Queue & Worker Monitoring
Monitor background jobs from queue to completion
Track jobs through queues, workers, processing, and persistence. Know when jobs stall, fail silently, or produce invalid output before it affects your product.
Why Queue Monitoring Matters
Most products run critical work in the background: sending emails, processing payments, generating reports, syncing data, running AI inference. These jobs go through a queue, get picked up by workers, and produce a result.
The problem: a worker process can be running and reporting healthy while the jobs it processes are silently failing. The queue looks fine, the worker looks fine, but customers are not getting their emails, their payments are not being processed, and their data is stale.
Queue monitoring tracks what actually happens inside the pipeline, not just whether the process is alive.
What Goes Wrong in Background Pipelines
Jobs sit in the queue too long
Workers are overloaded or a consumer died. The queue grows and processing latency climbs without any error.
Workers process but produce bad output
The job runs and exits with code 0, but the result is empty, malformed, or contains stale data.
Results never reach their destination
Processing completes but the write to the database, the API call, or the notification never happens.
Retry storms hide root causes
Failed jobs retry automatically. They eventually succeed, but the pattern of failures and the wasted compute go unnoticed.
What upti.my Tracks
Common Queue Patterns to Monitor
Email and notification delivery
Track whether messages are sent after being queued, not just whether the worker ran.
Data imports and ETL
Monitor rows parsed, records validated, and sync completion for bulk processing jobs.
Report generation
Track whether reports are built, stored, and delivered within expected time windows.
AI and ML inference
Monitor model input validation, inference time, and result persistence for async AI jobs.
Frequently Asked Questions
What does queue monitoring track beyond basic job status?
Basic job monitoring tells you a job was enqueued and whether it exited with code 0. Queue monitoring tracks whether the worker picked it up, how long processing took, whether the output was valid, and whether downstream steps completed. A job can succeed technically but produce wrong results.
Which queue systems does this work with?
upti.my monitors the processing pipeline, not the queue software directly. It works with any queue system: Redis-backed queues like Sidekiq and Bull, Celery, RabbitMQ, SQS, and custom implementations. You instrument the processing steps, not the queue itself.
How do I know when a worker is silently stuck?
Each processing step has an expected time window. If a worker picks up a job but does not report the next step within that window, upti.my alerts you. This catches workers that are stuck in infinite loops, deadlocked, or processing at unexpectedly slow rates.
Can I monitor job throughput and queue depth?
Yes. You can track whether jobs are being processed at the expected rate. If your queue normally processes 100 jobs per hour and that drops to 10, upti.my flags the change before it creates a visible backlog.
How is this different from monitoring the worker process itself?
Process monitoring tells you the worker is running. Queue monitoring tells you it is picking up jobs, processing them correctly, and producing valid output. A worker process can be alive but stuck, overloaded, or processing stale data.
Related Topics
Workflow Monitoring
Track multi-step workflows and validate data between steps.
Webhook Monitoring
Monitor webhook processing from receipt to downstream action.
Cron Job Monitoring
Heartbeat monitoring for scheduled tasks and background jobs.
What You Can Monitor
See everything upti.my can monitor across your stack.
Your workers are running. Are they doing the right thing?
Monitor what happens inside the pipeline, not just whether the process is alive.