NestJS 12 can emit JSON directly through ConsoleLogger and treats plain objects passed after the message as structured metadata. TaskFlow keeps that built-in path instead of adding another logging library before a concrete need appears. const app = await NestFactory.create(AppModule, { logger: new ConsoleLogger({ json: process.env.NODE_ENV === 'production', }), });
private readonly logger = new Logger(TasksService.name);
this.logger.log('Task status updated', { requestId, taskId, fromStatus, toStatus, userId, });
Stable event fields Field Meaning
requestId Correlates one incoming HTTP request and downstream work
event Stable machine-searchable event name
context Service/module emitting the record
userId Internal domain ID when policy permits
workspaceId Tenant scope when relevant
durationMs Measured operation duration
errorCode Application error code, not raw secret-bearing exception text
Log level policy • debug: local diagnosis and temporary high-detail context; normally disabled or sampled in production.
• log/info: expected lifecycle or meaningful business/operational events.
• warn: degraded/recoverable state that deserves attention but did not fail the request.
• error: request/job failed or invariant unexpectedly broke.
• fatal: process cannot continue safely. Production caution: Never log bearer tokens, refresh tokens, cookies, service-role keys, DATABASE_URL, passwords, signed upload tokens, or full request bodies by default.
Structured Logging Log Levels and Events matters because it changes a real boundary in TaskFlow. The goal is to understand the inputs, owner, observable output, and failure modes before adding more abstraction.
Restate the goal of “Structured Logging Log Levels and Events” as one observable behavior. Write the success signal before touching code.
Trace the boundary map: request → correlation id → structured event → metric/trace → diagnosis. Mark the one boundary this lesson changes.
Inspect the current repository state and record the exact files, route, table, or runtime involved. Avoid creating an abstraction before you can name the existing owner.
Implement the smallest vertical slice. Add one coherent change, run the narrowest verification command, and read the output before continuing.
Connect the slice to TaskFlow’s phase artifact: Observability layer connecting Next.js/API errors and request IDs to structured logs and monitoring releases.. Verify behavior from the outside as a user or API client would.
Create one controlled failure that is safe to reproduce. Predict the symptom first, capture evidence, locate the earliest broken boundary, then fix only that cause.
Close the reference and rebuild or explain the core change from memory. Record what you would monitor or test before trusting the same change in production.
logger.error({
requestId, route: request.url, userId: user?.id,
errorCode: error.code, durationMs,
}, "request failed");Do not copy this as a finished answer. Predict what each boundary does, type the smallest useful slice, run it, then compare the result with your prediction.
Return to the nearest observable boundary: input, network, process log, database, or rendered UI. Compare actual evidence with the predicted path.
Change one variable at a time and reproduce the original failure after the fix; otherwise you have correlation, not diagnosis.
Without copying the final source, create a second small scenario that applies “Structured Logging Log Levels and Events” to a different TaskFlow resource or input. Write the acceptance criteria first, implement it, and provide the evidence that each criterion is satisfied.
Generate or propagate a request ID and return it so support can correlate client reports.
Use the smallest change that demonstrates this lesson. Stop after it works and capture evidence.Tokens/passwords in logs
Predict the symptom before causing the failure. Then locate the earliest boundary where reality diverges from expectation.Why does this responsibility live here, what input does it trust, what output proves success, and what would go wrong if another layer owned it?
If your explanation is vague, repeat the boundary trace before moving on.Close the reference. Reproduce the core idea from memory or explain the exact request/data flow aloud. Then check your diff or notes for accidental shortcuts that bypass validation, authorization, error handling, or verification earned in earlier phases.