RabbitMQ monitoring provides real-time visibility into your message broker infrastructure to ensure reliable message processing and prevent costly downtime in distributed systems. Using OpenTelemetry Collector, you get comprehensive monitoring through a flexible, vendor-neutral approach that works across self-hosted environments.
Why RabbitMQ monitoring?
- Prevent outages - Get alerts for queue backlogs, consumer failures, and memory/disk alarms before they cause downtime
- Optimize performance - Identify slow consumers, message bottlenecks, and resource constraints that affect processing speed
- Plan capacity - Track resource usage, message rates, and connection counts to scale proactively
- Ensure message delivery - Monitor queue depths, acknowledgment rates, and message persistence to prevent data loss
Common use case
Whether you're processing order fulfillment messages, handling event-driven microservices communication, or managing background job queues, RabbitMQ monitoring helps you catch issues before they impact your business. Get alerted when queue depths spike threatening message processing SLAs, when consumer failures risk message accumulation, or when memory alarms threaten broker stability. This monitoring is essential for e-commerce platforms, financial systems, and any application where message delivery delays or failures can affect user experience or business operations.
Get started
Ready to start monitoring your RabbitMQ message broker? The setup guide includes prerequisites, configuration steps, and troubleshooting tips.
How it works
The OpenTelemetry Collector connects to your RabbitMQ management API to collect comprehensive metrics:
Data collection:
- RabbitMQ receiver connects to RabbitMQ management API (port 15672) for queue metrics, node health, consumer activity, and connection status
Data flow:
- Collector gathers metrics from the management API at regular intervals
- Data is processed, enriched with host information, and batched for efficient transmission
- Metrics are exported to New Relic via the OTLP exporter
- New Relic automatically creates entities and populates dashboards
What you get: Key metrics include queue depths, message rates, consumer counts, node resource utilization, memory/disk alarms, and connection activity.
For complete metric names, descriptions, and alerting recommendations, see RabbitMQ metrics reference.
Optional: Add log collection
The monitoring setup above tracks your RabbitMQ broker health and performance. To get the full picture of what's happening in your message broker, you can also collect and forward RabbitMQ logs.
Log collection adds:
- Error messages and warnings from RabbitMQ processes
- Connection and authentication events
- Queue and exchange operations
- Complete visibility from message ingestion to delivery
Setup: RabbitMQ log collection is available for self-hosted deployments. See the self-hosted installation guide for configuration details.
Next steps
Ready to start monitoring your RabbitMQ message broker?
Set up monitoring:
- Self-hosted RabbitMQ - Monitor RabbitMQ running on physical or virtual machines
After setup:
- Find and query your data - Navigate New Relic UI and write NRQL queries
- Explore RabbitMQ metrics - Complete metrics reference with alerting recommendations