Monitoring and Alerts
The monitoring data in the embedded panel can be used for RabbitMQ monitoring and alerts in terms of resources, performance, etc., and supports the configuration of notification strategies.
The intuitively presented monitoring data can assist in decision-making for operational inspections or performance tuning, and the comprehensive alert and notification mechanism will help ensure stable database operations.
Monitoring
The platform collects commonly used monitoring metrics for RabbitMQ resources, performance, etc., by default. In the instance's Monitoring tab, real-time monitoring data for the metrics can be viewed.
| Category | Metrics |
|---|---|
| Node Monitoring | Monitoring of node available memory, disk, file descriptors, and other metrics |
| Message Monitoring | Monitoring of sent and received messages |
| Queue Monitoring | Overall monitoring of queues |
| Channel Monitoring | Overall monitoring of channels |
| Connection Monitoring | Overall monitoring of client connections |
RabbitMQ metrics primarily expose overall metrics for various components; thus, the default monitoring panel cannot accurately monitor the status of a specific
QueueorExchange.
Alerts
Go to the Application Service's Alerts > Alert Policies page to create an alert policy corresponding to RabbitMQ (you may also use the platform-wide alert feature to create alerts).
Configuring Alert Policies
To enable alerts, first, create an alert policy in the Application Service. The alert policy describes the objects you wish to monitor, under what circumstances you wish to receive alerts, and how you should be notified of related alerts.
The platform includes the following built-in alert metrics:
| Name | Recommended Trigger Conditions | Description |
|---|---|---|
| Instance Availability | !=1, and persists for 30 seconds | Monitors the availability of the cluster |
| Channel Count | Set thresholds based on actual specifications and client applications | Real-time monitoring of the number of channels |
| Message Write Frequency | Set thresholds based on actual specifications | Real-time monitoring of message write frequency |
| Connection Count | Set thresholds based on actual specifications | Real-time monitoring of the number of connections |
| Queue Count | Set thresholds based on actual specifications | Real-time monitoring of the number of queues |
| Node CPU Utilization | >80%, and persists for 30 seconds | Real-time monitoring of CPU usage; if CPU usage is too high, consider scaling. |
| Node Memory Utilization | >80%, and persists for 30 seconds | Real-time monitoring of memory usage; if memory usage is too high, scaling is needed immediately. |
| Node Storage Space Utilization | >80%, and persists for 30 seconds | Real-time monitoring of storage space; if usage is too high, consider scaling. |
These alert metrics allow for the quick creation of alert policies.
In addition to the built-in alert metrics, custom alert metrics can also be defined. Custom alerts require you to edit PromQL yourself and submit it to the alert metric form. PromQL is a relatively complex expression that can be edited and debugged using the built-in Prometheus Console. For basic PromQL support, please refer to the PromQL official documentation.
For more information on configuring and using alerts, please refer to .