feat: add Metrics page, remove app bar badge, fix sidebar label
- Add src/api/metrics.ts: Prometheus text parser + fetchGpuPluginMetrics() fetching from Intel GPU device plugin pods (port 9090). Extracts engine utilization (active/total ticks → %), boost frequency (MHz), VRAM and system memory usage, cumulative energy (µJ). - Add src/components/MetricsPage.tsx: per-card metrics display with inline utilization bars, graceful fallback when enableMonitoring is not set. - Register Metrics sidebar entry (mdi:chart-line) and route /intel-gpu/metrics. - Remove registerAppBarAction and AppBarGpuBadge (colored info bubble). - Fix sidebar parent label: 'Intel GPU' → 'intel-gpu'. - Bump to v0.2.0; update artifacthub-pkg.yml with new archive URL and checksum. Generated with [Claude Code](https://claude.ai/code) via [Happy](https://happy.engineering) Co-Authored-By: Claude <noreply@anthropic.com> Co-Authored-By: Happy <yesreply@happy.engineering>
This commit is contained in:
+13
-5
@@ -1,4 +1,4 @@
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version: "0.1.0"
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version: "0.2.0"
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name: headlamp-intel-gpu-plugin
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displayName: Intel GPU
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description: >-
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@@ -7,13 +7,15 @@ description: >-
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allocation, pods requesting Intel GPU resources, and injects Intel GPU
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sections into native Node and Pod detail pages. Supports discrete (i915),
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Xe, and integrated GPU nodes with graceful degradation when the device
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plugin operator is not installed.
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plugin operator is not installed. Includes a Metrics page showing real-time
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engine utilization, GPU frequency, VRAM usage, and energy from the device
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plugin's Prometheus endpoint.
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createdAt: "2026-02-18T00:00:00Z"
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license: Apache-2.0
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category: monitoring-logging
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homeURL: https://github.com/privilegedescalation/headlamp-intel-gpu-plugin
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appVersion: "0.1.0"
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appVersion: "0.2.0"
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keywords:
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- headlamp
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@@ -43,6 +45,12 @@ links:
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url: https://intel.github.io/intel-device-plugins-for-kubernetes/
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changes:
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- kind: added
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description: "Metrics page: real-time engine utilization, boost frequency, VRAM usage, and energy from Intel GPU device plugin Prometheus endpoint (port 9090)"
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- kind: changed
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description: "Sidebar label changed to intel-gpu"
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- kind: removed
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description: "Removed app bar health badge"
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- kind: added
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description: "Overview dashboard: plugin health, GPU node summary, allocation bar, active GPU pods"
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- kind: added
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@@ -61,7 +69,7 @@ changes:
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description: "App bar health badge: hidden when no Intel GPU plugin detected"
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annotations:
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headlamp/plugin/archive-url: "https://github.com/privilegedescalation/headlamp-intel-gpu-plugin/releases/download/v0.1.0/headlamp-intel-gpu-plugin-0.1.0.tar.gz"
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headlamp/plugin/archive-checksum: "sha256:d6a50567d0f9e537f0edadac334d6a03cd182f5b64b47264577f2213fd882687"
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headlamp/plugin/archive-url: "https://github.com/privilegedescalation/headlamp-intel-gpu-plugin/releases/download/v0.2.0/headlamp-intel-gpu-plugin-0.2.0.tar.gz"
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headlamp/plugin/archive-checksum: "sha256:404be582bd13c167f61785028eb6eb91dd621106cbe76038f2c071a576a1a442"
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headlamp/plugin/version-compat: ">=0.20.0"
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headlamp/plugin/distro-compat: "in-cluster,web,app"
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+1
-1
@@ -1,6 +1,6 @@
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{
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"name": "headlamp-intel-gpu-plugin",
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"version": "0.1.0",
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"version": "0.2.0",
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"description": "Headlamp plugin for Intel GPU device plugin visibility and monitoring",
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"repository": {
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"type": "git",
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@@ -0,0 +1,257 @@
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/**
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* Prometheus text format parser for Intel GPU device plugin metrics.
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*
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* Fetches raw metrics from the Intel GPU device plugin pod (port 9090)
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* via the Kubernetes API proxy and parses key metric families.
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*
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* Metrics exposed by intel-gpu-plugin when enableMonitoring: true:
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* gpu_i915_engine_active_ticks — engine busy ticks (per card, engine)
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* gpu_i915_engine_total_ticks — engine total ticks (for utilization %)
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* gpu_i915_energy_microjoules — cumulative energy (µJ → power = delta/dt)
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* gpu_i915_gt_boost_freq_mhz — current GT boost frequency (MHz)
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* gpu_i915_memory_local — local (VRAM) memory usage (bytes)
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* gpu_i915_memory_system — system memory usage (bytes)
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*/
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import { ApiProxy } from '@kinvolk/headlamp-plugin/lib';
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// ---------------------------------------------------------------------------
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// Types
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// ---------------------------------------------------------------------------
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export interface MetricSample {
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labels: Record<string, string>;
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value: number;
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}
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export interface MetricFamily {
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name: string;
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help: string;
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type: string;
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samples: MetricSample[];
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}
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export type ParsedMetrics = Map<string, MetricFamily>;
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export interface GpuNodeMetrics {
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/** Node name this metric set was fetched from (via plugin pod) */
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nodeName: string;
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/** Pod name of the intel-gpu-plugin daemonset pod */
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podName: string;
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/** Engine utilization per (card, engine): 0–100 */
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engineUtilization: Array<{ card: string; engine: string; pct: number }>;
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/** Current GT boost frequency in MHz per card */
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boostFreqMhz: Array<{ card: string; value: number }>;
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/** Local VRAM usage in bytes per card */
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memoryLocalBytes: Array<{ card: string; value: number }>;
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/** System memory usage in bytes per card */
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memorySystemBytes: Array<{ card: string; value: number }>;
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/** Cumulative energy in µJ per card (raw counter; compute delta for power) */
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energyMicrojoules: Array<{ card: string; value: number }>;
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/** Raw parsed metric families for advanced use */
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raw: ParsedMetrics;
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}
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// ---------------------------------------------------------------------------
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// Prometheus text format parser
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// ---------------------------------------------------------------------------
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const LABEL_PAIR_RE = /(\w+)="([^"]*)"/g;
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function parseLabels(labelStr: string): Record<string, string> {
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const labels: Record<string, string> = {};
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let match: RegExpExecArray | null;
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const re = new RegExp(LABEL_PAIR_RE.source, 'g');
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while ((match = re.exec(labelStr)) !== null) {
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const key = match[1];
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const val = match[2];
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if (key && val !== undefined) {
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labels[key] = val;
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}
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}
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return labels;
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}
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export function parsePrometheusText(text: string): ParsedMetrics {
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const families = new Map<string, MetricFamily>();
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let currentName = '';
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let currentHelp = '';
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let currentType = '';
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for (const rawLine of text.split('\n')) {
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const line = rawLine.trim();
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if (!line) continue;
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if (line.startsWith('# HELP ')) {
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const rest = line.slice(7);
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const spaceIdx = rest.indexOf(' ');
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currentName = spaceIdx >= 0 ? rest.slice(0, spaceIdx) : rest;
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currentHelp = spaceIdx >= 0 ? rest.slice(spaceIdx + 1) : '';
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continue;
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}
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if (line.startsWith('# TYPE ')) {
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const rest = line.slice(7);
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const spaceIdx = rest.indexOf(' ');
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currentType = spaceIdx >= 0 ? rest.slice(spaceIdx + 1) : '';
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continue;
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}
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if (line.startsWith('#')) continue;
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const openBrace = line.indexOf('{');
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const closeBrace = line.lastIndexOf('}');
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let metricName: string;
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let labels: Record<string, string>;
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let valuePart: string;
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if (openBrace >= 0 && closeBrace > openBrace) {
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metricName = line.slice(0, openBrace);
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labels = parseLabels(line.slice(openBrace + 1, closeBrace));
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valuePart = line.slice(closeBrace + 1).trim();
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} else {
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const spaceIdx = line.lastIndexOf(' ');
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if (spaceIdx < 0) continue;
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metricName = line.slice(0, spaceIdx);
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labels = {};
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valuePart = line.slice(spaceIdx + 1).trim();
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}
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const valueTokens = valuePart.split(' ');
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const valueStr = valueTokens[0] ?? '';
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const value = parseFloat(valueStr);
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if (!Number.isFinite(value)) continue;
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const familyKey = metricName;
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let family = families.get(familyKey);
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if (!family) {
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family = {
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name: familyKey,
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help: metricName === currentName ? currentHelp : '',
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type: metricName === currentName ? currentType : '',
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samples: [],
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};
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families.set(familyKey, family);
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}
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family.samples.push({ labels, value });
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}
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return families;
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}
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// ---------------------------------------------------------------------------
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// Extract Intel GPU metrics from the parsed map
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// ---------------------------------------------------------------------------
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function samplesFor(families: ParsedMetrics, name: string): MetricSample[] {
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return families.get(name)?.samples ?? [];
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}
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export function extractGpuNodeMetrics(
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families: ParsedMetrics,
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nodeName: string,
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podName: string
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): GpuNodeMetrics {
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const activeSamples = samplesFor(families, 'gpu_i915_engine_active_ticks');
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const totalSamples = samplesFor(families, 'gpu_i915_engine_total_ticks');
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// Build utilization: active/total per (card, engine)
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const engineUtilization: GpuNodeMetrics['engineUtilization'] = [];
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for (const active of activeSamples) {
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const card = active.labels['card'] ?? active.labels['gpu'] ?? 'gpu0';
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const engine = active.labels['engine'] ?? 'render/0';
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const totalSample = totalSamples.find(
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s =>
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(s.labels['card'] ?? s.labels['gpu']) === card &&
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s.labels['engine'] === engine
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);
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const total = totalSample?.value ?? 0;
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const pct = total > 0 ? Math.min(100, Math.round((active.value / total) * 100)) : 0;
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engineUtilization.push({ card, engine, pct });
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}
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// Boost frequency
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const boostFreqMhz = samplesFor(families, 'gpu_i915_gt_boost_freq_mhz').map(s => ({
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card: s.labels['card'] ?? s.labels['gpu'] ?? 'gpu0',
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value: s.value,
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}));
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// Memory
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const memoryLocalBytes = samplesFor(families, 'gpu_i915_memory_local').map(s => ({
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card: s.labels['card'] ?? s.labels['gpu'] ?? 'gpu0',
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value: s.value,
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}));
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const memorySystemBytes = samplesFor(families, 'gpu_i915_memory_system').map(s => ({
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card: s.labels['card'] ?? s.labels['gpu'] ?? 'gpu0',
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value: s.value,
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}));
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// Energy
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const energyMicrojoules = samplesFor(families, 'gpu_i915_energy_microjoules').map(s => ({
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card: s.labels['card'] ?? s.labels['gpu'] ?? 'gpu0',
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value: s.value,
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}));
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return {
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nodeName,
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podName,
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engineUtilization,
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boostFreqMhz,
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memoryLocalBytes,
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memorySystemBytes,
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energyMicrojoules,
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raw: families,
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};
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}
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// ---------------------------------------------------------------------------
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// Fetch metrics from an Intel GPU device plugin pod
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// ---------------------------------------------------------------------------
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/**
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* Fetches and parses Prometheus metrics from an Intel GPU device plugin pod.
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*
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* The proxy path is:
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* /api/v1/namespaces/{namespace}/pods/{podName}:9090/proxy/metrics
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*
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* Returns null if the pod is not exposing metrics (enableMonitoring: false)
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* or if the proxy request fails.
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*/
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export async function fetchGpuPluginMetrics(
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podName: string,
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namespace: string,
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nodeName: string
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): Promise<GpuNodeMetrics | null> {
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const path = `/api/v1/namespaces/${namespace}/pods/${podName}:9090/proxy/metrics`;
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try {
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const raw: unknown = await ApiProxy.request(path, {
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method: 'GET',
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isJSON: false,
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});
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if (typeof raw !== 'string') return null;
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const families = parsePrometheusText(raw);
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return extractGpuNodeMetrics(families, nodeName, podName);
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} catch {
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return null;
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}
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}
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// ---------------------------------------------------------------------------
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// Formatting helpers
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// ---------------------------------------------------------------------------
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export function formatBytes(bytes: number): string {
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if (bytes >= 1e9) return `${(bytes / 1e9).toFixed(1)} GB`;
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if (bytes >= 1e6) return `${(bytes / 1e6).toFixed(1)} MB`;
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if (bytes >= 1e3) return `${(bytes / 1e3).toFixed(1)} KB`;
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return `${bytes} B`;
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}
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export function formatFreq(mhz: number): string {
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return `${Math.round(mhz)} MHz`;
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}
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@@ -0,0 +1,311 @@
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/**
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* MetricsPage — real-time Intel GPU metrics from the device plugin pods.
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*
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* Fetches Prometheus metrics from each Intel GPU device plugin pod (port 9090)
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* and displays per-card engine utilization, GPU frequency, memory usage,
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* and cumulative energy. Requires `enableMonitoring: true` in GpuDevicePlugin.
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*/
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import {
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Loader,
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NameValueTable,
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SectionBox,
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SectionHeader,
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StatusLabel,
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} from '@kinvolk/headlamp-plugin/lib/CommonComponents';
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import React, { useCallback, useEffect, useState } from 'react';
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import { useIntelGpuContext } from '../api/IntelGpuDataContext';
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import {
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fetchGpuPluginMetrics,
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formatBytes,
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formatFreq,
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GpuNodeMetrics,
|
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} from '../api/metrics';
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import { IntelGpuPod } from '../api/k8s';
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// ---------------------------------------------------------------------------
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// Utilization bar
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// ---------------------------------------------------------------------------
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function UtilizationBar({ pct }: { pct: number }) {
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const color = pct >= 90 ? '#d32f2f' : pct >= 70 ? '#f57c00' : '#0071c5';
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return (
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<div style={{ display: 'flex', alignItems: 'center', gap: '8px' }}>
|
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<div
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style={{
|
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width: '100px',
|
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height: '8px',
|
||||
backgroundColor: '#e0e0e0',
|
||||
borderRadius: '4px',
|
||||
overflow: 'hidden',
|
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flexShrink: 0,
|
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}}
|
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>
|
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<div
|
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style={{
|
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width: `${pct}%`,
|
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height: '100%',
|
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backgroundColor: color,
|
||||
borderRadius: '4px',
|
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transition: 'width 0.3s ease',
|
||||
}}
|
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/>
|
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</div>
|
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<span style={{ fontSize: '12px', fontVariantNumeric: 'tabular-nums' }}>{pct}%</span>
|
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</div>
|
||||
);
|
||||
}
|
||||
|
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// ---------------------------------------------------------------------------
|
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// Per-node metrics card
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
function NodeMetricsCard({ metrics }: { metrics: GpuNodeMetrics }) {
|
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const { nodeName, podName, engineUtilization, boostFreqMhz, memoryLocalBytes, memorySystemBytes, energyMicrojoules } = metrics;
|
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|
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// Group engines by card
|
||||
const byCard = new Map<string, typeof engineUtilization>();
|
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for (const e of engineUtilization) {
|
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if (!byCard.has(e.card)) byCard.set(e.card, []);
|
||||
byCard.get(e.card)!.push(e);
|
||||
}
|
||||
|
||||
const freqByCard = new Map(boostFreqMhz.map(f => [f.card, f.value]));
|
||||
const memLocalByCard = new Map(memoryLocalBytes.map(m => [m.card, m.value]));
|
||||
const memSysByCard = new Map(memorySystemBytes.map(m => [m.card, m.value]));
|
||||
const energyByCard = new Map(energyMicrojoules.map(e => [e.card, e.value]));
|
||||
|
||||
const cards = Array.from(
|
||||
new Set([
|
||||
...byCard.keys(),
|
||||
...freqByCard.keys(),
|
||||
...memLocalByCard.keys(),
|
||||
])
|
||||
).sort();
|
||||
|
||||
if (cards.length === 0) {
|
||||
return (
|
||||
<SectionBox title={`${nodeName} — No Metric Data`}>
|
||||
<NameValueTable
|
||||
rows={[
|
||||
{
|
||||
name: 'Pod',
|
||||
value: podName,
|
||||
},
|
||||
{
|
||||
name: 'Note',
|
||||
value: 'No GPU metrics found. Ensure enableMonitoring: true is set in GpuDevicePlugin.',
|
||||
},
|
||||
]}
|
||||
/>
|
||||
</SectionBox>
|
||||
);
|
||||
}
|
||||
|
||||
return (
|
||||
<>
|
||||
{cards.map(card => {
|
||||
const engines = byCard.get(card) ?? [];
|
||||
const freq = freqByCard.get(card);
|
||||
const memLocal = memLocalByCard.get(card);
|
||||
const memSys = memSysByCard.get(card);
|
||||
const energy = energyByCard.get(card);
|
||||
|
||||
const rows: Array<{ name: string; value: React.ReactNode }> = [
|
||||
{ name: 'Node', value: nodeName },
|
||||
{ name: 'Plugin Pod', value: podName },
|
||||
{ name: 'GPU Card', value: card },
|
||||
];
|
||||
|
||||
if (freq !== undefined) {
|
||||
rows.push({ name: 'Boost Frequency', value: formatFreq(freq) });
|
||||
}
|
||||
|
||||
if (memLocal !== undefined) {
|
||||
rows.push({ name: 'VRAM (local)', value: formatBytes(memLocal) });
|
||||
}
|
||||
if (memSys !== undefined && memSys > 0) {
|
||||
rows.push({ name: 'System Memory', value: formatBytes(memSys) });
|
||||
}
|
||||
|
||||
if (energy !== undefined) {
|
||||
rows.push({
|
||||
name: 'Energy (cumulative)',
|
||||
value: `${(energy / 1e6).toFixed(2)} J`,
|
||||
});
|
||||
}
|
||||
|
||||
// Engine utilization rows
|
||||
for (const e of engines) {
|
||||
rows.push({
|
||||
name: `Engine: ${e.engine}`,
|
||||
value: <UtilizationBar pct={e.pct} />,
|
||||
});
|
||||
}
|
||||
|
||||
return (
|
||||
<SectionBox key={`${nodeName}-${card}`} title={`${nodeName} — ${card}`}>
|
||||
<NameValueTable rows={rows} />
|
||||
</SectionBox>
|
||||
);
|
||||
})}
|
||||
</>
|
||||
);
|
||||
}
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// Main page
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
export default function MetricsPage() {
|
||||
const { pluginPods, pluginInstalled, loading: ctxLoading } = useIntelGpuContext();
|
||||
|
||||
const [metricsMap, setMetricsMap] = useState<Map<string, GpuNodeMetrics | 'error'>>(new Map());
|
||||
const [fetching, setFetching] = useState(false);
|
||||
|
||||
const fetchAll = useCallback(async (pods: IntelGpuPod[]) => {
|
||||
if (pods.length === 0) return;
|
||||
setFetching(true);
|
||||
|
||||
const results = await Promise.all(
|
||||
pods.map(async pod => {
|
||||
const name = pod.metadata.name;
|
||||
const namespace = pod.metadata.namespace ?? 'kube-system';
|
||||
const nodeName = pod.spec?.nodeName ?? name;
|
||||
const result = await fetchGpuPluginMetrics(name, namespace, nodeName);
|
||||
return { name, result };
|
||||
})
|
||||
);
|
||||
|
||||
const map = new Map<string, GpuNodeMetrics | 'error'>();
|
||||
for (const { name, result } of results) {
|
||||
map.set(name, result ?? 'error');
|
||||
}
|
||||
setMetricsMap(map);
|
||||
setFetching(false);
|
||||
}, []);
|
||||
|
||||
useEffect(() => {
|
||||
if (!ctxLoading && pluginPods.length > 0) {
|
||||
void fetchAll(pluginPods);
|
||||
}
|
||||
}, [ctxLoading, pluginPods, fetchAll]);
|
||||
|
||||
if (ctxLoading) {
|
||||
return <Loader title="Loading Intel GPU data..." />;
|
||||
}
|
||||
|
||||
return (
|
||||
<>
|
||||
<div style={{ display: 'flex', justifyContent: 'space-between', alignItems: 'center', marginBottom: '20px' }}>
|
||||
<SectionHeader title="Intel GPU — Metrics" />
|
||||
<button
|
||||
onClick={() => void fetchAll(pluginPods)}
|
||||
disabled={fetching || pluginPods.length === 0}
|
||||
aria-label="Refresh metrics"
|
||||
style={{
|
||||
padding: '6px 16px',
|
||||
backgroundColor: 'transparent',
|
||||
color: 'var(--mui-palette-primary-main, #0071c5)',
|
||||
border: '1px solid var(--mui-palette-primary-main, #0071c5)',
|
||||
borderRadius: '4px',
|
||||
cursor: 'pointer',
|
||||
fontSize: '13px',
|
||||
fontWeight: 500,
|
||||
}}
|
||||
>
|
||||
{fetching ? 'Refreshing…' : 'Refresh'}
|
||||
</button>
|
||||
</div>
|
||||
|
||||
{!pluginInstalled && (
|
||||
<SectionBox title="Intel GPU Plugin Not Detected">
|
||||
<NameValueTable
|
||||
rows={[
|
||||
{
|
||||
name: 'Status',
|
||||
value: (
|
||||
<StatusLabel status="warning">No Intel GPU device plugin pods found</StatusLabel>
|
||||
),
|
||||
},
|
||||
{
|
||||
name: 'Note',
|
||||
value: 'Install the Intel GPU device plugin and set enableMonitoring: true to expose Prometheus metrics.',
|
||||
},
|
||||
]}
|
||||
/>
|
||||
</SectionBox>
|
||||
)}
|
||||
|
||||
{pluginInstalled && pluginPods.length === 0 && (
|
||||
<SectionBox title="No Plugin Pods Found">
|
||||
<NameValueTable
|
||||
rows={[
|
||||
{
|
||||
name: 'Status',
|
||||
value: (
|
||||
<StatusLabel status="warning">Plugin detected via CRD but no pods found</StatusLabel>
|
||||
),
|
||||
},
|
||||
]}
|
||||
/>
|
||||
</SectionBox>
|
||||
)}
|
||||
|
||||
{pluginPods.length > 0 && metricsMap.size === 0 && fetching && (
|
||||
<Loader title="Fetching GPU metrics..." />
|
||||
)}
|
||||
|
||||
{pluginPods.length > 0 && metricsMap.size === 0 && !fetching && (
|
||||
<SectionBox title="Metrics Unavailable">
|
||||
<NameValueTable
|
||||
rows={[
|
||||
{
|
||||
name: 'Status',
|
||||
value: (
|
||||
<StatusLabel status="warning">
|
||||
Could not fetch metrics from any plugin pod
|
||||
</StatusLabel>
|
||||
),
|
||||
},
|
||||
{
|
||||
name: 'Requirements',
|
||||
value: 'Set enableMonitoring: true in GpuDevicePlugin spec and ensure port 9090 is accessible via kube-apiserver proxy.',
|
||||
},
|
||||
{
|
||||
name: 'Plugin Pods Found',
|
||||
value: pluginPods.map(p => p.metadata.name).join(', '),
|
||||
},
|
||||
]}
|
||||
/>
|
||||
</SectionBox>
|
||||
)}
|
||||
|
||||
{Array.from(metricsMap.entries()).map(([podName, metrics]) => {
|
||||
if (metrics === 'error') {
|
||||
return (
|
||||
<SectionBox key={podName} title={`${podName} — Metrics Unavailable`}>
|
||||
<NameValueTable
|
||||
rows={[
|
||||
{
|
||||
name: 'Status',
|
||||
value: (
|
||||
<StatusLabel status="error">
|
||||
Failed to fetch metrics from pod
|
||||
</StatusLabel>
|
||||
),
|
||||
},
|
||||
{
|
||||
name: 'Hint',
|
||||
value: 'Ensure enableMonitoring: true is set in the GpuDevicePlugin CR and the pod is running.',
|
||||
},
|
||||
]}
|
||||
/>
|
||||
</SectionBox>
|
||||
);
|
||||
}
|
||||
return <NodeMetricsCard key={podName} metrics={metrics} />;
|
||||
})}
|
||||
</>
|
||||
);
|
||||
}
|
||||
+25
-17
@@ -1,20 +1,17 @@
|
||||
/**
|
||||
* headlamp-intel-gpu-plugin — entry point.
|
||||
*
|
||||
* Registers sidebar entries, routes, detail view sections, table column
|
||||
* processors, and app bar action for Intel GPU device plugin visibility
|
||||
* in Headlamp.
|
||||
* Registers sidebar entries, routes, detail view sections, and table column
|
||||
* processors for Intel GPU device plugin visibility in Headlamp.
|
||||
*
|
||||
* Surfaces Intel GPU information in the following places:
|
||||
* - Dedicated sidebar section: Overview / Device Plugins / Nodes / Pods
|
||||
* - Dedicated sidebar section: Overview / Device Plugins / Nodes / Pods / Metrics
|
||||
* - Native Node detail page: Intel GPU section (capacity, utilization, pods)
|
||||
* - Native Pod detail page: GPU resource requests per container
|
||||
* - Native Nodes table: GPU Type and GPU Devices columns
|
||||
* - App bar: health badge (hidden when plugin not installed)
|
||||
*/
|
||||
|
||||
import {
|
||||
registerAppBarAction,
|
||||
registerDetailsViewSection,
|
||||
registerResourceTableColumnsProcessor,
|
||||
registerRoute,
|
||||
@@ -22,9 +19,9 @@ import {
|
||||
} from '@kinvolk/headlamp-plugin/lib';
|
||||
import React from 'react';
|
||||
import { IntelGpuDataProvider } from './api/IntelGpuDataContext';
|
||||
import AppBarGpuBadge from './components/AppBarGpuBadge';
|
||||
import DevicePluginsPage from './components/DevicePluginsPage';
|
||||
import { buildNodeGpuColumns } from './components/integrations/NodeColumns';
|
||||
import MetricsPage from './components/MetricsPage';
|
||||
import NodeDetailSection from './components/NodeDetailSection';
|
||||
import NodesPage from './components/NodesPage';
|
||||
import OverviewPage from './components/OverviewPage';
|
||||
@@ -38,7 +35,7 @@ import PodsPage from './components/PodsPage';
|
||||
registerSidebarEntry({
|
||||
parent: null,
|
||||
name: 'intel-gpu',
|
||||
label: 'Intel GPU',
|
||||
label: 'intel-gpu',
|
||||
url: '/intel-gpu',
|
||||
icon: 'mdi:gpu',
|
||||
});
|
||||
@@ -75,6 +72,14 @@ registerSidebarEntry({
|
||||
icon: 'mdi:cube-outline',
|
||||
});
|
||||
|
||||
registerSidebarEntry({
|
||||
parent: 'intel-gpu',
|
||||
name: 'intel-gpu-metrics',
|
||||
label: 'Metrics',
|
||||
url: '/intel-gpu/metrics',
|
||||
icon: 'mdi:chart-line',
|
||||
});
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// Routes
|
||||
// ---------------------------------------------------------------------------
|
||||
@@ -127,6 +132,18 @@ registerRoute({
|
||||
),
|
||||
});
|
||||
|
||||
registerRoute({
|
||||
path: '/intel-gpu/metrics',
|
||||
sidebar: 'intel-gpu-metrics',
|
||||
name: 'intel-gpu-metrics',
|
||||
exact: true,
|
||||
component: () => (
|
||||
<IntelGpuDataProvider>
|
||||
<MetricsPage />
|
||||
</IntelGpuDataProvider>
|
||||
),
|
||||
});
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// Detail view section — Node pages
|
||||
// Inject Intel GPU section into native Node detail page for GPU nodes.
|
||||
@@ -164,12 +181,3 @@ registerResourceTableColumnsProcessor(({ id, columns }) => {
|
||||
return columns;
|
||||
});
|
||||
|
||||
// ---------------------------------------------------------------------------
|
||||
// App bar action — Intel GPU health badge
|
||||
// ---------------------------------------------------------------------------
|
||||
|
||||
registerAppBarAction(() => (
|
||||
<IntelGpuDataProvider>
|
||||
<AppBarGpuBadge />
|
||||
</IntelGpuDataProvider>
|
||||
));
|
||||
|
||||
Reference in New Issue
Block a user