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Rqueue

Monitoring Queue Statistics

Rqueue provides built-in monitoring support through the Micrometer metrics library. These metrics can be exported to monitoring systems such as Prometheus, Datadog, or any other Micrometer-supported backend.

Gauge Metrics

Rqueue exposes several gauge metrics that provide real-time insights into the state of your queues.

Metric Description
queue.size The number of tasks currently waiting in the queue.
dead.letter.queue.size The number of tasks moved to the dead letter queue after repeated failures.
scheduled.queue.size The approximate number of tasks scheduled for future execution.
processing.queue.size The approximate number of tasks currently being processed by workers.

These metrics are essential for tracking queue health and identifying processing bottlenecks or backlogs.

Execution and Failure Counters

Rqueue can also publish execution and failure counters. These counters are disabled by default but can be enabled via configuration.

rqueue.metrics.count.execution=true
rqueue.metrics.count.failure=true
Counter Description
execution counter Tracks the total number of successfully executed tasks.
failure counter Tracks the total number of task execution failures.

These counters help you monitor reliability and set up alerts based on failure rates.

Metric Name Prefixes

By default, Rqueue publishes metrics without a namespace prefix. For example:

queue.size

If multiple components in your system export similar metrics, this can lead to naming collisions or cluttered dashboards.

To group Rqueue metrics under a specific namespace, configure a metrics prefix:

rqueue.metrics.prefix=rq.

With this configuration applied, metrics will be exported as:

rq.queue.size
rq.dead.letter.queue.size
rq.processing.queue.size

Using a prefix helps keep your dashboards, alerts, and monitoring queries organized.

Integration

Spring Boot Applications

To enable monitoring in a Spring Boot application:

  1. Add the necessary Micrometer dependencies and your chosen exporter (e.g., Prometheus).
  2. Configure optional metric tags if needed:
rqueue.metrics.tags.<name>=<value>
  1. Enable execution and failure counters if required.

Spring Applications

For standard Spring (non-Boot) applications:

  1. Add Micrometer dependencies to your project.
  2. Define a MeterRegistry bean.
  3. Configure an RqueueMetricsProperties bean with your desired settings.

Example Grafana Dashboard

Below is an example Grafana dashboard that visualizes Rqueue metrics.

Grafana Dashboard