Inngest And Trigger.dev Job Telemetry

Implementation evidence

Inngest And Trigger.dev Job Telemetry: from boundary to verified row

Use Inngest And Trigger.dev Job Telemetry at a controlled application boundary, keep the event contract small, and verify a known outcome before building aggregate views.

1
Choose the outcome
Background job monitoring
2
Define the contract
provider, job_name, run_id, queue_name, and trigger_type
3
Instrument the boundary
Emit attempt events only when attempt-level analysis is required, and emit one separate terminal event so retries cannot inflate completed-job counts.
4
Verify the evidence
Exercise a known fixture, then inspect job_completed for one correctly typed terminal row.

Before you start

Prerequisites and boundaries

An Inngest function or Trigger.dev task with stable function, task, and run identifiers
Lifecycle hooks or terminal handlers that observe success, exhausted retries, and cancellation
Idempotent side effects and an explicit distinction between an attempt and the final run outcome

Delivery setup

Install and initialize server-side

Import telemetry-sh in server-only code and initialize it once with process.env.TELEMETRY_API_KEY. Keep ingestion credentials out of browser bundles, client-visible environment variables, source control, logs, and exception messages.

inngest-trigger-background-jobs-install

npm installation

bash

npm install telemetry-sh

1Prepare one reusable server-side delivery client with bounded network behavior.
2Add the outcome event at the success, failure, retry, or timeout boundary.
3Send controlled fixtures and inspect the stored rows before enabling an alert.

Snippet

Start with one structured event

Add this shape where the workflow completes, fails, or retries. Then build the dashboard from real fields.

inngest-trigger-background-jobs

Inngest And Trigger.dev Job Telemetry event

javascript

await telemetry.log("job_completed", {
  provider: "inngest",
  job_name: "sync_stripe_subscription",
  run_id: runId,
  queue_name: "billing",
  attempt: 1,
  status: "success",
  duration_ms: 4120,
  item_count: 37,
  retry_exhausted: false,
  release: process.env.APP_RELEASE,
});

Event contract

provider, job_name, run_id, queue_name, and trigger_type

attempt, status, duration_ms, scheduled_at, started_at, and error_type

item_count, retry_exhausted, idempotency_outcome, and release

Implementation checkpoints

Checkpoint 1

Emit attempt events only when attempt-level analysis is required, and emit one separate terminal event so retries cannot inflate completed-job counts.

Checkpoint 2

Use provider lifecycle or failure hooks for exhausted retries; a caught step error is not necessarily a failed function or task.

Checkpoint 3

Test replay and retry behavior with an idempotent fixture so monitoring does not conceal duplicate side effects.

Verification

Prove the event arrived

Run this after exercising known success and failure cases. Replace the fallback table name if your final event contract differs from the snippet.

inngest-trigger-background-jobs-verification

Inngest And Trigger.dev Job Telemetry verification query

sql

SELECT *
FROM job_completed
ORDER BY timestamp_utc DESC
LIMIT 20;

Confirm one terminal row per logical outcome, with the expected status, identifiers, units, and UTC time.

Inspect the inferred schema and verify that retries do not change field types or generate a new logical event ID.

Search the stored fields for credentials, raw payloads, prompts, private content, and unbounded error messages.

Exercise a provider timeout, ingestion rejection, and process shutdown before treating the dashboard as complete.

Implementation references

Review the event contract, data-safety guidance, and upstream primary documentation before enabling a new production path.

Queue worker observability Retry-storm SQL Stalled-job SQL Inngest error handling and retries Trigger.dev task lifecycle and retries

Production boundary

Keep the outcome event small and recoverable

This pattern provides

A bounded, SQL-ready outcome beside the upstream workflow.
Stable fields for dashboards, alerts, and cross-event correlation.
A fixture-driven path for validating success, failure, retry, and timeout behavior.

This pattern does not provide

An OTLP exporter, automatic collection pipeline, or replacement for detailed traces and diagnostic logs.
Exactly-once delivery merely because the payload contains an event ID.
Permission to collect raw provider payloads, user content, credentials, or regulated data.

Delivery and idempotency Batching and shutdown Troubleshoot ingestion

Event schema starting points

Review the row grain, emit boundary, required types, privacy classes, example payload, and validation checklist before adapting a query or snippet to production.

Async reliability11 fields