How to monitor Python RQ jobs and get alerted before failures pile up

Redis Queue (RQ) is a popular Python background job library, but its simplicity often leads teams to under-monitor it, allowing job failures to accumulate silently in the FailedJobRegistry. When a job fails, RQ moves it to the registry without crashing the worker, making failures invisible unless the registry is actively watched. Key metrics to track include failure rate, queue backlog, job latency, and worker liveness, all of which can be queried directly from Redis using RQ's built-in registries. Alerts should be based on failure rates over a time window rather than individual failures, and identical exceptions should be grouped to avoid alert storms. Monitoring options range from a simple cron-based setup to Prometheus and Grafana exports or hosted monitoring services.