HaproxyHttpSlowingDown

HaproxyHttpSlowingDown #

Average request time is increasing

Alert Rule
alert: HaproxyHttpSlowingDown
annotations:
  description: |-
    Average request time is increasing
      VALUE = {{ $value }}
      LABELS = {{ $labels }}    
  runbook: https://srerun.github.io/prometheus-alerts/runbooks/haproxy-exporter-v1/haproxyhttpslowingdown/
  summary: HAProxy HTTP slowing down (instance {{ $labels.instance }})
expr: avg by (backend) (haproxy_backend_http_total_time_average_seconds) > 1
for: 1m
labels:
  severity: warning

Here is a runbook for the HaproxyHttpSlowingDown alert:

Meaning #

The HaproxyHttpSlowingDown alert is triggered when the average HTTP request time exceeds 1 second for a particular backend, indicating that HAProxy is experiencing performance issues.

Impact #

This issue can lead to:

  • Slower response times for users, resulting in a poor user experience
  • Increased latency, potentially causing timeouts and errors
  • Reduced throughput, impacting the overall performance of the application
  • Increased load on the system, potentially leading to resource exhaustion

Diagnosis #

To diagnose the issue, follow these steps:

  1. Check the HAProxy logs for any errors or warnings related to the slow requests
  2. Verify that the backend services are functioning correctly and responding within the expected timeframe
  3. Investigate any recent changes to the configuration or deployment of the HAProxy instance or backend services
  4. Check the system resources (CPU, memory, disk space) to identify any potential bottlenecks
  5. Use tools like haproxy -vv or haproxy-cli to inspect the current configuration and statistics

Mitigation #

To mitigate this issue, follow these steps:

  1. Investigate and resolve any issues with the backend services, such as slow responses or resource constraints
  2. Check and adjust the HAProxy configuration to optimize performance, such as tuning timeouts, maxconn, and server weights
  3. Consider implementing load balancing or caching mechanisms to reduce the load on the HAProxy instance
  4. Verify that the system resources are sufficient to handle the current load, and consider scaling up or optimizing resource allocation
  5. Monitor the HAProxy performance and adjust the configuration as needed to prevent future slowdowns

Additionally, consider implementing proactive measures to prevent slow downs, such as:

  • Regularly reviewing HAProxy logs and performance metrics
  • Implementing automated testing and monitoring for backend services
  • Conducting regular load testing and performance benchmarking
  • Maintaining a comprehensive incident response plan to quickly respond to performance issues.
Edit this page