TraefikHighHttp5xxErrorRateBackend #

Traefik backend 5xx error rate is above 5%

Alert Rule

alert: TraefikHighHttp5xxErrorRateBackend
annotations:
  description: |-
    Traefik backend 5xx error rate is above 5%
      VALUE = {{ $value }}
      LABELS = {{ $labels }}    
  runbook: https://srerun.github.io/prometheus-alerts/runbooks/embedded-exporter-v1/traefikhighhttp5xxerrorratebackend/
  summary: Traefik high HTTP 5xx error rate backend (instance {{ $labels.instance
    }})
expr: sum(rate(traefik_backend_requests_total{code=~&#34;5.*&#34;}[3m])) by (backend) / sum(rate(traefik_backend_requests_total[3m]))
  by (backend) * 100 &gt; 5
for: 1m
labels:
  severity: critical

Meaning #

The TraefikHighHttp5xxErrorRateBackend alert is triggered when the 5xx error rate for a Traefik backend exceeds 5% over a 3-minute period. This indicates that the backend is experiencing a high rate of internal server errors, which can impact the availability and performance of the application.

Impact #

High 5xx error rates can lead to:
- Increased latency and response times
- Decreased application availability
- Frustrated users and potential loss of revenue
- Increased load on the backend, leading to resource exhaustion
If left unaddressed, this issue can cause a cascading failure of the application and related services.

Diagnosis #

Check the Traefik dashboard and logs for errors and exceptions related to the backend
Investigate the backend service for issues, such as:
- High CPU or memory usage
- Slow database queries or connectivity issues
- Configuration errors or misconfigurations
- Insufficient resources or capacity
Review the Traefik configuration for any misconfigurations or issues with the backend routing
Verify that the backend service is properly deployed and configured

Mitigation #

Immediately investigate and address the root cause of the 5xx errors in the backend service
Implement short-term mitigations, such as:
- Temporarily reducing the load on the backend by load-shedding or rate-limiting requests
- Increasing the capacity of the backend service by adding more resources or instances
- Enabling caching or buffering to reduce the load on the backend
Work on long-term solutions, such as:
- Optimizing database queries and database performance
- Improving the architecture and design of the backend service
- Implementing monitoring and alerting to detect issues earlier
- Conducting regular performance testing and reviews to identify bottlenecks and areas for improvement