RabbitmqTooManyConnections #

RabbitMQ instance has too many connections (> 1000)

alert: RabbitmqTooManyConnections
annotations:
  description: |-
    RabbitMQ instance has too many connections (> 1000)
      VALUE = {{ $value }}
      LABELS = {{ $labels }}    
  runbook: https://srerun.github.io/prometheus-alerts/runbooks/kbudde-rabbitmq-exporter/rabbitmqtoomanyconnections/
  summary: RabbitMQ too many connections (instance {{ $labels.instance }})
expr: rabbitmq_connectionsTotal > 1000
for: 2m
labels:
  severity: warning

Here is the runbook for the RabbitmqTooManyConnections alert:

Meaning #

The RabbitmqTooManyConnections alert is triggered when the number of connections to a RabbitMQ instance exceeds 1000. This alert indicates that the RabbitMQ instance is experiencing a high load, which can lead to performance issues, slower message processing, and potentially even crashes.

Impact #

If left unaddressed, a high number of connections to RabbitMQ can have several negative impacts:

• Slower message processing and increased latency
• Increased memory usage, leading to potential crashes or performance degradation
• Decreased overall system performance and reliability
• Potential message loss or corruption due to connection timeouts or failures

Diagnosis #

To diagnose the root cause of the RabbitmqTooManyConnections alert, follow these steps:

1. Check the RabbitMQ dashboard or command-line tools to verify the number of connections and identify the source of the connections.
2. Investigate recent changes to the system, such as increased load, new applications or services connecting to RabbitMQ, or changes to messaging patterns.
3. Review RabbitMQ logs to identify any errors or issues related to connection handling or message processing.
4. Check system resources, such as CPU, memory, and disk usage, to ensure they are within acceptable levels.

Mitigation #

To mitigate the effects of the RabbitmqTooManyConnections alert, follow these steps:

1. Identify and terminate unnecessary connections to RabbitMQ, such as idle or abandoned connections.
2. Implement connection limits or quotas to prevent excessive connections to RabbitMQ.
3. Optimize RabbitMQ configuration and tuning to handle high connection loads, such as increasing the number of file descriptors or adjusting the connection timeout.
4. Consider load balancing or clustering RabbitMQ instances to distribute the connection load across multiple nodes.
5. Monitor RabbitMQ performance and adjust system resources as needed to ensure sufficient capacity to handle the connection load.

Remember to always test and validate changes to RabbitMQ configuration and tuning to ensure they do not introduce new issues or affect system performance.