Google Cloud Pub/Sub Telemetry: from boundary to verified row
Use Google Cloud Pub/Sub Telemetry at a controlled application boundary, keep the event contract small, and verify a known outcome before building aggregate views.
- 1
Choose the outcome
Pub/Sub delivery reliability
- 2
Define the contract
message_id, message_type, topic, subscription, ordering_key_category, and release
- 3
Instrument the boundary
Pub/Sub can redeliver messages; keep the provider message ID and delivery attempt separate from the final business outcome.
- 4
Verify the evidence
Exercise a known fixture, then inspect pubsub_message_completed for one correctly typed terminal row.
Before you start
Prerequisites and boundaries
- @google-cloud/pubsub and telemetry-sh initialized in a trusted publisher or subscriber
- Stable topic, subscription, message type, and logical outcome definitions
- An idempotent consumer and a documented acknowledgement or exactly-once policy
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.
npm installation
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.
Google Cloud Pub/Sub Telemetry event
await telemetry.log("pubsub_message_completed", {
message_id: message.id,
message_type: "account_export",
topic: "account-exports",
subscription: "account-export-worker",
status: "success",
delivery_attempt: message.deliveryAttempt ?? 1,
wait_ms: Date.now() - Number(message.publishTime.getTime()),
duration_ms: Math.round(performance.now() - startedAt),
acknowledged: true,
dead_lettered: false,
service: "export-worker",
release: process.env.APP_RELEASE,
});Event contract
message_id, message_type, topic, subscription, ordering_key_category, and release
status, delivery_attempt, wait_ms, duration_ms, acknowledged, and error_type
dead_lettered, published_at, account_id, service, region, and environment
Implementation checkpoints
Checkpoint 1
Pub/Sub can redeliver messages; keep the provider message ID and delivery attempt separate from the final business outcome.
Checkpoint 2
Exactly-once delivery has subscription and regional constraints, so verify the actual configuration instead of inferring it from an acknowledgement call.
Checkpoint 3
Monitor provider backlog metrics beside application outcomes, and do not copy message data, attributes with private content, or unrestricted errors into events.
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.
Google Cloud Pub/Sub Telemetry verification query
SELECT *
FROM pubsub_message_completed
ORDER BY timestamp_utc DESC
LIMIT 20;Implementation references
Review the event contract, data-safety guidance, and upstream primary documentation before enabling a new production path.
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.
Event schema starting points
Event contracts for this workflow
Review the row grain, emit boundary, required types, privacy classes, example payload, and validation checklist before adapting a query or snippet to production.
Related product capability
Continue this workflow in Alerts
Promote the reviewed reliability query into an owned threshold and response workflow.
Related SQL recipes
Answer the next question with SQL
Run the query against the structured fields from this workflow, inspect the example result, and turn a useful answer into a dashboard or alert.
Measure Queue Wait Time by Job
Which jobs wait longest before a worker starts them?
Open recipeMeasure Background Job Retry and Failure Rate
Which background jobs consume the most retries or still fail?
Open recipeMeasure Dead-Letter Queue Growth
Which queues are adding dead-letter jobs faster than they are resolving them?
Open recipeMeasure Late-Arriving Events
Which event producers deliver data late enough to distort analysis?
Open recipeBrowse by implementation family
Compare related integration patterns
Templates to pair with this integration
Background Job Failure Monitor
Capture queue, cron, import, billing sync, and webhook job health from the first run through retries and failures.
Open templateEvent Tracking Plan Template
Create a reviewable event catalog covering grain, ownership, fields, privacy, retention, validation, and downstream SQL dependencies.
Open templateMore integrations
BullMQ Queue Monitoring
Measure BullMQ queue wait, execution duration, retries, failures, and dead-letter growth with SQL-ready lifecycle events.
Open guideRabbitMQ Queue Telemetry
Track RabbitMQ publish confirmation, delivery, acknowledgement, redelivery, queue wait, retries, and dead-letter outcomes with structured events.
Open guideAzure Service Bus Telemetry
Track Azure Service Bus sends, receives, lock renewal, settlement, redelivery, deferral, and dead-letter outcomes without collecting message bodies.
Open guide