshold: ${slaThresholdMs}ms`,
|
||||
borderColor: slaCompliance >= 99 ? 'var(--success)' : slaCompliance >= 95 ? 'var(--warning)' : 'var(--error)',
|
||||
},
|
||||
{
|
||||
label: 'Error Velocity',
|
||||
value: `${totalVelocity.toFixed(1)}/min`,
|
||||
trend: {
|
||||
label: velocityTrendLabel,
|
||||
variant: velocityVariant,
|
||||
},
|
||||
subtitle: `${errorList.length} error type${errorList.length !== 1 ? 's' : ''} tracked`,
|
||||
borderColor: hasAccelerating ? 'var(--error)' : allDecelerating ? 'var(--success)' : 'var(--text-muted)',
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
// ── Component ───────────────────────────────────────────────────────────────
|
||||
|
||||
export default function DashboardL2() {
|
||||
const { appId } = useParams<{ appId: string }>();
|
||||
const navigate = useNavigate();
|
||||
const { timeRange } = useGlobalFilters();
|
||||
const timeFrom = timeRange.start.toISOString();
|
||||
const timeTo = timeRange.end.toISOString();
|
||||
const windowSeconds = (timeRange.end.getTime() - timeRange.start.getTime()) / 1000;
|
||||
|
||||
// Data hooks
|
||||
const { data: stats } = useExecutionStats(timeFrom, timeTo, undefined, appId);
|
||||
const { data: timeseries } = useStatsTimeseries(timeFrom, timeTo, undefined, appId);
|
||||
const { data: metrics } = useRouteMetrics(timeFrom, timeTo, appId);
|
||||
const { data: timeseriesByRoute } = useTimeseriesByRoute(timeFrom, timeTo, appId);
|
||||
const { data: errors } = useTopErrors(timeFrom, timeTo, appId);
|
||||
const { data: appSettings } = useAppSettings(appId);
|
||||
|
||||
const slaThresholdMs = appSettings?.slaThresholdMs ?? 300;
|
||||
|
||||
// Route performance table rows
|
||||
const routeRows: RouteRow[] = useMemo(() =>
|
||||
(metrics || []).map((m: RouteMetrics) => {
|
||||
const sla = m.p99DurationMs <= slaThresholdMs
|
||||
? 99.9
|
||||
: Math.max(0, 100 - ((m.p99DurationMs - slaThresholdMs) / slaThresholdMs) * 10);
|
||||
return {
|
||||
id: m.routeId,
|
||||
routeId: m.routeId,
|
||||
exchangeCount: m.exchangeCount,
|
||||
successRate: m.successRate,
|
||||
avgDurationMs: m.avgDurationMs,
|
||||
p99DurationMs: m.p99DurationMs,
|
||||
slaCompliance: sla,
|
||||
sparkline: m.sparkline ?? [],
|
||||
};
|
||||
}),
|
||||
[metrics, slaThresholdMs],
|
||||
);
|
||||
|
||||
// KPI sparklines from timeseries
|
||||
const throughputSparkline = useMemo(() =>
|
||||
(timeseries?.buckets || []).map((b) => b.totalCount),
|
||||
[timeseries],
|
||||
);
|
||||
const latencySparkline = useMemo(() =>
|
||||
(timeseries?.buckets || []).map((b) => b.p99DurationMs),
|
||||
[timeseries],
|
||||
);
|
||||
|
||||
const kpiItems = useMemo(() =>
|
||||
buildKpiItems(stats, slaThresholdMs, throughputSparkline, latencySparkline, errors, windowSeconds),
|
||||
[stats, slaThresholdMs, throughputSparkline, latencySparkline, errors, windowSeconds],
|
||||
);
|
||||
|
||||
// Throughput by Route — stacked area chart series
|
||||
const throughputByRouteSeries = useMemo(() => {
|
||||
if (!timeseriesByRoute) return [];
|
||||
return Object.entries(timeseriesByRoute).map(([routeId, data]) => ({
|
||||
label: routeId,
|
||||
data: (data.buckets || []).map((b, i) => ({
|
||||
x: i as number,
|
||||
y: b.totalCount,
|
||||
})),
|
||||
}));
|
||||
}, [timeseriesByRoute]);
|
||||
|
||||
// Latency percentiles chart — P99 line from app-level timeseries
|
||||
const latencyChartSeries = useMemo(() => {
|
||||
const buckets = timeseries?.buckets || [];
|
||||
return [
|
||||
{
|
||||
label: 'P99',
|
||||
data: buckets.map((b, i) => ({
|
||||
x: i as number,
|
||||
y: b.p99DurationMs,
|
||||
})),
|
||||
},
|
||||
{
|
||||
label: 'Avg',
|
||||
data: buckets.map((b, i) => ({
|
||||
x: i as number,
|
||||
y: b.avgDurationMs,
|
||||
})),
|
||||
},
|
||||
];
|
||||
}, [timeseries]);
|
||||
|
||||
// Error rows with stable identity
|
||||
const errorRows = useMemo(() =>
|
||||
(errors ?? []).map((e, i) => ({ ...e, id: `${e.errorType}-${e.routeId}-${i}` })),
|
||||
[errors],
|
||||
);
|
||||
|
||||
return (
|
||||
<div className={styles.content}>
|
||||
<div className={styles.refreshIndicator}>
|
||||
<span className={styles.refreshDot} />
|
||||
<span className={styles.refreshText}>Auto-refresh: 30s</span>
|
||||
</div>
|
||||
|
||||
{/* KPI Strip */}
|
||||
<KpiStrip items={kpiItems} />
|
||||
|
||||
{/* Route Performance Table */}
|
||||
<div className={styles.tableSection}>
|
||||
<div className={styles.tableHeader}>
|
||||
<span className={styles.tableTitle}>Route Performance</span>
|
||||
<div className={styles.tableRight}>
|
||||
<span className={styles.tableMeta}>{routeRows.length} routes</span>
|
||||
<Badge label="LIVE" color="success" />
|
||||
</div>
|
||||
</div>
|
||||
<DataTable
|
||||
columns={ROUTE_COLUMNS}
|
||||
data={routeRows}
|
||||
sortable
|
||||
onRowClick={(row) => navigate(`/dashboard/${appId}/${row.routeId}`)}
|
||||
/>
|
||||
</div>
|
||||
|
||||
{/* Charts: Throughput by Route + Latency Percentiles */}
|
||||
{(timeseries?.buckets?.length ?? 0) > 0 && (
|
||||
<div className={styles.chartGrid}>
|
||||
<Card title="Throughput by Route">
|
||||
<AreaChart
|
||||
series={throughputByRouteSeries}
|
||||
yLabel="msg/s"
|
||||
stacked
|
||||
height={200}
|
||||
className={styles.chart}
|
||||
/>
|
||||
</Card>
|
||||
|
||||
<Card title="Latency Percentiles">
|
||||
<LineChart
|
||||
series={latencyChartSeries}
|
||||
yLabel="ms"
|
||||
threshold={{ value: slaThresholdMs, label: `SLA ${slaThresholdMs}ms` }}
|
||||
height={200}
|
||||
className={styles.chart}
|
||||
/>
|
||||
</Card>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Top 5 Errors — hidden when empty */}
|
||||
{errorRows.length > 0 && (
|
||||
<div className={styles.errorsSection}>
|
||||
<div className={styles.tableHeader}>
|
||||
<span className={styles.tableTitle}>Top Errors</span>
|
||||
<span className={styles.tableMeta}>{errorRows.length} error types</span>
|
||||
</div>
|
||||
<DataTable
|
||||
columns={ERROR_COLUMNS}
|
||||
data={errorRows}
|
||||
sortable
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
434
ui/src/pages/DashboardTab/DashboardL3.tsx
Normal file
434
ui/src/pages/DashboardTab/DashboardL3.tsx
Normal file
@@ -0,0 +1,434 @@
|
||||
import { useMemo } from 'react';
|
||||
import { useParams } from 'react-router';
|
||||
import {
|
||||
KpiStrip,
|
||||
DataTable,
|
||||
AreaChart,
|
||||
LineChart,
|
||||
Card,
|
||||
MonoText,
|
||||
Badge,
|
||||
} from '@cameleer/design-system';
|
||||
import type { KpiItem, Column } from '@cameleer/design-system';
|
||||
import { useGlobalFilters } from '@cameleer/design-system';
|
||||
import { useExecutionStats, useStatsTimeseries } from '../../api/queries/executions';
|
||||
import { useProcessorMetrics } from '../../api/queries/processor-metrics';
|
||||
import { useTopErrors, useAppSettings } from '../../api/queries/dashboard';
|
||||
import type { TopError } from '../../api/queries/dashboard';
|
||||
import { useDiagramByRoute } from '../../api/queries/diagrams';
|
||||
import { ProcessDiagram } from '../../components/ProcessDiagram';
|
||||
import {
|
||||
formatRelativeTime,
|
||||
trendArrow,
|
||||
formatThroughput,
|
||||
formatSlaCompliance,
|
||||
trendIndicator,
|
||||
} from './dashboard-utils';
|
||||
import styles from './DashboardTab.module.css';
|
||||
|
||||
// ── Row types ───────────────────────────────────────────────────────────────
|
||||
|
||||
interface ProcessorRow {
|
||||
id: string;
|
||||
processorId: string;
|
||||
processorType: string;
|
||||
totalCount: number;
|
||||
avgDurationMs: number;
|
||||
p99DurationMs: number;
|
||||
errorRate: number;
|
||||
pctTime: number;
|
||||
}
|
||||
|
||||
interface ErrorRow extends TopError {
|
||||
id: string;
|
||||
}
|
||||
|
||||
// ── Processor table columns ─────────────────────────────────────────────────
|
||||
|
||||
const PROCESSOR_COLUMNS: Column<ProcessorRow>[] = [
|
||||
{
|
||||
key: 'processorId',
|
||||
header: 'Processor ID',
|
||||
sortable: true,
|
||||
render: (_, row) => <MonoText size="sm">{row.processorId}</MonoText>,
|
||||
},
|
||||
{
|
||||
key: 'processorType',
|
||||
header: 'Type',
|
||||
sortable: true,
|
||||
render: (_, row) => <Badge label={row.processorType} color="muted" />,
|
||||
},
|
||||
{
|
||||
key: 'totalCount',
|
||||
header: 'Invocations',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{row.totalCount.toLocaleString()}</MonoText>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'avgDurationMs',
|
||||
header: 'Avg(ms)',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{Math.round(row.avgDurationMs)}</MonoText>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'p99DurationMs',
|
||||
header: 'P99(ms)',
|
||||
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)}</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(2)}%</MonoText>;
|
||||
},
|
||||
},
|
||||
{
|
||||
key: 'pctTime',
|
||||
header: '% Time',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{row.pctTime.toFixed(1)}%</MonoText>
|
||||
),
|
||||
},
|
||||
];
|
||||
|
||||
// ── Error table columns ─────────────────────────────────────────────────────
|
||||
|
||||
const ERROR_COLUMNS: Column<ErrorRow>[] = [
|
||||
{
|
||||
key: 'errorType',
|
||||
header: 'Error Type',
|
||||
sortable: true,
|
||||
render: (_, row) => <MonoText size="sm">{row.errorType}</MonoText>,
|
||||
},
|
||||
{
|
||||
key: 'processorId',
|
||||
header: 'Processor',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{row.processorId ?? '\u2014'}</MonoText>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'count',
|
||||
header: 'Count',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<MonoText size="sm">{row.count.toLocaleString()}</MonoText>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'trend',
|
||||
header: 'Velocity',
|
||||
render: (_, row) => (
|
||||
<span>{trendArrow(row.trend)} {row.trend}</span>
|
||||
),
|
||||
},
|
||||
{
|
||||
key: 'lastSeen',
|
||||
header: 'Last Seen',
|
||||
sortable: true,
|
||||
render: (_, row) => (
|
||||
<span>{formatRelativeTime(row.lastSeen)}</span>
|
||||
),
|
||||
},
|
||||
];
|
||||
|
||||
// ── Build KPI items ─────────────────────────────────────────────────────────
|
||||
|
||||
function buildKpiItems(
|
||||
stats: {
|
||||
totalCount: number;
|
||||
failedCount: number;
|
||||
avgDurationMs: number;
|
||||
p99LatencyMs: number;
|
||||
activeCount: number;
|
||||
prevTotalCount: number;
|
||||
prevFailedCount: number;
|
||||
prevP99LatencyMs: number;
|
||||
} | undefined,
|
||||
slaThresholdMs: number,
|
||||
bottleneck: { processorId: string; avgMs: number; pct: number } | null,
|
||||
throughputSparkline: number[],
|
||||
windowSeconds: number,
|
||||
): KpiItem[] {
|
||||
const totalCount = stats?.totalCount ?? 0;
|
||||
const failedCount = stats?.failedCount ?? 0;
|
||||
const prevTotalCount = stats?.prevTotalCount ?? 0;
|
||||
const p99Ms = stats?.p99LatencyMs ?? 0;
|
||||
const avgMs = stats?.avgDurationMs ?? 0;
|
||||
|
||||
const successRate = totalCount > 0 ? ((totalCount - failedCount) / totalCount) * 100 : 100;
|
||||
const slaCompliance = totalCount > 0
|
||||
? ((totalCount - failedCount) / totalCount) * 100
|
||||
: 100;
|
||||
|
||||
const throughputTrend = trendIndicator(totalCount, prevTotalCount);
|
||||
|
||||
return [
|
||||
{
|
||||
label: 'Throughput',
|
||||
value: formatThroughput(totalCount, windowSeconds),
|
||||
trend: {
|
||||
label: throughputTrend.label,
|
||||
variant: throughputTrend.direction === 'up' ? 'success' as const : throughputTrend.direction === 'down' ? 'error' as const : 'muted' as const,
|
||||
},
|
||||
subtitle: `${totalCount.toLocaleString()} total exchanges`,
|
||||
sparkline: throughputSparkline,
|
||||
borderColor: 'var(--amber)',
|
||||
},
|
||||
{
|
||||
label: 'Success Rate',
|
||||
value: `${successRate.toFixed(2)}%`,
|
||||
trend: {
|
||||
label: failedCount > 0 ? `${failedCount} failed` : 'No errors',
|
||||
variant: successRate >= 99 ? 'success' as const : successRate >= 97 ? 'warning' as const : 'error' as const,
|
||||
},
|
||||
subtitle: `${totalCount - failedCount} succeeded / ${totalCount.toLocaleString()} total`,
|
||||
borderColor: successRate >= 99 ? 'var(--success)' : 'var(--error)',
|
||||
},
|
||||
{
|
||||
label: 'P99 Latency',
|
||||
value: `${Math.round(p99Ms)}ms`,
|
||||
trend: {
|
||||
label: p99Ms > slaThresholdMs ? 'BREACH' : 'OK',
|
||||
variant: p99Ms > slaThresholdMs ? 'error' as const : 'success' as const,
|
||||
},
|
||||
subtitle: `SLA threshold: ${slaThresholdMs}ms \u00B7 Avg: ${Math.round(avgMs)}ms`,
|
||||
borderColor: p99Ms > slaThresholdMs ? 'var(--warning)' : 'var(--success)',
|
||||
},
|
||||
{
|
||||
label: 'SLA Compliance',
|
||||
value: formatSlaCompliance(slaCompliance),
|
||||
trend: {
|
||||
label: slaCompliance >= 99.9 ? 'Excellent' : slaCompliance >= 99 ? 'Good' : 'Degraded',
|
||||
variant: slaCompliance >= 99 ? 'success' as const : slaCompliance >= 95 ? 'warning' as const : 'error' as const,
|
||||
},
|
||||
subtitle: `Target: 99.9%`,
|
||||
borderColor: slaCompliance >= 99 ? 'var(--success)' : 'var(--warning)',
|
||||
},
|
||||
{
|
||||
label: 'Bottleneck',
|
||||
value: bottleneck ? `${Math.round(bottleneck.avgMs)}ms` : '\u2014',
|
||||
trend: {
|
||||
label: bottleneck ? `${bottleneck.pct.toFixed(1)}% of total` : '\u2014',
|
||||
variant: bottleneck && bottleneck.pct > 50 ? 'error' as const : 'muted' as const,
|
||||
},
|
||||
subtitle: bottleneck
|
||||
? `${bottleneck.processorId} \u00B7 ${Math.round(bottleneck.avgMs)}ms \u00B7 ${bottleneck.pct.toFixed(1)}% of total`
|
||||
: 'No processor data',
|
||||
borderColor: 'var(--running)',
|
||||
},
|
||||
];
|
||||
}
|
||||
|
||||
// ── Component ───────────────────────────────────────────────────────────────
|
||||
|
||||
export default function DashboardL3() {
|
||||
const { appId, routeId } = useParams<{ appId: string; routeId: string }>();
|
||||
const { timeRange } = useGlobalFilters();
|
||||
const timeFrom = timeRange.start.toISOString();
|
||||
const timeTo = timeRange.end.toISOString();
|
||||
const windowSeconds = (timeRange.end.getTime() - timeRange.start.getTime()) / 1000;
|
||||
|
||||
// ── Data hooks ──────────────────────────────────────────────────────────
|
||||
const { data: stats } = useExecutionStats(timeFrom, timeTo, routeId, appId);
|
||||
const { data: timeseries } = useStatsTimeseries(timeFrom, timeTo, routeId, appId);
|
||||
const { data: processorMetrics } = useProcessorMetrics(routeId ?? null, appId);
|
||||
const { data: topErrors } = useTopErrors(timeFrom, timeTo, appId, routeId);
|
||||
const { data: diagramLayout } = useDiagramByRoute(appId, routeId);
|
||||
const { data: appSettings } = useAppSettings(appId);
|
||||
|
||||
const slaThresholdMs = appSettings?.slaThresholdMs ?? 300;
|
||||
|
||||
// ── Bottleneck (processor with highest avgDurationMs) ───────────────────
|
||||
const bottleneck = useMemo(() => {
|
||||
if (!processorMetrics?.length) return null;
|
||||
const routeAvg = stats?.avgDurationMs ?? 0;
|
||||
const sorted = [...processorMetrics].sort(
|
||||
(a: any, b: any) => b.avgDurationMs - a.avgDurationMs,
|
||||
);
|
||||
const top = sorted[0];
|
||||
const pct = routeAvg > 0 ? (top.avgDurationMs / routeAvg) * 100 : 0;
|
||||
return { processorId: top.processorId, avgMs: top.avgDurationMs, pct };
|
||||
}, [processorMetrics, stats]);
|
||||
|
||||
// ── Sparklines from timeseries ──────────────────────────────────────────
|
||||
const throughputSparkline = useMemo(
|
||||
() => (timeseries?.buckets || []).map((b: any) => b.totalCount),
|
||||
[timeseries],
|
||||
);
|
||||
|
||||
// ── KPI strip ───────────────────────────────────────────────────────────
|
||||
const kpiItems = useMemo(
|
||||
() => buildKpiItems(stats, slaThresholdMs, bottleneck, throughputSparkline, windowSeconds),
|
||||
[stats, slaThresholdMs, bottleneck, throughputSparkline, windowSeconds],
|
||||
);
|
||||
|
||||
// ── Chart series ────────────────────────────────────────────────────────
|
||||
const throughputChartSeries = useMemo(() => [{
|
||||
label: 'Throughput',
|
||||
data: (timeseries?.buckets || []).map((b: any, i: number) => ({
|
||||
x: i,
|
||||
y: b.totalCount,
|
||||
})),
|
||||
}], [timeseries]);
|
||||
|
||||
const latencyChartSeries = useMemo(() => [{
|
||||
label: 'P99',
|
||||
data: (timeseries?.buckets || []).map((b: any, i: number) => ({
|
||||
x: i,
|
||||
y: b.p99DurationMs,
|
||||
})),
|
||||
}], [timeseries]);
|
||||
|
||||
const errorRateChartSeries = useMemo(() => [{
|
||||
label: 'Error Rate',
|
||||
data: (timeseries?.buckets || []).map((b: any, i: number) => ({
|
||||
x: i,
|
||||
y: b.totalCount > 0 ? (b.failedCount / b.totalCount) * 100 : 0,
|
||||
})),
|
||||
color: 'var(--error)',
|
||||
}], [timeseries]);
|
||||
|
||||
// ── Processor table rows ────────────────────────────────────────────────
|
||||
const processorRows: ProcessorRow[] = useMemo(() => {
|
||||
if (!processorMetrics?.length) return [];
|
||||
const routeAvg = stats?.avgDurationMs ?? 0;
|
||||
return processorMetrics.map((m: any) => ({
|
||||
id: m.processorId,
|
||||
processorId: m.processorId,
|
||||
processorType: m.processorType,
|
||||
totalCount: m.totalCount,
|
||||
avgDurationMs: m.avgDurationMs,
|
||||
p99DurationMs: m.p99DurationMs,
|
||||
errorRate: m.errorRate,
|
||||
pctTime: routeAvg > 0 ? (m.avgDurationMs / routeAvg) * 100 : 0,
|
||||
}));
|
||||
}, [processorMetrics, stats]);
|
||||
|
||||
// ── Latency heatmap for ProcessDiagram ──────────────────────────────────
|
||||
const latencyHeatmap = useMemo(() => {
|
||||
if (!processorMetrics?.length) return new Map();
|
||||
const totalAvg = processorMetrics.reduce(
|
||||
(sum: number, m: any) => sum + m.avgDurationMs, 0,
|
||||
);
|
||||
const map = new Map<string, { avgDurationMs: number; p99DurationMs: number; pctOfRoute: number }>();
|
||||
for (const m of processorMetrics) {
|
||||
map.set(m.processorId, {
|
||||
avgDurationMs: m.avgDurationMs,
|
||||
p99DurationMs: m.p99DurationMs,
|
||||
pctOfRoute: totalAvg > 0 ? (m.avgDurationMs / totalAvg) * 100 : 0,
|
||||
});
|
||||
}
|
||||
return map;
|
||||
}, [processorMetrics]);
|
||||
|
||||
// ── Error table rows ────────────────────────────────────────────────────
|
||||
const errorRows: ErrorRow[] = useMemo(
|
||||
() => (topErrors || []).map((e, i) => ({ ...e, id: `${e.errorType}-${i}` })),
|
||||
[topErrors],
|
||||
);
|
||||
|
||||
return (
|
||||
<div className={styles.content}>
|
||||
<div className={styles.refreshIndicator}>
|
||||
<span className={styles.refreshDot} />
|
||||
<span className={styles.refreshText}>Auto-refresh: 30s</span>
|
||||
</div>
|
||||
|
||||
{/* KPI Strip */}
|
||||
<KpiStrip items={kpiItems} />
|
||||
|
||||
{/* Charts — 3 in a row */}
|
||||
{(timeseries?.buckets?.length ?? 0) > 0 && (
|
||||
<div className={styles.chartRow}>
|
||||
<Card title="Throughput">
|
||||
<AreaChart
|
||||
series={throughputChartSeries}
|
||||
yLabel="msg/s"
|
||||
height={200}
|
||||
/>
|
||||
</Card>
|
||||
|
||||
<Card title="Latency Percentiles">
|
||||
<LineChart
|
||||
series={latencyChartSeries}
|
||||
yLabel="ms"
|
||||
threshold={{ value: slaThresholdMs, label: `SLA ${slaThresholdMs}ms` }}
|
||||
height={200}
|
||||
/>
|
||||
</Card>
|
||||
|
||||
<Card title="Error Rate">
|
||||
<AreaChart
|
||||
series={errorRateChartSeries}
|
||||
yLabel="%"
|
||||
height={200}
|
||||
/>
|
||||
</Card>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Process Diagram with Latency Heatmap */}
|
||||
{appId && routeId && (
|
||||
<div className={styles.diagramSection}>
|
||||
<ProcessDiagram
|
||||
application={appId}
|
||||
routeId={routeId}
|
||||
diagramLayout={diagramLayout}
|
||||
latencyHeatmap={latencyHeatmap}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Processor Metrics Table */}
|
||||
<div className={styles.tableSection}>
|
||||
<div className={styles.tableHeader}>
|
||||
<span className={styles.tableTitle}>Processor Metrics</span>
|
||||
<div>
|
||||
<span className={styles.tableMeta}>
|
||||
{processorRows.length} processor{processorRows.length !== 1 ? 's' : ''}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
<DataTable
|
||||
columns={PROCESSOR_COLUMNS}
|
||||
data={processorRows}
|
||||
sortable
|
||||
defaultSort={{ key: 'p99DurationMs', direction: 'desc' }}
|
||||
/>
|
||||
</div>
|
||||
|
||||
{/* Top 5 Errors — hidden if empty */}
|
||||
{errorRows.length > 0 && (
|
||||
<div className={styles.errorsSection}>
|
||||
<div className={styles.tableHeader}>
|
||||
<span className={styles.tableTitle}>Top 5 Errors</span>
|
||||
<Badge label={`${errorRows.length}`} color="error" />
|
||||
</div>
|
||||
<DataTable
|
||||
columns={ERROR_COLUMNS}
|
||||
data={errorRows}
|
||||
sortable
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -2,16 +2,20 @@ import { useParams } from 'react-router';
|
||||
import { lazy, Suspense } from 'react';
|
||||
import { Spinner } from '@cameleer/design-system';
|
||||
|
||||
const RoutesMetrics = lazy(() => import('../Routes/RoutesMetrics'));
|
||||
const RouteDetail = lazy(() => import('../Routes/RouteDetail'));
|
||||
const DashboardL1 = lazy(() => import('./DashboardL1'));
|
||||
const DashboardL2 = lazy(() => import('./DashboardL2'));
|
||||
const DashboardL3 = lazy(() => import('./DashboardL3'));
|
||||
|
||||
const Fallback = <div style={{ display: 'flex', justifyContent: 'center', padding: '4rem' }}><Spinner size="lg" /></div>;
|
||||
|
||||
export default function DashboardPage() {
|
||||
const { routeId } = useParams<{ appId?: string; routeId?: string }>();
|
||||
const { appId, routeId } = useParams<{ appId?: string; routeId?: string }>();
|
||||
|
||||
if (routeId) {
|
||||
return <Suspense fallback={Fallback}><RouteDetail /></Suspense>;
|
||||
if (routeId && appId) {
|
||||
return <Suspense fallback={Fallback}><DashboardL3 /></Suspense>;
|
||||
}
|
||||
return <Suspense fallback={Fallback}><RoutesMetrics /></Suspense>;
|
||||
if (appId) {
|
||||
return <Suspense fallback={Fallback}><DashboardL2 /></Suspense>;
|
||||
}
|
||||
return <Suspense fallback={Fallback}><DashboardL1 /></Suspense>;
|
||||
}
|
||||
|
||||
133
ui/src/pages/DashboardTab/DashboardTab.module.css
Normal file
133
ui/src/pages/DashboardTab/DashboardTab.module.css
Normal file
@@ -0,0 +1,133 @@
|
||||
.content {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 20px;
|
||||
}
|
||||
|
||||
.refreshIndicator {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 6px;
|
||||
justify-content: flex-end;
|
||||
}
|
||||
|
||||
.refreshDot {
|
||||
width: 7px;
|
||||
height: 7px;
|
||||
border-radius: 50%;
|
||||
background: var(--success);
|
||||
box-shadow: 0 0 4px rgba(61, 124, 71, 0.5);
|
||||
animation: pulse 2s ease-in-out infinite;
|
||||
}
|
||||
|
||||
@keyframes pulse {
|
||||
0%, 100% { opacity: 1; }
|
||||
50% { opacity: 0.5; }
|
||||
}
|
||||
|
||||
.refreshText {
|
||||
font-size: 11px;
|
||||
color: var(--text-muted);
|
||||
font-family: var(--font-mono);
|
||||
}
|
||||
|
||||
/* Tables */
|
||||
.tableSection {
|
||||
background: var(--bg-surface);
|
||||
border: 1px solid var(--border-subtle);
|
||||
border-radius: var(--radius-lg);
|
||||
box-shadow: var(--shadow-card);
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.tableHeader {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
padding: 12px 16px;
|
||||
border-bottom: 1px solid var(--border-subtle);
|
||||
}
|
||||
|
||||
.tableTitle {
|
||||
font-size: 13px;
|
||||
font-weight: 600;
|
||||
color: var(--text-primary);
|
||||
}
|
||||
|
||||
.tableMeta {
|
||||
font-size: 11px;
|
||||
color: var(--text-muted);
|
||||
font-family: var(--font-mono);
|
||||
}
|
||||
|
||||
/* Charts */
|
||||
.chartGrid {
|
||||
display: grid;
|
||||
grid-template-columns: 1fr 1fr;
|
||||
gap: 16px;
|
||||
}
|
||||
|
||||
.chartRow {
|
||||
display: grid;
|
||||
grid-template-columns: 1fr 1fr 1fr;
|
||||
gap: 16px;
|
||||
}
|
||||
|
||||
/* Cells */
|
||||
.monoCell {
|
||||
font-size: 12px;
|
||||
font-family: var(--font-mono);
|
||||
color: var(--text-primary);
|
||||
}
|
||||
|
||||
.appNameCell {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 8px;
|
||||
font-size: 12px;
|
||||
font-weight: 500;
|
||||
color: var(--text-primary);
|
||||
font-family: var(--font-mono);
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.appNameCell:hover {
|
||||
text-decoration: underline;
|
||||
}
|
||||
|
||||
/* Rate coloring */
|
||||
.rateGood { color: var(--success); }
|
||||
.rateWarn { color: var(--warning); }
|
||||
.rateBad { color: var(--error); }
|
||||
.rateNeutral { color: var(--text-secondary); }
|
||||
|
||||
/* Diagram container */
|
||||
.diagramSection {
|
||||
background: var(--bg-surface);
|
||||
border: 1px solid var(--border-subtle);
|
||||
border-radius: var(--radius-lg);
|
||||
box-shadow: var(--shadow-card);
|
||||
overflow: hidden;
|
||||
height: 280px;
|
||||
}
|
||||
|
||||
/* Table right side (meta + badge) */
|
||||
.tableRight {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 10px;
|
||||
}
|
||||
|
||||
/* Chart fill */
|
||||
.chart {
|
||||
width: 100%;
|
||||
}
|
||||
|
||||
/* Errors section */
|
||||
.errorsSection {
|
||||
background: var(--bg-surface);
|
||||
border: 1px solid var(--border-subtle);
|
||||
border-radius: var(--radius-lg);
|
||||
box-shadow: var(--shadow-card);
|
||||
overflow: hidden;
|
||||
}
|
||||
70
ui/src/pages/DashboardTab/dashboard-utils.ts
Normal file
70
ui/src/pages/DashboardTab/dashboard-utils.ts
Normal file
@@ -0,0 +1,70 @@
|
||||
import type { AppSettings } from '../../api/queries/dashboard';
|
||||
|
||||
export type HealthStatus = 'success' | 'warning' | 'error';
|
||||
|
||||
const DEFAULT_SETTINGS: Pick<AppSettings, 'healthErrorWarn' | 'healthErrorCrit' | 'healthSlaWarn' | 'healthSlaCrit'> = {
|
||||
healthErrorWarn: 1.0,
|
||||
healthErrorCrit: 5.0,
|
||||
healthSlaWarn: 99.0,
|
||||
healthSlaCrit: 95.0,
|
||||
};
|
||||
|
||||
export function computeHealthDot(
|
||||
errorRate: number,
|
||||
slaCompliance: number,
|
||||
settings?: Partial<AppSettings> | null,
|
||||
): HealthStatus {
|
||||
const s = { ...DEFAULT_SETTINGS, ...settings };
|
||||
const errorPct = errorRate * 100;
|
||||
|
||||
if (errorPct > s.healthErrorCrit || slaCompliance < s.healthSlaCrit) return 'error';
|
||||
if (errorPct > s.healthErrorWarn || slaCompliance < s.healthSlaWarn) return 'warning';
|
||||
return 'success';
|
||||
}
|
||||
|
||||
export function formatThroughput(count: number, windowSeconds: number): string {
|
||||
if (windowSeconds <= 0) return '0/s';
|
||||
const tps = count / windowSeconds;
|
||||
if (tps >= 1000) return `${(tps / 1000).toFixed(1)}k/s`;
|
||||
if (tps >= 1) return `${tps.toFixed(0)}/s`;
|
||||
return `${tps.toFixed(2)}/s`;
|
||||
}
|
||||
|
||||
export function formatSlaCompliance(pct: number): string {
|
||||
if (pct < 0) return '—';
|
||||
return `${pct.toFixed(1)}%`;
|
||||
}
|
||||
|
||||
export function trendIndicator(current: number, previous: number): { label: string; direction: 'up' | 'down' | 'flat' } {
|
||||
if (previous === 0) return { label: '—', direction: 'flat' };
|
||||
const delta = ((current - previous) / previous) * 100;
|
||||
if (Math.abs(delta) < 0.5) return { label: '—', direction: 'flat' };
|
||||
return {
|
||||
label: `${delta > 0 ? '+' : ''}${delta.toFixed(1)}%`,
|
||||
direction: delta > 0 ? 'up' : 'down',
|
||||
};
|
||||
}
|
||||
|
||||
export function trendArrow(trend: 'accelerating' | 'stable' | 'decelerating'): string {
|
||||
switch (trend) {
|
||||
case 'accelerating': return '\u25B2';
|
||||
case 'decelerating': return '\u25BC';
|
||||
default: return '\u2500\u2500';
|
||||
}
|
||||
}
|
||||
|
||||
export function formatDuration(ms: number): string {
|
||||
if (ms < 1) return '<1ms';
|
||||
if (ms < 1000) return `${Math.round(ms)}ms`;
|
||||
return `${(ms / 1000).toFixed(2)}s`;
|
||||
}
|
||||
|
||||
export function formatRelativeTime(isoString: string): string {
|
||||
const diff = Date.now() - new Date(isoString).getTime();
|
||||
const minutes = Math.floor(diff / 60_000);
|
||||
if (minutes < 1) return 'just now';
|
||||
if (minutes < 60) return `${minutes} min ago`;
|
||||
const hours = Math.floor(minutes / 60);
|
||||
if (hours < 24) return `${hours} hr ago`;
|
||||
return `${Math.floor(hours / 24)} d ago`;
|
||||
}
|
||||
Reference in New Issue
Block a user