feat(usage): add resource-usage API client, meta hook, and shared utils

The data layer the resource tabs build on:
- apis/resource.ts: adapter over the unified metered_usage read API
  (resource/gpu-instances/storage/summary/events breakdowns), flattening
  the server's generic shape into the per-tab item shape.
- hooks/use-resource-meta.ts: loads creators/instances/volumes filter
  options for the current scope.
- utils/time-buckets.ts: day/week/month/hour bucket keys + range fill.
- utils/export-breakdown.ts: derive Excel columns from antd table specs.
This commit is contained in:
michelia
2026-06-03 17:10:51 +08:00
committed by michela feng
parent 234e42ccfa
commit 2407416e33
4 changed files with 635 additions and 0 deletions
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/**
* Resource Usage API client — adapter over the unified ``metered_usage``
* read API (``/usage/{resource,gpu-instances,storage,summary,events}``).
*
* The server returns a generic ``{ key, id, metrics:{...} }`` breakdown shape
* (one engine for every tab). This module flattens it into the per-tab item
* shape the components consume, maps the frontend ``group_by`` vocabulary onto
* the backend's (``gpu_type`` → ``instance_type``/sku), and derives the few
* convenience fields (``gpu_minutes``). Metrics the backend doesn't track
* (cpu/memory/ephemeral hours, dangling volumes) are left at 0 — the
* whole-machine SKU model meters runtime, not decomposed components.
*/
import { request } from '@umijs/max';
export interface ResourceUsageFilters {
creator_ids?: number[];
cluster_ids?: number[];
instance_ids?: number[];
gpu_types?: string[];
volume_ids?: number[];
}
export interface ResourceBreakdownRequest {
start_date: string;
end_date: string;
scope?: 'self' | 'all';
filters?: ResourceUsageFilters;
group_by?:
| 'date'
| 'resource_type'
| 'gpu_type'
| 'type'
| 'instance'
| 'user'
| 'volume'
| null;
granularity?: 'hour' | 'day' | 'week' | 'month';
page?: number;
perPage?: number;
}
export interface ResourceBreakdownSummary {
gpu_hours: number;
gpu_minutes: number;
instance_hours: number;
cpu_hours: number;
memory_gb_hours: number;
ephemeral_gb_hours: number;
active_instances: number;
gpu_types_used: number;
active_users: number;
storage_gb_days: number;
storage_gb_hours: number;
active_volumes: number;
dangling_volumes: number;
}
export interface ResourceBreakdownItem extends ResourceBreakdownSummary {
date?: string;
resource_type?: string;
gpu_type?: string;
instance_id?: number;
instance_name?: string;
volume_id?: number;
volume_name?: string;
user_id?: number;
user_name?: string;
last_active?: string;
}
export interface ResourceBreakdownResponse {
summary: ResourceBreakdownSummary;
group_by?: string;
granularity?: string;
pagination: {
page: number;
perPage: number;
total: number;
totalPage: number;
};
items: ResourceBreakdownItem[];
}
export interface UsageOption {
key: string;
label: string;
}
export interface ResourceUsageFilterOption {
id: number;
label: string;
}
export interface ResourceUsageMetaResponse {
metrics: UsageOption[];
granularities: UsageOption[];
group_bys: UsageOption[];
filters: {
creators?: ResourceUsageFilterOption[];
clusters?: ResourceUsageFilterOption[];
instances?: ResourceUsageFilterOption[];
gpu_types?: UsageOption[];
volumes?: ResourceUsageFilterOption[];
};
}
export interface ResourceEventItem {
id: number;
occurred_at: string;
creator_id?: number;
creator_name?: string;
cluster_id?: number;
cluster_name?: string;
resource_type: string;
resource_id?: number;
resource_name: string;
event_type: string;
event_message?: string;
phase?: string;
}
export interface ResourceEventsResponse {
pagination: {
page: number;
perPage: number;
total: number;
totalPage: number;
};
items: ResourceEventItem[];
}
export interface SummaryResourceDistributionItem {
label: string;
value: number;
percentage: number;
}
export interface UsageSummaryResponse {
total_tokens: number;
input_tokens: number;
output_tokens: number;
token_active_users: number;
gpu_hours: number;
instance_hours: number;
active_instances: number;
storage_gb_days: number;
active_users: number;
distribution: SummaryResourceDistributionItem[];
}
// --- endpoints -----------------------------------------------------------
const URL = {
RESOURCE_BREAKDOWN: '/usage/resource/breakdown',
GPU_BREAKDOWN: '/usage/gpu-instances/breakdown',
STORAGE_BREAKDOWN: '/usage/storage/breakdown',
EVENTS: '/usage/resource-events',
SUMMARY: '/usage/summary',
RESOURCE_META: '/usage/resource/meta'
};
// --- server (generic) shapes ---------------------------------------------
interface ServerMetrics {
instance_hours?: number;
gpu_hours?: number;
gb_days?: number;
gb_hours?: number;
resources?: number;
active_users?: number;
last_active?: string;
}
// gpu_type / type both mean the sku (Type) on the server.
interface ServerBreakdownItem {
key?: string | null;
id?: number | null;
date?: string | null;
sku?: string | null;
deleted?: boolean | null;
metrics: ServerMetrics;
}
interface ServerBreakdownResponse {
summary: ServerMetrics;
group_by?: string;
pagination: {
page: number;
perPage: number;
total: number;
totalPage: number;
};
items: ServerBreakdownItem[];
}
// --- transforms ----------------------------------------------------------
// Frontend group_by vocabulary → backend. "gpu_type" / "type" both mean the
// sku (Type / flavor) on the server.
const GROUP_BY_MAP: Record<string, string> = {
resource_type: 'resource_type',
gpu_type: 'instance_type',
type: 'type',
instance: 'instance',
volume: 'volume',
user: 'user',
date: 'date'
};
const num = (v?: number) => Number(v ?? 0);
function flattenMetrics(m: ServerMetrics): ResourceBreakdownSummary {
const gpuHours = num(m.gpu_hours);
return {
gpu_hours: gpuHours,
gpu_minutes: gpuHours * 60,
instance_hours: num(m.instance_hours),
// not metered under the whole-machine SKU model → 0
cpu_hours: 0,
memory_gb_hours: 0,
ephemeral_gb_hours: 0,
active_instances: num(m.resources),
gpu_types_used: 0,
active_users: num(m.active_users),
storage_gb_days: num(m.gb_days),
storage_gb_hours: num(m.gb_hours),
active_volumes: num(m.resources),
dangling_volumes: 0
};
}
function flattenItem(
groupBy: string | null | undefined,
it: ServerBreakdownItem
): ResourceBreakdownItem {
const flat: ResourceBreakdownItem = {
...flattenMetrics(it.metrics || {}),
last_active: it.metrics?.last_active ?? undefined
};
if (it.date) flat.date = it.date;
const id = it.id ?? undefined;
// Deleted entities get a "(Deleted)" suffix, matching the Token breakdown.
const rawKey = it.key ?? undefined;
const key = it.deleted && rawKey != null ? `${rawKey} (Deleted)` : rawKey;
switch (groupBy) {
case 'resource_type':
flat.resource_type = key;
break;
case 'gpu_type':
case 'type':
flat.gpu_type = key;
break;
case 'instance':
flat.instance_name = key;
flat.instance_id = id;
break;
case 'volume':
flat.volume_name = key;
flat.volume_id = id;
break;
case 'user':
flat.user_name = key;
flat.user_id = id;
break;
default:
break;
}
// Per-resource rows (instance / volume) carry their sku → surface it as the
// Instance Type / Type column when not already the group key.
if (!flat.gpu_type && it.sku) {
flat.gpu_type = it.sku;
}
return flat;
}
function flattenResponse(
groupBy: string | null | undefined,
res: ServerBreakdownResponse
): ResourceBreakdownResponse {
return {
summary: flattenMetrics(res.summary || {}),
group_by: res.group_by,
pagination: res.pagination,
items: (res.items || []).map((it) => flattenItem(groupBy, it))
};
}
function toServerRequest(data: ResourceBreakdownRequest) {
const groupBy = data.group_by ?? 'resource_type';
const { creator_ids, instance_ids, volume_ids } = data.filters ?? {};
return {
body: {
start_date: data.start_date,
end_date: data.end_date,
scope: data.scope ?? 'all',
group_by: GROUP_BY_MAP[groupBy] ?? groupBy,
granularity: data.granularity ?? 'day',
// POST endpoints take proper id arrays. "filter by user" + "filter by
// resource" (instance ids on the GPU tab / volume ids on Storage).
...(creator_ids?.length ? { creator_ids } : {}),
...(instance_ids?.length ? { instance_ids } : {}),
...(volume_ids?.length ? { volume_ids } : {}),
page: data.page ?? 1,
perPage: data.perPage ?? 20
},
groupBy
};
}
// --- request helpers -----------------------------------------------------
async function _breakdown(
url: string,
data: ResourceBreakdownRequest
): Promise<ResourceBreakdownResponse> {
const { body, groupBy } = toServerRequest(data);
const res = await request<ServerBreakdownResponse>(url, {
data: body,
method: 'POST'
});
return flattenResponse(groupBy, res);
}
export async function queryResourceBreakdown(
data: ResourceBreakdownRequest
): Promise<ResourceBreakdownResponse> {
return _breakdown(URL.RESOURCE_BREAKDOWN, data);
}
export async function queryGpuInstancesBreakdown(
data: ResourceBreakdownRequest
): Promise<ResourceBreakdownResponse> {
return _breakdown(URL.GPU_BREAKDOWN, data);
}
export async function queryStorageBreakdown(
data: ResourceBreakdownRequest
): Promise<ResourceBreakdownResponse> {
return _breakdown(URL.STORAGE_BREAKDOWN, data);
}
export async function queryResourceEvents(data: {
start_date: string;
end_date: string;
scope?: 'self' | 'all';
filters?: ResourceUsageFilters;
resource_types?: string[];
event_types?: string[];
page?: number;
perPage?: number;
}): Promise<ResourceEventsResponse> {
const creatorIds = data.filters?.creator_ids;
return request<ResourceEventsResponse>(URL.EVENTS, {
params: {
start_date: data.start_date,
end_date: data.end_date,
scope: data.scope ?? 'all',
resource_type: data.resource_types?.[0],
// GET endpoints take creator_ids as a CSV string (avoids axios array
// serialization quirks); the server splits it back into a list.
...(creatorIds?.length ? { creator_ids: creatorIds.join(',') } : {}),
page: data.page ?? 1,
perPage: data.perPage ?? 50
},
method: 'GET'
});
}
export interface ResourceFilterOption {
id: number;
label: string;
}
export interface ResourceFilterMeta {
creators: ResourceFilterOption[];
instances: ResourceFilterOption[];
volumes: ResourceFilterOption[];
}
export async function queryResourceFilterMeta(
scope: 'self' | 'all' = 'all'
): Promise<ResourceFilterMeta> {
const res = await request<Partial<ResourceFilterMeta>>(URL.RESOURCE_META, {
params: { scope },
method: 'GET'
});
return {
creators: res.creators || [],
instances: res.instances || [],
volumes: res.volumes || []
};
}
export async function queryUsageSummary(params: {
start_date: string;
end_date: string;
scope?: 'self' | 'all';
creator_ids?: number[];
}): Promise<UsageSummaryResponse> {
const { creator_ids, ...rest } = params;
const res = await request<{
total_tokens: number;
input_tokens: number;
output_tokens: number;
token_active_users: number;
gpu_hours: number;
instance_hours: number;
storage_gb_days: number;
active_users: number;
}>(URL.SUMMARY, {
params: {
...rest,
scope: params.scope ?? 'all',
...(creator_ids?.length ? { creator_ids: creator_ids.join(',') } : {})
},
method: 'GET'
});
// Resource Distribution donut — by GPU type, using GPU-Hours (a single,
// well-defined unit). Built from the GPU-instances breakdown grouped by
// instance type. (A true cross-resource split needs a common unit.)
let distribution: SummaryResourceDistributionItem[] = [];
try {
const byType = await queryGpuInstancesBreakdown({
start_date: params.start_date,
end_date: params.end_date,
scope: params.scope ?? 'all',
group_by: 'gpu_type',
...(creator_ids?.length ? { filters: { creator_ids } } : {}),
page: 1,
perPage: 100
});
const total = byType.items.reduce((s, i) => s + (i.gpu_hours || 0), 0);
distribution = byType.items
.filter((i) => (i.gpu_hours || 0) > 0)
.map((i) => ({
label: i.gpu_type || 'unknown',
value: i.gpu_hours,
percentage: total > 0 ? (i.gpu_hours / total) * 100 : 0
}));
} catch {
distribution = [];
}
return {
total_tokens: num(res.total_tokens),
input_tokens: num(res.input_tokens),
output_tokens: num(res.output_tokens),
token_active_users: num(res.token_active_users),
gpu_hours: num(res.gpu_hours),
instance_hours: num(res.instance_hours),
active_instances: 0,
storage_gb_days: num(res.storage_gb_days),
active_users: num(res.active_users),
distribution
};
}
// Meta is synthesized client-side — the components hardcode their metric /
// group_by options and don't call these, but keep them for any external
// importers. Filter dropdowns are empty until a meta endpoint lands.
const STATIC_META: ResourceUsageMetaResponse = {
metrics: [],
granularities: [
{ key: 'day', label: 'Day' },
{ key: 'week', label: 'Week' },
{ key: 'month', label: 'Month' }
],
group_bys: [],
filters: {}
};
export async function queryResourceMeta(): Promise<ResourceUsageMetaResponse> {
return STATIC_META;
}
export async function queryGpuInstancesMeta(): Promise<ResourceUsageMetaResponse> {
return STATIC_META;
}
export async function queryStorageMeta(): Promise<ResourceUsageMetaResponse> {
return STATIC_META;
}
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import { useEffect, useState } from 'react';
import {
queryResourceFilterMeta,
ResourceFilterOption
} from '../apis/resource';
export interface SelectOption {
value: number;
label: string;
}
export interface ResourceMetaOptions {
creators: SelectOption[];
instances: SelectOption[];
volumes: SelectOption[];
}
const EMPTY: ResourceMetaOptions = {
creators: [],
instances: [],
volumes: []
};
const toOptions = (items: ResourceFilterOption[]): SelectOption[] =>
items.map((i) => ({ value: i.id, label: i.label }));
/**
* Loads the resource tabs' filter dropdown sources in one call:
* - ``creators`` — "filter by user" (Tokens-tab equivalent of /usage/meta
* users); only shown to managers, but cheap to always load.
* - ``instances`` — "filter by GPU instance" (GPU Instances tab)
* - ``volumes`` — "filter by volume" (Storage tab)
*
* Scope-aware: managers get the org-wide lists, others only their own
* resources. Refetched when ``scope`` changes.
*/
export default function useResourceMeta(
scope: 'self' | 'all' = 'all'
): ResourceMetaOptions {
const [meta, setMeta] = useState<ResourceMetaOptions>(EMPTY);
useEffect(() => {
queryResourceFilterMeta(scope)
.then((res) =>
setMeta({
creators: toOptions(res.creators),
instances: toOptions(res.instances),
volumes: toOptions(res.volumes)
})
)
.catch(() => {
// Network/auth errors surface via the global interceptor; leave the
// dropdowns empty rather than crashing the tab.
});
}, [scope]);
return meta;
}
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/**
* Export a resource-breakdown table to Excel — the GPU Instances / Storage
* tabs' counterpart to the Tokens tab export.
*
* Columns are derived from the same antd column specs the table renders, so the
* export always matches what's on screen (whichever group_by tab is active).
* Raw values are written (not the table's formatted render output) so numbers
* stay sortable / calculable in the spreadsheet.
*/
import { exportJsonToExcel } from '@gpustack/core-ui/excel';
export interface ExportColumn {
title: string;
dataIndex: string;
}
// Keep only real data columns (drop index / render-only columns), and only
// those whose title is a plain string so the header is meaningful.
export const toExportColumns = (columns: any[]): ExportColumn[] =>
(columns || [])
.filter(
(c) => typeof c?.dataIndex === 'string' && typeof c?.title === 'string'
)
.map((c) => ({
title: c.title as string,
dataIndex: c.dataIndex as string
}));
export const exportBreakdownRows = (
rows: any[],
columns: ExportColumn[],
fileName: string,
sheetName = 'usage'
): void => {
const fields = columns.map((c) => c.dataIndex);
const fieldLabels = Object.fromEntries(
columns.map((c) => [c.dataIndex, c.title])
);
const jsonData = (rows || []).map((r) => {
const o: Record<string, any> = {};
columns.forEach((c) => {
o[c.dataIndex] = r?.[c.dataIndex] ?? '';
});
return o;
});
exportJsonToExcel({
fileName,
sheets: [{ jsonData, sheetName, fields, fieldLabels, formatMap: {} }]
});
};
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/**
* Time-bucket helpers shared by the resource-usage tabs' charts.
*
* The backend returns a per-bucket value keyed by ``bucket_start`` (hourly) or
* a date_trunc'd date (day/week/month). The chart x-axis must use the SAME key
* format so series line up. ``bucketKey`` normalizes any returned value to that
* format via dayjs; ``generateBucketRange`` produces a contiguous axis.
*/
import dayjs from 'dayjs';
export type Granularity = 'hour' | 'day' | 'week' | 'month';
// Cap the hourly axis so a wide date range doesn't render hundreds of bars.
const HOUR_MAX_DAYS = 7;
export const bucketKey = (value: any, granularity: Granularity): string => {
const d = dayjs(value);
if (granularity === 'hour') return d.format('YYYY-MM-DD HH:00');
if (granularity === 'month') return d.format('YYYY-MM');
return d.format('YYYY-MM-DD'); // day / week (week-start date as returned)
};
export const generateBucketRange = (
start: string,
end: string,
granularity: Granularity
): string[] => {
if (!start || !end) return [];
const endDay = dayjs(end);
let cursor = dayjs(start);
// Hour view: clamp to the last HOUR_MAX_DAYS to keep the axis readable.
if (granularity === 'hour') {
const clampStart = endDay.subtract(HOUR_MAX_DAYS, 'day');
if (cursor.isBefore(clampStart)) cursor = clampStart;
}
const step = granularity === 'hour' ? 'hour' : granularity;
const out: string[] = [];
const last =
granularity === 'hour' ? endDay.endOf('day') : endDay.startOf('day');
while (cursor.isBefore(last) || cursor.isSame(last)) {
out.push(bucketKey(cursor, granularity));
cursor = cursor.add(1, step as dayjs.ManipulateType);
}
return out;
};