Update NodeMemoryMajorPagesFaults.md

content/runbooks/node/NodeMemoryMajorPagesFaults.md

@@ -7,25 +7,30 @@ weight: 20
 
 ## Meaning
 
-Memory major pages are occurring at very high rate at {{ $labels.instance }}, 500 major page faults per second for the last 15 minutes, is currently at {{ printf "%.2f" $value }}.
-Please check that there is enough memory available at this instance.
+The `NodeMemoryMajorPagesFaults` alert is triggered when a Kubernetes node experiences a significant number of major page faults, indicating issues with memory access. This could be due to excessive swapping of memory pages to the swap area or general memory problems.
+
+As shown here: 
+[Kubernetes-Mixin](https://monitoring.mixins.dev/node-exporter/)
+> Memory major pages are occurring at very high rate at {{ $labels.instance }}, 500 major page faults per second for the last 15 minutes, is currently at {{ printf "%.2f" $value }}. 
+>
+> Please check that there is enough memory available at this instance. 
 
 ## Impact
 
-The high rate of memory major pages faults indicates potential issues with memory management on the instance, which could lead to degraded performance or even service disruptions.
+- Possible performance degradation for applications running on the affected Kubernetes node.
+- Increased latency for memory accesses.
+- Risk of application crashes or errors due to memory overload.
 
 ## Diagnosis
 
-1. **Check Memory Usage**: Review the memory usage statistics on the instance to determine if memory is being exhausted.
-2. **Identify Resource-Intensive Processes**: Identify any processes or applications that are consuming large amounts of memory.
-3. **Review System Logs**: Check system logs for any error messages related to memory allocation or paging.
-4. **Analyze Historical Data**: Review historical metrics data to identify any recent changes or trends in memory usage.
-5. **Check for Memory Leaks**: Investigate for any memory leaks in applications running on the instance.
+1. Check the utilization of physical memory (RAM) and swap space on the affected Kubernetes node.
+2. Examine the memory profiles of running applications to determine which processes are consuming memory.
+3. Monitor memory usage over time to identify trends and peak loads.
+
 
 ## Mitigation
 
-1. **Increase Memory**: Consider increasing the memory allocation for the instance to provide more resources for applications and processes.
-2. **Optimize Applications**: Optimize memory usage within applications to reduce the likelihood of memory exhaustion.
-3. **Restart Services**: If possible, restart any services or applications that are consuming excessive memory to free up resources.
-4. **Monitor and Tune**: Continuously monitor memory usage and tune system parameters as needed to ensure optimal performance.
-5. **Alerting**: Set up alerts to notify administrators when memory usage exceeds certain thresholds to proactively address potential issues.
+1. Optimize the resource utilization of running applications by stopping unnecessary processes or adjusting their resource requirements.
+2. Review Kubernetes resource requests and limits configuration to ensure they match the actual requirements of the applications.
+3. Scale the resources of the Kubernetes node as needed by adding additional memory or increasing node capacity.
+4. Optimize swap configuration to ensure efficient utilization while minimizing the impact of swapping on performance.