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Saxon FletcherandClaude Opus 5.5
09c3167551
Adds an optional `scope` to the unified logs search that narrows every query (rows, counts, chart and facets, on both the OTEL and BigQuery builders) to one edge function's invocations and runtime output. - New `edge function runtime` log type backed by `function_logs`, with its level read from the console level and details kept in metadata - `getLogTypeVisibility` keeps that type out of the project-wide Logs page, which already shows runtime logs inside each invocation - `toQuerySearchParams` attaches the scope Nothing sets a scope yet, so the Logs page is unchanged. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
88 lines
3.0 KiB
TypeScript
88 lines
3.0 KiB
TypeScript
import { z } from 'zod'
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import { parseOtelTimestamp } from './otel-inspection.utils'
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import { LEVELS } from '@/components/ui/DataTable/DataTable.constants'
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import { tryParseJson } from '@/lib/helpers'
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type UnifiedLogMetadataRow = {
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log_type?: string | null
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status?: string | number | null
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method?: string | null
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pathname?: string | null
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event_message?: string | null
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}
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const unifiedLogsQueryRowSchema = z.object({
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id: z.string(),
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timestamp: z.union([z.string(), z.number()]),
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log_type: z.string(),
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status: z.union([z.string(), z.number()]).nullable(),
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level: z.enum(LEVELS).nullable(),
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pathname: z.string().nullable(),
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event_message: z.string().nullable(),
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method: z.string().nullable(),
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log_count: z.number().nullable(),
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logs: z.array(z.unknown()).nullable(),
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auth_user: z.string().nullish(),
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metadata: z.record(z.string(), z.unknown()).nullish(),
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})
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export type UnifiedLogsQueryRow = z.infer<typeof unifiedLogsQueryRowSchema>
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export const parseUnifiedLogsQueryRows = (value: unknown): UnifiedLogsQueryRow[] =>
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z.array(unifiedLogsQueryRowSchema).parse(value ?? [])
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const extractLeadingStatus = (s?: string) => {
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const m = typeof s === 'string' ? s.match(/^(\d{3})\b/) : null
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return m ? Number(m[1]) : undefined
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}
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// Log types whose rows aren't HTTP requests, so they carry no status, method or pathname.
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const NON_REQUEST_LOG_TYPES = new Set(['compute', 'edge function runtime'])
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export const extractLogMetadata = (row: UnifiedLogMetadataRow) => {
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if (row.log_type && NON_REQUEST_LOG_TYPES.has(row.log_type)) {
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return { status: null, method: null, pathname: null }
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}
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// [Joshen] For auth logs, these metadata are nested within event_message,
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// so opting to bring them out at the query level
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const eventMessage = tryParseJson(row.event_message)
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const status =
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row.log_type === 'auth'
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? (eventMessage?.status ??
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extractLeadingStatus(eventMessage?.msg) ??
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extractLeadingStatus(eventMessage?.error))
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: (row.status ?? 200)
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const method = row.log_type === 'auth' ? eventMessage?.method : row.method
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const pathname = row.log_type === 'auth' ? eventMessage?.path : row.pathname || ''
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return { status, method, pathname }
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}
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export const mapUnifiedLogRow = (row: UnifiedLogsQueryRow) => {
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const isComputeLog = row.log_type === 'compute'
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const { status, method, pathname } = extractLogMetadata(row)
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const mappedRow = {
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id: row.id,
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date: parseOtelTimestamp(row.timestamp),
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method,
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pathname,
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status,
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timestamp: row.timestamp,
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level: isComputeLog ? null : row.level,
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event_message: row.event_message ?? '',
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log_type: row.log_type,
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log_count: row.log_count ?? null,
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logs: row.logs ?? [],
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auth_user: isComputeLog ? null : row.auth_user || null,
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}
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// Compute and edge function runtime rows keep their details in metadata (log_attributes)
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if (isComputeLog || row.log_type === 'edge function runtime') {
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return { ...mappedRow, metadata: row.metadata ?? null }
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}
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return mappedRow
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}
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