Kubernetes - Oversubscribed clusters recommendation
The Oversubscribed clusters recommendation identifies Kubernetes clusters that are oversubscribed.
You can configure a recommendation as per your requirement by modifying the condition in the corresponding Optimizer rule. A user with administrative privileges can reconfigure or add new Optimizer rules to modify the recommendations. For more information, see Configuring and managing Optimizer rules.
The following details are provided in the recommendation:
- Number of days that are remaining for the resources saturation
- Severity or Efficiency level of the recommendation. The thresholds for calculating the efficiency level is defined in the associated optimizer rule.
- Date when this recommendation is generated on. It is the date of the last run of the associated optimizer rule.
- Name of the associated optimizer rule
- Recommended actions to resolve the resource saturation
- Actions that you can perform on your recommendations. For details, see Managing the recommendations.
- Comparison between the current resource usage and trend and the estimated future usage after reconfiguring the system
- Criteria used for generating the recommendation
- Benefits of implementing the recommendation
A cluster is detected to be oversubscribed if the configured limit for resources (CPU, Memory) exceeds the total resources available by more than the threshold values:
- CPU Overcommitment
- Memory Overcommitment
Overcommitment is the ratio of configured limit and the total resources available in the cluster expressed as a percentage. High overcommitment for CPU can cause the processer throttle and result in performance degradation. High overcommitment of memory can lead to performance degradation. You can change the default values of these thresholds on the Rules page in the Administration > Optimizer section.
For more information about modifying the Optimizer rules, see Configuring and managing Optimizer rules.
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