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, Hyper-V, OpenStack, and vSphere

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

You can analyse 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 Adding-a-template-based-Optimizer-rule.

The Memory Demand indicator is used to determine whether a VM is overallocated. For vSphere VMs, this indicator is computed by considering the 95th percentile value of the MEM_REAL_UTIL or MEM_ACTIVE metrics. When using the MEM_ACTIVE metric, the vSphere VM Active Memory increase factor is applied to increase the MEM_ACTIVE metric value. For more information about the Memory Demand indicator, see Indicators.

You can change the value of the vSphere VM Active Memory increase factor on the Thresholds page in the Helix Capacity Optimization Console.

overallocated_recommendation_indicator_threshold.png


For more information about configuring thresholds, see Configuring-and-managing-thresholds-for-metrics-and-indicators.

Ideal size computation of the target VM

The ideal size of the target VM is calculated by considering the estimated future usage and the estimated past usage of the resources. The estimated past usage value of each resource is computed based on the selected Optimization behavior (Aggressive, Balanced, Conservative) and stored in the corresponding Indicators.  

For VMs that are provisioned in a public cloud, the resizing recommendation for the CPU resource also considers CPU benchmark. The estimated CPU benchmark value of the source VM is compared with that of the probable target VMs and the VM with the best match is recommended. 

If the CPU benchmark value for the source VM is unavailable, then the resizing recommendation is generated without considering benchmarks. SPECint_rate2006 is used as the reference benchmark to compare the hardware of the source and target VMs. The CPU benchmark consideration is to ensure that the suggested target VM performs at the same computing power as that of the source VM, even if the hardware is different. 

Past usage estimation

The following table explains how the past usage is computed per optimization behavior:

Optimization behavior

Description

Aggressive

Resource utilization in the server is computed by considering the average value of hourly samples. Spikes in the resource utilization within the hour are not considered. Then, 95th percentile of the hourly value over the last 30 days is computed for each resource to generate the configuration of the target virtual machine or instance type.

Balanced (Default)

Resource utilization in the server is computed by considering the 90th percentile value of hourly samples. Only 10% of spikes in the utilization within the hour are not considered. Then, 95th percentile of the hourly value over the last 30 days is computed for each resource to generate the configuration of the target virtual machine or instance type.

Conservative

Resource utilization in the server is computed by considering the 99th percentile value of hourly samples. Only 1% of spikes in the utilization within the hour are not considered. Then, 95th percentile of the hourly value over the last 30 days is computed for each resource to generate the configuration of the target virtual machine or instance type.

Information

If you select the Conservative or Balanced optimization behavior for a server that is not instrumented, the results are based on the Aggressive behavior.

BMC recommends the Conservative behavior for servers that are running business-critical applications.

Other recommendation details

The Overallocated VM recommendation window displays an 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.

To modify the Optimization behavior

For more information about how to modify the optimization behavior, see the following topics:

Where to go from here

To view the overallocated VM recommendations, see the Recommendations page of the capacity view of the supported cloud provider and technology:

Related topics

Using-recommendations-to-resolve-capacity-risk-and-efficiency-issues

Using

 

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