WindowsServerMemoryUsage

WindowsServerMemoryUsage #

Memory usage is more than 90%

Alert Rule
alert: WindowsServerMemoryUsage
annotations:
  description: |-
    Memory usage is more than 90%
      VALUE = {{ $value }}
      LABELS = {{ $labels }}    
  runbook: https://srerun.github.io/prometheus-alerts/runbooks/windows-exporter/windowsservermemoryusage/
  summary: Windows Server memory Usage (instance {{ $labels.instance }})
expr: 100 - ((windows_os_physical_memory_free_bytes / windows_cs_physical_memory_bytes)
  * 100) > 90
for: 2m
labels:
  severity: warning

Here is a runbook for the WindowsServerMemoryUsage alert rule:

Meaning #

The WindowsServerMemoryUsage alert indicates that the memory usage on a Windows server has exceeded 90%. This can lead to performance issues, slow response times, and even crashes if left unchecked.

Impact #

High memory usage can significantly impact the performance and reliability of the Windows server, leading to:

  • Slow application response times
  • Increased CPU usage
  • Reduced system stability
  • Potential crashes or freezes
  • Impaired user experience

Diagnosis #

To diagnose the issue, follow these steps:

  1. Verify the alert: Check the Prometheus graph to confirm that the memory usage is indeed above 90%.
  2. Check system logs: Review system logs to identify any error messages or warnings related to memory issues.
  3. Investigate running processes: Use tools like Task Manager or Process Explorer to identify which processes are consuming the most memory.
  4. Check for memory leaks: Look for any signs of memory leaks or abnormal memory usage patterns.
  5. Verify system configuration: Check the system configuration to ensure that memory settings are adequate for the server’s workload.

Mitigation #

To mitigate the issue, follow these steps:

  1. Identify and terminate unnecessary processes: Terminate any unnecessary processes consuming excessive memory.
  2. Optimize system configuration: Adjust system configuration settings to optimize memory usage for the server’s workload.
  3. Implement memory monitoring: Set up regular memory usage monitoring to detect potential issues before they become critical.
  4. Consider capacity planning: Review capacity planning to ensure the server has sufficient resources to handle its workload.
  5. Apply OS and software updates: Ensure the operating system and software are up-to-date, as newer versions may include memory-related performance optimizations.
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