feat: initial release of headlamp-intel-gpu-plugin v0.1.0

Adds a Headlamp plugin for Intel GPU device plugin visibility:

- Dedicated sidebar section: Overview, Device Plugins, GPU Nodes, GPU Pods
- Native Node detail page injection: GPU capacity, allocatable, utilization, active pods
- Native Pod detail page injection: per-container GPU resource requests/limits
- Native Nodes table: GPU Type and GPU Devices columns
- App bar health badge (hidden when plugin not installed)
- GpuDevicePlugin CRD monitoring (deviceplugin.intel.com/v1) with graceful
  degradation when CRD is not present
- Supports discrete (i915), Xe, and integrated GPU nodes via node labels
- 48 unit tests, TypeScript clean, 28 kB production bundle

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:
2026-02-18 17:58:49 -05:00
commit 41bf2aead4
18 changed files with 21053 additions and 0 deletions
+230
View File
@@ -0,0 +1,230 @@
/**
* IntelGpuDataContext — shared data provider for Intel GPU device plugin resources.
*
* Wraps K8s hook calls and ApiProxy requests, providing filtered Intel GPU
* resources to all child pages through React context, avoiding prop drilling
* and duplicate API calls.
*/
import { ApiProxy, K8s } from '@kinvolk/headlamp-plugin/lib';
import React, { createContext, useCallback, useContext, useEffect, useMemo, useState } from 'react';
import {
filterGpuRequestingPods,
filterIntelGpuNodes,
filterIntelGpuPluginPods,
GpuDevicePlugin,
INTEL_DEVICE_PLUGIN_API_GROUP,
INTEL_DEVICE_PLUGIN_API_VERSION,
IntelGpuNode,
IntelGpuPod,
isGpuDevicePlugin,
isKubeList,
} from './k8s';
// ---------------------------------------------------------------------------
// Context shape
// ---------------------------------------------------------------------------
export interface IntelGpuContextValue {
/** GpuDevicePlugin CRD instances — one per GPU type/config */
devicePlugins: GpuDevicePlugin[];
/** True if at least one GpuDevicePlugin CR exists */
pluginInstalled: boolean;
/** Nodes that have Intel GPU resources or labels */
gpuNodes: IntelGpuNode[];
/** Pods requesting Intel GPU resources */
gpuPods: IntelGpuPod[];
/** Intel GPU device plugin daemon pods */
pluginPods: IntelGpuPod[];
/** True if the GpuDevicePlugin CRD is available on the cluster */
crdAvailable: boolean;
/** Loading / error state */
loading: boolean;
error: string | null;
/** Manual refresh trigger */
refresh: () => void;
}
// ---------------------------------------------------------------------------
// Context
// ---------------------------------------------------------------------------
const IntelGpuContext = createContext<IntelGpuContextValue | null>(null);
export function useIntelGpuContext(): IntelGpuContextValue {
const ctx = useContext(IntelGpuContext);
if (!ctx) {
throw new Error('useIntelGpuContext must be used within an IntelGpuDataProvider');
}
return ctx;
}
// ---------------------------------------------------------------------------
// Provider
// ---------------------------------------------------------------------------
export function IntelGpuDataProvider({ children }: { children: React.ReactNode }) {
// K8s resource hooks — headlamp re-fetches on cluster context changes
const [allNodes, nodeError] = K8s.ResourceClasses.Node.useList();
const [allPods, podError] = K8s.ResourceClasses.Pod.useList({ namespace: '' });
// Async state for CRD resources
const [devicePlugins, setDevicePlugins] = useState<GpuDevicePlugin[]>([]);
const [pluginPods, setPluginPods] = useState<IntelGpuPod[]>([]);
const [crdAvailable, setCrdAvailable] = useState(false);
const [asyncLoading, setAsyncLoading] = useState(true);
const [asyncError, setAsyncError] = useState<string | null>(null);
const [refreshKey, setRefreshKey] = useState(0);
const refresh = useCallback(() => {
setRefreshKey(k => k + 1);
}, []);
useEffect(() => {
let cancelled = false;
async function fetchAsync() {
setAsyncLoading(true);
setAsyncError(null);
try {
// GpuDevicePlugin CRDs — graceful degradation if CRD not installed
try {
const pluginList = await ApiProxy.request(
`/apis/${INTEL_DEVICE_PLUGIN_API_GROUP}/${INTEL_DEVICE_PLUGIN_API_VERSION}/gpudeviceplugins`
);
if (!cancelled && isKubeList(pluginList)) {
setCrdAvailable(true);
setDevicePlugins(pluginList.items.filter(isGpuDevicePlugin));
}
} catch {
if (!cancelled) {
setCrdAvailable(false);
setDevicePlugins([]);
}
}
// Intel GPU plugin DaemonSet pods — look across all namespaces
// The device plugin is commonly deployed in kube-system but may vary
const pluginPodSelectors = [
// Intel device plugins operator deployment
`/api/v1/pods?labelSelector=${encodeURIComponent('app=intel-gpu-plugin')}`,
// Alternative: by component label
`/api/v1/pods?labelSelector=${encodeURIComponent('app.kubernetes.io/name=intel-gpu-plugin')}`,
// Intel device plugins from inteldeviceplugins-system namespace
`/api/v1/namespaces/inteldeviceplugins-system/pods`,
];
const foundPluginPods: IntelGpuPod[] = [];
for (const url of pluginPodSelectors) {
try {
const list = await ApiProxy.request(url);
if (!cancelled && isKubeList(list)) {
const gpuPluinPods = filterIntelGpuPluginPods(list.items);
foundPluginPods.push(...gpuPluinPods);
}
} catch {
// Silently ignore — some selectors may not match
}
}
// Deduplicate by pod UID
const seen = new Set<string>();
const uniquePluginPods = foundPluginPods.filter(p => {
const uid = p.metadata.uid;
if (!uid || seen.has(uid)) return false;
seen.add(uid);
return true;
});
if (!cancelled) setPluginPods(uniquePluginPods);
} catch (err: unknown) {
if (!cancelled) {
setAsyncError(err instanceof Error ? err.message : String(err));
}
} finally {
if (!cancelled) setAsyncLoading(false);
}
}
void fetchAsync();
return () => { cancelled = true; };
}, [refreshKey]);
// ---------------------------------------------------------------------------
// Derived / filtered values — memoized to avoid recomputation on every render
//
// Headlamp useList() returns KubeObject class instances that store raw
// Kubernetes JSON under `.jsonData`. Extract jsonData so our plain-object
// type helpers work correctly.
// ---------------------------------------------------------------------------
const extractJsonData = (items: unknown[]): unknown[] =>
items.map(item =>
item && typeof item === 'object' && 'jsonData' in item
? (item as { jsonData: unknown }).jsonData
: item
);
const gpuNodes = useMemo(() => {
if (!allNodes) return [];
return filterIntelGpuNodes(extractJsonData(allNodes as unknown[]));
}, [allNodes]);
const gpuPods = useMemo(() => {
if (!allPods) return [];
return filterGpuRequestingPods(extractJsonData(allPods as unknown[]));
}, [allPods]);
// ---------------------------------------------------------------------------
// Combined loading / error state
// ---------------------------------------------------------------------------
const loading = asyncLoading || !allNodes || !allPods;
const errors: string[] = [];
if (nodeError) errors.push(String(nodeError));
if (podError) errors.push(String(podError));
if (asyncError) errors.push(asyncError);
const error = errors.length > 0 ? errors.join('; ') : null;
const pluginInstalled = devicePlugins.length > 0 || pluginPods.length > 0;
// ---------------------------------------------------------------------------
// Memoized context value
// ---------------------------------------------------------------------------
const value = useMemo<IntelGpuContextValue>(
() => ({
devicePlugins,
pluginInstalled,
gpuNodes,
gpuPods,
pluginPods,
crdAvailable,
loading,
error,
refresh,
}),
[
devicePlugins,
pluginInstalled,
gpuNodes,
gpuPods,
pluginPods,
crdAvailable,
loading,
error,
refresh,
]
);
return <IntelGpuContext.Provider value={value}>{children}</IntelGpuContext.Provider>;
}
+477
View File
@@ -0,0 +1,477 @@
/**
* Unit tests for Intel GPU k8s helper functions.
*/
import { describe, expect, it } from 'vitest';
import {
filterGpuRequestingPods,
filterIntelGpuNodes,
formatAge,
formatGpuResourceName,
formatGpuType,
getNodeGpuCount,
getNodeGpuType,
getPodGpuRequests,
INTEL_GPU_NODE_LABEL,
INTEL_GPU_RESOURCE,
INTEL_GPU_XE_RESOURCE,
isGpuRequestingPod,
isIntelGpuNode,
isKubeList,
isNodeReady,
pluginStatusText,
pluginStatusToStatus,
type GpuDevicePlugin,
type IntelGpuNode,
type IntelGpuPod,
} from './k8s';
// ---------------------------------------------------------------------------
// Test helpers
// ---------------------------------------------------------------------------
function makeNode(overrides: Record<string, unknown> = {}): IntelGpuNode {
return {
apiVersion: 'v1',
kind: 'Node',
metadata: { name: 'test-node' },
status: {},
...overrides,
};
}
function makeGpuNode(type: 'discrete' | 'integrated' | 'generic' = 'discrete'): IntelGpuNode {
const labels: Record<string, string> = {};
if (type === 'discrete') labels['node-role.kubernetes.io/gpu'] = 'true';
if (type === 'integrated') labels['node-role.kubernetes.io/igpu'] = 'true';
if (type === 'generic') labels[INTEL_GPU_NODE_LABEL] = 'true';
return {
apiVersion: 'v1',
kind: 'Node',
metadata: { name: 'gpu-node', labels },
status: {
capacity: { [INTEL_GPU_RESOURCE]: '2' },
allocatable: { [INTEL_GPU_RESOURCE]: '2' },
conditions: [{ type: 'Ready', status: 'True' }],
},
};
}
function makeGpuPod(gpuResourceKey: string = INTEL_GPU_RESOURCE, amount = '1'): IntelGpuPod {
return {
apiVersion: 'v1',
kind: 'Pod',
metadata: { name: 'gpu-pod', namespace: 'default' },
spec: {
nodeName: 'gpu-node',
containers: [
{
name: 'workload',
resources: {
requests: { [gpuResourceKey]: amount },
limits: { [gpuResourceKey]: amount },
},
},
],
},
status: { phase: 'Running' },
};
}
// ---------------------------------------------------------------------------
// isIntelGpuNode
// ---------------------------------------------------------------------------
describe('isIntelGpuNode', () => {
it('returns true for nodes with discrete GPU label', () => {
const node = makeGpuNode('discrete');
expect(isIntelGpuNode(node)).toBe(true);
});
it('returns true for nodes with integrated GPU label', () => {
const node = makeGpuNode('integrated');
expect(isIntelGpuNode(node)).toBe(true);
});
it('returns true for nodes with generic Intel GPU label', () => {
const node = makeGpuNode('generic');
expect(isIntelGpuNode(node)).toBe(true);
});
it('returns true for nodes with gpu.intel.com/* in capacity', () => {
const node = makeNode({
status: { capacity: { 'gpu.intel.com/i915': '1' } },
});
expect(isIntelGpuNode(node)).toBe(true);
});
it('returns false for nodes with no GPU labels or resources', () => {
const node = makeNode({
metadata: { name: 'regular-node', labels: {} },
status: { capacity: { cpu: '8', memory: '16Gi' } },
});
expect(isIntelGpuNode(node)).toBe(false);
});
it('returns false for null/undefined', () => {
expect(isIntelGpuNode(null)).toBe(false);
expect(isIntelGpuNode(undefined)).toBe(false);
});
});
// ---------------------------------------------------------------------------
// filterIntelGpuNodes
// ---------------------------------------------------------------------------
describe('filterIntelGpuNodes', () => {
it('filters out non-GPU nodes', () => {
const gpuNode = makeGpuNode('discrete');
const regularNode = makeNode({ metadata: { name: 'regular' } });
const result = filterIntelGpuNodes([gpuNode, regularNode]);
expect(result).toHaveLength(1);
expect(result[0].metadata.name).toBe('gpu-node');
});
it('handles empty array', () => {
expect(filterIntelGpuNodes([])).toHaveLength(0);
});
});
// ---------------------------------------------------------------------------
// getNodeGpuType
// ---------------------------------------------------------------------------
describe('getNodeGpuType', () => {
it('returns discrete for GPU node role label', () => {
expect(getNodeGpuType(makeGpuNode('discrete'))).toBe('discrete');
});
it('returns integrated for iGPU node role label', () => {
expect(getNodeGpuType(makeGpuNode('integrated'))).toBe('integrated');
});
it('returns unknown for generic Intel GPU label', () => {
expect(getNodeGpuType(makeGpuNode('generic'))).toBe('unknown');
});
it('returns unknown for nodes with no labels', () => {
const node = makeNode({ status: { capacity: { [INTEL_GPU_RESOURCE]: '1' } } });
expect(getNodeGpuType(node)).toBe('unknown');
});
});
// ---------------------------------------------------------------------------
// getNodeGpuCount
// ---------------------------------------------------------------------------
describe('getNodeGpuCount', () => {
it('returns count from i915 resource', () => {
const node = makeNode({
status: { capacity: { [INTEL_GPU_RESOURCE]: '4' } },
});
expect(getNodeGpuCount(node)).toBe(4);
});
it('returns count from xe resource', () => {
const node = makeNode({
status: { capacity: { [INTEL_GPU_XE_RESOURCE]: '2' } },
});
expect(getNodeGpuCount(node)).toBe(2);
});
it('returns sum of i915 and xe resources', () => {
const node = makeNode({
status: {
capacity: {
[INTEL_GPU_RESOURCE]: '2',
[INTEL_GPU_XE_RESOURCE]: '1',
},
},
});
expect(getNodeGpuCount(node)).toBe(3);
});
it('returns 0 for nodes with no GPU capacity', () => {
const node = makeNode({ status: { capacity: { cpu: '8' } } });
expect(getNodeGpuCount(node)).toBe(0);
});
});
// ---------------------------------------------------------------------------
// isNodeReady
// ---------------------------------------------------------------------------
describe('isNodeReady', () => {
it('returns true when Ready condition is True', () => {
const node = makeNode({
status: { conditions: [{ type: 'Ready', status: 'True' }] },
});
expect(isNodeReady(node)).toBe(true);
});
it('returns false when Ready condition is False', () => {
const node = makeNode({
status: { conditions: [{ type: 'Ready', status: 'False' }] },
});
expect(isNodeReady(node)).toBe(false);
});
it('returns false when no conditions', () => {
const node = makeNode({ status: {} });
expect(isNodeReady(node)).toBe(false);
});
});
// ---------------------------------------------------------------------------
// isGpuRequestingPod
// ---------------------------------------------------------------------------
describe('isGpuRequestingPod', () => {
it('returns true for pods requesting i915 GPU', () => {
expect(isGpuRequestingPod(makeGpuPod(INTEL_GPU_RESOURCE))).toBe(true);
});
it('returns true for pods requesting xe GPU', () => {
expect(isGpuRequestingPod(makeGpuPod(INTEL_GPU_XE_RESOURCE))).toBe(true);
});
it('returns true for pods requesting millicores', () => {
expect(isGpuRequestingPod(makeGpuPod('gpu.intel.com/millicores', '500'))).toBe(true);
});
it('returns false for pods with no GPU resources', () => {
const pod: IntelGpuPod = {
apiVersion: 'v1',
kind: 'Pod',
metadata: { name: 'no-gpu-pod' },
spec: {
containers: [
{
name: 'app',
resources: {
requests: { cpu: '1', memory: '1Gi' },
},
},
],
},
};
expect(isGpuRequestingPod(pod)).toBe(false);
});
it('returns false for null', () => {
expect(isGpuRequestingPod(null)).toBe(false);
});
});
// ---------------------------------------------------------------------------
// filterGpuRequestingPods
// ---------------------------------------------------------------------------
describe('filterGpuRequestingPods', () => {
it('filters out non-GPU pods', () => {
const gpuPod = makeGpuPod();
const regularPod: IntelGpuPod = {
apiVersion: 'v1',
kind: 'Pod',
metadata: { name: 'regular' },
spec: { containers: [{ name: 'app' }] },
};
const result = filterGpuRequestingPods([gpuPod, regularPod]);
expect(result).toHaveLength(1);
expect(result[0].metadata.name).toBe('gpu-pod');
});
});
// ---------------------------------------------------------------------------
// getPodGpuRequests
// ---------------------------------------------------------------------------
describe('getPodGpuRequests', () => {
it('returns GPU resource requests from containers', () => {
const pod = makeGpuPod(INTEL_GPU_RESOURCE, '2');
const requests = getPodGpuRequests(pod);
expect(requests[INTEL_GPU_RESOURCE]).toBe('2');
});
it('returns empty object for non-GPU pods', () => {
const pod: IntelGpuPod = {
apiVersion: 'v1',
kind: 'Pod',
metadata: { name: 'regular' },
spec: { containers: [{ name: 'app', resources: { requests: { cpu: '1' } } }] },
};
expect(getPodGpuRequests(pod)).toEqual({});
});
it('sums requests across multiple containers', () => {
const pod: IntelGpuPod = {
apiVersion: 'v1',
kind: 'Pod',
metadata: { name: 'multi' },
spec: {
containers: [
{ name: 'a', resources: { requests: { [INTEL_GPU_RESOURCE]: '1' } } },
{ name: 'b', resources: { requests: { [INTEL_GPU_RESOURCE]: '2' } } },
],
},
};
const requests = getPodGpuRequests(pod);
expect(requests[INTEL_GPU_RESOURCE]).toBe('3');
});
});
// ---------------------------------------------------------------------------
// isKubeList
// ---------------------------------------------------------------------------
describe('isKubeList', () => {
it('returns true for objects with items array', () => {
expect(isKubeList({ items: [] })).toBe(true);
expect(isKubeList({ items: [1, 2, 3] })).toBe(true);
});
it('returns false for objects without items', () => {
expect(isKubeList({ data: [] })).toBe(false);
expect(isKubeList(null)).toBe(false);
expect(isKubeList('string')).toBe(false);
});
});
// ---------------------------------------------------------------------------
// formatAge
// ---------------------------------------------------------------------------
describe('formatAge', () => {
it('returns unknown for undefined', () => {
expect(formatAge(undefined)).toBe('unknown');
});
it('formats seconds', () => {
const ts = new Date(Date.now() - 30 * 1000).toISOString();
expect(formatAge(ts)).toBe('30s');
});
it('formats minutes', () => {
const ts = new Date(Date.now() - 5 * 60 * 1000).toISOString();
expect(formatAge(ts)).toBe('5m');
});
it('formats hours', () => {
const ts = new Date(Date.now() - 3 * 60 * 60 * 1000).toISOString();
expect(formatAge(ts)).toBe('3h');
});
it('formats days', () => {
const ts = new Date(Date.now() - 2 * 24 * 60 * 60 * 1000).toISOString();
expect(formatAge(ts)).toBe('2d');
});
});
// ---------------------------------------------------------------------------
// formatGpuResourceName
// ---------------------------------------------------------------------------
describe('formatGpuResourceName', () => {
it('formats i915 resource', () => {
expect(formatGpuResourceName('gpu.intel.com/i915')).toBe('GPU (i915)');
});
it('formats xe resource', () => {
expect(formatGpuResourceName('gpu.intel.com/xe')).toBe('GPU (Xe)');
});
it('formats millicores resource', () => {
expect(formatGpuResourceName('gpu.intel.com/millicores')).toBe('GPU Millicores');
});
it('returns raw suffix for unknown resources', () => {
expect(formatGpuResourceName('gpu.intel.com/custom')).toBe('custom');
});
});
// ---------------------------------------------------------------------------
// formatGpuType
// ---------------------------------------------------------------------------
describe('formatGpuType', () => {
it('formats discrete', () => {
expect(formatGpuType('discrete')).toBe('Discrete');
});
it('formats integrated', () => {
expect(formatGpuType('integrated')).toBe('Integrated');
});
it('formats unknown', () => {
expect(formatGpuType('unknown')).toBe('Unknown');
});
});
// ---------------------------------------------------------------------------
// pluginStatusToStatus
// ---------------------------------------------------------------------------
describe('pluginStatusToStatus', () => {
function makePlugin(
desired: number,
ready: number,
unavailable = 0
): GpuDevicePlugin {
return {
apiVersion: 'deviceplugin.intel.com/v1',
kind: 'GpuDevicePlugin',
metadata: { name: 'test-plugin' },
spec: {},
status: {
desiredNumberScheduled: desired,
numberReady: ready,
numberUnavailable: unavailable,
},
};
}
it('returns success when all nodes ready', () => {
expect(pluginStatusToStatus(makePlugin(3, 3))).toBe('success');
});
it('returns warning when desired is 0', () => {
expect(pluginStatusToStatus(makePlugin(0, 0))).toBe('warning');
});
it('returns warning when some nodes unavailable', () => {
expect(pluginStatusToStatus(makePlugin(3, 2, 1))).toBe('warning');
});
it('returns error when ready < desired with no unavailable', () => {
expect(pluginStatusToStatus(makePlugin(3, 1))).toBe('error');
});
});
// ---------------------------------------------------------------------------
// pluginStatusText
// ---------------------------------------------------------------------------
describe('pluginStatusText', () => {
it('shows ready/desired counts', () => {
const plugin: GpuDevicePlugin = {
apiVersion: 'deviceplugin.intel.com/v1',
kind: 'GpuDevicePlugin',
metadata: { name: 'p' },
spec: {},
status: { desiredNumberScheduled: 3, numberReady: 2 },
};
expect(pluginStatusText(plugin)).toBe('2/3 ready');
});
it('shows no nodes scheduled when desired is 0', () => {
const plugin: GpuDevicePlugin = {
apiVersion: 'deviceplugin.intel.com/v1',
kind: 'GpuDevicePlugin',
metadata: { name: 'p' },
spec: {},
status: { desiredNumberScheduled: 0, numberReady: 0 },
};
expect(pluginStatusText(plugin)).toBe('No nodes scheduled');
});
});
+393
View File
@@ -0,0 +1,393 @@
/**
* Kubernetes type definitions and helper functions for Intel GPU device plugin resources.
*
* All K8s resource types are typed at the fields we actually use.
* External data from the API is validated at the boundary before use.
*/
// ---------------------------------------------------------------------------
// Intel GPU device plugin constants
// ---------------------------------------------------------------------------
/** API group for Intel device plugin CRDs */
export const INTEL_DEVICE_PLUGIN_API_GROUP = 'deviceplugin.intel.com';
export const INTEL_DEVICE_PLUGIN_API_VERSION = 'v1';
/** Kubernetes extended resource names for Intel GPU */
export const INTEL_GPU_RESOURCE = 'gpu.intel.com/i915' as const;
export const INTEL_GPU_XE_RESOURCE = 'gpu.intel.com/xe' as const;
export const INTEL_GPU_MILLICORES_RESOURCE = 'gpu.intel.com/millicores' as const;
export const INTEL_GPU_MEMORY_RESOURCE = 'gpu.intel.com/memory.max' as const;
/** All Intel GPU resource names (prefix match) */
export const INTEL_GPU_RESOURCE_PREFIX = 'gpu.intel.com/';
/** Node labels set by Intel Node Feature Discovery */
export const INTEL_GPU_NODE_LABEL = 'intel.feature.node.kubernetes.io/gpu';
export const INTEL_DISCRETE_GPU_NODE_ROLE = 'node-role.kubernetes.io/gpu';
export const INTEL_INTEGRATED_GPU_NODE_ROLE = 'node-role.kubernetes.io/igpu';
/** Label selector for Intel GPU device plugin DaemonSet pods */
export const INTEL_GPU_PLUGIN_LABEL_SELECTOR =
'app=intel-gpu-plugin';
// ---------------------------------------------------------------------------
// Generic Kubernetes object base shapes
// ---------------------------------------------------------------------------
export interface KubeObjectMeta {
name: string;
namespace?: string;
creationTimestamp?: string;
labels?: Record<string, string>;
annotations?: Record<string, string>;
uid?: string;
}
export interface KubeObject {
apiVersion?: string;
kind?: string;
metadata: KubeObjectMeta;
}
// ---------------------------------------------------------------------------
// GpuDevicePlugin CRD (deviceplugin.intel.com/v1)
// ---------------------------------------------------------------------------
export interface GpuDevicePluginSpec {
image?: string;
sharedDevNum?: number;
enableMonitoring?: boolean;
preferredAllocationPolicy?: string;
nodeSelector?: Record<string, string>;
resourceManager?: boolean;
logLevel?: number;
}
export interface GpuDevicePluginStatus {
/** Number of nodes where the plugin daemonset is scheduled */
desiredNumberScheduled?: number;
/** Number of nodes where the plugin daemonset is running and ready */
numberReady?: number;
/** Number of nodes where the plugin daemonset pod is unavailable */
numberUnavailable?: number;
/** Number of nodes where the plugin daemonset is available */
numberAvailable?: number;
}
export interface GpuDevicePlugin extends KubeObject {
spec: GpuDevicePluginSpec;
status?: GpuDevicePluginStatus;
}
export function isGpuDevicePlugin(value: unknown): value is GpuDevicePlugin {
if (!value || typeof value !== 'object') return false;
const obj = value as Record<string, unknown>;
return obj['kind'] === 'GpuDevicePlugin';
}
// ---------------------------------------------------------------------------
// Node (with GPU resource fields)
// ---------------------------------------------------------------------------
export interface NodeResources {
[key: string]: string | undefined;
}
export interface NodeStatus {
capacity?: NodeResources;
allocatable?: NodeResources;
conditions?: Array<{
type: string;
status: string;
lastHeartbeatTime?: string;
reason?: string;
message?: string;
}>;
nodeInfo?: {
kernelVersion?: string;
osImage?: string;
architecture?: string;
kubeletVersion?: string;
};
}
export interface NodeSpec {
taints?: Array<{ key: string; effect: string; value?: string }>;
unschedulable?: boolean;
}
export interface IntelGpuNode extends KubeObject {
spec?: NodeSpec;
status?: NodeStatus;
}
/** Returns true if the node has any Intel GPU resources in its capacity */
export function isIntelGpuNode(node: unknown): node is IntelGpuNode {
if (!node || typeof node !== 'object') return false;
const obj = node as Record<string, unknown>;
const meta = obj['metadata'] as Record<string, unknown> | undefined;
const labels = meta?.['labels'] as Record<string, string> | undefined;
const status = obj['status'] as Record<string, unknown> | undefined;
const capacity = status?.['capacity'] as Record<string, string> | undefined;
// Check node labels (added by Intel Node Feature Discovery)
if (labels) {
if (
labels[INTEL_GPU_NODE_LABEL] === 'true' ||
labels[INTEL_DISCRETE_GPU_NODE_ROLE] === 'true' ||
labels[INTEL_INTEGRATED_GPU_NODE_ROLE] === 'true'
) {
return true;
}
}
// Check node capacity for Intel GPU resources
if (capacity) {
for (const key of Object.keys(capacity)) {
if (key.startsWith(INTEL_GPU_RESOURCE_PREFIX)) return true;
}
}
return false;
}
export function filterIntelGpuNodes(items: unknown[]): IntelGpuNode[] {
return items.filter(isIntelGpuNode);
}
/** Get all Intel GPU resource entries from a node's capacity/allocatable */
export function getGpuResources(resources: NodeResources | undefined): Record<string, string> {
if (!resources) return {};
const gpuResources: Record<string, string> = {};
for (const [key, value] of Object.entries(resources)) {
if (key.startsWith(INTEL_GPU_RESOURCE_PREFIX) && value !== undefined) {
gpuResources[key] = value;
}
}
return gpuResources;
}
/** Get total GPU count from node capacity */
export function getNodeGpuCount(node: IntelGpuNode): number {
const capacity = node.status?.capacity ?? {};
let count = 0;
for (const [key, value] of Object.entries(capacity)) {
if ((key === INTEL_GPU_RESOURCE || key === INTEL_GPU_XE_RESOURCE) && value) {
count += parseInt(value, 10) || 0;
}
}
return count;
}
/** Determine GPU type from node labels */
export type GpuType = 'discrete' | 'integrated' | 'unknown';
export function getNodeGpuType(node: IntelGpuNode): GpuType {
const labels = node.metadata.labels ?? {};
if (labels[INTEL_DISCRETE_GPU_NODE_ROLE] === 'true') return 'discrete';
if (labels[INTEL_INTEGRATED_GPU_NODE_ROLE] === 'true') return 'integrated';
// Fallback: check for generic Intel GPU label
if (labels[INTEL_GPU_NODE_LABEL] === 'true') return 'unknown';
return 'unknown';
}
export function formatGpuType(type: GpuType): string {
switch (type) {
case 'discrete': return 'Discrete';
case 'integrated': return 'Integrated';
default: return 'Unknown';
}
}
// ---------------------------------------------------------------------------
// Pod (with GPU resource requests)
// ---------------------------------------------------------------------------
export interface ResourceRequirements {
requests?: Record<string, string>;
limits?: Record<string, string>;
}
export interface ContainerSpec {
name: string;
image?: string;
resources?: ResourceRequirements;
}
export interface ContainerStatus {
name: string;
ready: boolean;
restartCount: number;
image?: string;
state?: {
running?: { startedAt?: string };
waiting?: { reason?: string; message?: string };
terminated?: { exitCode?: number; reason?: string };
};
}
export interface PodSpec {
nodeName?: string;
containers?: ContainerSpec[];
initContainers?: ContainerSpec[];
}
export interface PodStatus {
phase?: string;
conditions?: Array<{ type: string; status: string }>;
containerStatuses?: ContainerStatus[];
}
export interface IntelGpuPod extends KubeObject {
spec?: PodSpec;
status?: PodStatus;
}
/** Returns true if any container in the pod requests Intel GPU resources */
export function isGpuRequestingPod(pod: unknown): pod is IntelGpuPod {
if (!pod || typeof pod !== 'object') return false;
const obj = pod as Record<string, unknown>;
const spec = obj['spec'] as Record<string, unknown> | undefined;
const containers = (spec?.['containers'] ?? []) as ContainerSpec[];
const initContainers = (spec?.['initContainers'] ?? []) as ContainerSpec[];
return [...containers, ...initContainers].some(c => {
const requests = c.resources?.requests ?? {};
const limits = c.resources?.limits ?? {};
return Object.keys({ ...requests, ...limits }).some(k =>
k.startsWith(INTEL_GPU_RESOURCE_PREFIX)
);
});
}
export function filterGpuRequestingPods(items: unknown[]): IntelGpuPod[] {
return items.filter(isGpuRequestingPod);
}
/** Returns true if any container in the pod requests Intel GPU resources (for plugin pods) */
export function isIntelGpuPluginPod(pod: unknown): pod is IntelGpuPod {
if (!pod || typeof pod !== 'object') return false;
const obj = pod as Record<string, unknown>;
const meta = obj['metadata'] as Record<string, unknown> | undefined;
const labels = meta?.['labels'] as Record<string, string> | undefined;
if (!labels) return false;
return labels['app'] === 'intel-gpu-plugin' ||
(labels['app.kubernetes.io/name'] === 'intel-gpu-plugin') ||
(labels['component'] === 'intel-gpu-plugin');
}
export function filterIntelGpuPluginPods(items: unknown[]): IntelGpuPod[] {
return items.filter(isIntelGpuPluginPod);
}
/** Get total GPU requests from a pod's containers */
export function getPodGpuRequests(pod: IntelGpuPod): Record<string, string> {
const totals: Record<string, number> = {};
const allContainers = [
...(pod.spec?.containers ?? []),
...(pod.spec?.initContainers ?? []),
];
for (const c of allContainers) {
const requests = c.resources?.requests ?? {};
for (const [key, value] of Object.entries(requests)) {
if (key.startsWith(INTEL_GPU_RESOURCE_PREFIX) && value) {
totals[key] = (totals[key] ?? 0) + (parseInt(value, 10) || 0);
}
}
}
return Object.fromEntries(Object.entries(totals).map(([k, v]) => [k, String(v)]));
}
export function isPodReady(pod: IntelGpuPod): boolean {
return (
pod.status?.conditions?.some(c => c.type === 'Ready' && c.status === 'True') ?? false
);
}
export function getPodRestarts(pod: IntelGpuPod): number {
return (
pod.status?.containerStatuses?.reduce((sum, c) => sum + c.restartCount, 0) ?? 0
);
}
// ---------------------------------------------------------------------------
// K8s API list response envelope
// ---------------------------------------------------------------------------
export interface KubeList<T> {
items: T[];
metadata?: { resourceVersion?: string };
}
export function isKubeList(value: unknown): value is KubeList<unknown> {
if (!value || typeof value !== 'object') return false;
return Array.isArray((value as Record<string, unknown>)['items']);
}
// ---------------------------------------------------------------------------
// Node condition helpers
// ---------------------------------------------------------------------------
export function isNodeReady(node: IntelGpuNode): boolean {
return (
node.status?.conditions?.some(c => c.type === 'Ready' && c.status === 'True') ?? false
);
}
// ---------------------------------------------------------------------------
// Utility: human-readable age
// ---------------------------------------------------------------------------
export function formatAge(timestamp: string | undefined): string {
if (!timestamp) return 'unknown';
const diffMs = Date.now() - new Date(timestamp).getTime();
const secs = Math.floor(diffMs / 1000);
if (secs < 60) return `${secs}s`;
const mins = Math.floor(secs / 60);
if (mins < 60) return `${mins}m`;
const hours = Math.floor(mins / 60);
if (hours < 24) return `${hours}h`;
const days = Math.floor(hours / 24);
return `${days}d`;
}
// ---------------------------------------------------------------------------
// Utility: GPU resource display name
// ---------------------------------------------------------------------------
export function formatGpuResourceName(resourceKey: string): string {
const name = resourceKey.replace(INTEL_GPU_RESOURCE_PREFIX, '');
const map: Record<string, string> = {
'i915': 'GPU (i915)',
'xe': 'GPU (Xe)',
'millicores': 'GPU Millicores',
'memory.max': 'GPU Memory (max)',
'tiles': 'GPU Tiles',
};
return map[name] ?? name;
}
// ---------------------------------------------------------------------------
// Status helpers
// ---------------------------------------------------------------------------
export function pluginStatusToStatus(
plugin: GpuDevicePlugin
): 'success' | 'warning' | 'error' {
const desired = plugin.status?.desiredNumberScheduled ?? 0;
const ready = plugin.status?.numberReady ?? 0;
const unavailable = plugin.status?.numberUnavailable ?? 0;
if (desired === 0) return 'warning';
if (unavailable > 0) return 'warning';
if (ready === desired) return 'success';
return 'error';
}
export function pluginStatusText(plugin: GpuDevicePlugin): string {
const desired = plugin.status?.desiredNumberScheduled ?? 0;
const ready = plugin.status?.numberReady ?? 0;
if (desired === 0) return 'No nodes scheduled';
return `${ready}/${desired} ready`;
}