HaproxyRetryHigh

HaproxyRetryHigh #

High rate of retry on {{ $labels.fqdn }}/{{ $labels.backend }} backend

Alert Rule
alert: HaproxyRetryHigh
annotations:
  description: |-
    High rate of retry on {{ $labels.fqdn }}/{{ $labels.backend }} backend
      VALUE = {{ $value }}
      LABELS = {{ $labels }}    
  runbook: https://srerun.github.io/prometheus-alerts/runbooks/haproxy-exporter-v1/haproxyretryhigh/
  summary: HAProxy retry high (instance {{ $labels.instance }})
expr: sum by (backend) (rate(haproxy_backend_retry_warnings_total[1m])) > 10
for: 2m
labels:
  severity: warning

Meaning #

The HaproxyRetryHigh alert is triggered when the rate of retry warnings for a HAProxy backend exceeds 10 per minute. This alert indicates that there is a high rate of retries on a specific backend, which can lead to performance issues, increased latency, and decreased system reliability.

Impact #

  • Increased latency and decreased response times for users
  • Decreased system reliability and potential for errors
  • Performance issues on the backend, potentially leading to cascading failures
  • Potential for resource exhaustion and increased load on the backend

Diagnosis #

To diagnose the issue, follow these steps:

  1. Check the HAProxy logs for errors and retry reasons
  2. Verify the backend configuration and check for any misconfigurations
  3. Investigate any recent changes to the backend or HAProxy configuration
  4. Check the system resources (CPU, memory, and disk usage) to rule out resource constraints
  5. Verify the network connectivity and latency between the HAProxy instance and the backend

Mitigation #

To mitigate the issue, follow these steps:

  1. Investigate and address the root cause of the retries (e.g., backend errors, network issues, or misconfigurations)
  2. Implement retry throttling or exponential backoff to reduce the load on the backend
  3. Consider load balancing or distributing the traffic across multiple backends to reduce the load on a single backend
  4. Monitor the HAProxy and backend performance metrics to detect any potential issues before they escalate
  5. Consider implementing circuit breakers or fallbacks to handle failures and reduce the impact on the system

Note: For more detailed steps and specific procedures, refer to the runbook linked in the alert annotations: https://github.com/srerun/prometheus-alerts/blob/main/content/runbooks/haproxy-exporter-v1/HaproxyRetryHigh.md

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