Overallocated VM recommendation

The Overallocated VM recommendation identifies virtual machines (VMs) with underutilized resources (CPU, memory, or storage). A VM is detected to be overallocated if the spare capacity of its resources (CPU, memory, storage) exceeds the corresponding threshold. The spare capacity of a resource is the difference between its actual configured value and its estimated future usage value. 

The Overallocated VM recommendation is available for these technologies: AWS, Azure, and GCP.

For details on the Kubernetes Overallocated Containers recommendations, see Kubernetes-Overallocated-containers-recommendation.

Related topic

Resolving-capacity-risk-and-efficiency-issues-by-using-recommendations

The following recommendation details are provided:

  • Recommended action that suggests reconfiguring the VM with the ideal configuration values to save costs. For a source VM that is in the public cloud, the recommended instance type for the target VM belongs to the same family as that of the source. For example, if the source VM is of type General Purpose - M4, then the recommended target instance can belong to M3 or M5, depending on the computed ideal size.
  • Comparison showing the difference between the current utilization of VM resources and their utilization after reconfiguring the VM
  • Criteria for detecting the VM as overallocated
  • Benefits of implementing the recommendation
  • Accuracy icon that indicates the accuracy or reliability of the resizing suggestion given in the recommended actions. The accuracy level shown in the icon is based on the selected Optimization behavior. For more information about the accuracy levels, see Troubleshooting resizing recommendations for overallocated VMs.

You can analyze these recommendation details and take any of these actions:

  • Reconfigure the VM with the recommended values to reclaim storage and achieve cost savings
  • Increase the VM load by allocating additional applications to improve the VM capacity utilization

overallocated_recommendation_details.png

The recommendation rule is based on these thresholds in the Optimizer rule:

  • Spare CPU (Cores)
  • Spare Memory (GB)
  • Spare Storage (GB)

You can change the default values of these thresholds on the Rules page in the Helix Capacity Optimization Console.

overallocated_recommendation_thresholds.png

For more information about modifying the Optimizer rules, see Configuring-and-managing-Optimizer-rules.

 

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