Overallocated VM recommendation

The Overallocated VM recommendation identifies virtual machines (VMs) with underutilized resources (CPU, memory, or storage).

The recommended action specifies the resource identifier of the overallocated VM (source VM) and suggests an ideal size for the VM (target VM) to avoid wastage and reduce 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. 

Overallocated VM detection

A VM is detected to be overallocated if the spare capacity of its resources (CPU, memory, storage) exceeds the corresponding threshold (specified in the Optimizer rule). 

The spare capacity of a resource is the difference between its actual configured value and its estimated future usage value. You can reconfigure or modify the spare capacity thresholds in the Optimizer rule.

The following table lists the default values of the configuration parameters that are used to generate the recommendation and links to topics that explain how you can reconfigure or modify them.

Parameter

How-to resource

Indicator thresholds

vSphere VM Active Memory increase factor = 50 %

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Parameters and thresholds in the Optimizer rule (Conditions section)
  • Spare CPU threshold = 5 GHz
  • Spare memory threshold = 1 GB
  • Spare storage threshold = 5 GB

Configuring and managing Optimizer rules Open link

Ideal size computation of the target VM 

The ideal size of the target VM is suggested 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  demand indicator Open link .  

For VMs that are provisioned in the 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 behaviorDescription
Aggressive

Resource utilization in the server is computed by considering the average value of the hourly samples. 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. Spikes in the resource utilization within the hour are not considered.

This optimization behavior does not require the server to be instrumented because granular or detailed metrics are not used for the computation.

Balanced (Default)

CPU utilization in the server is computed by considering the 90th percentile value of hourly samples. Then, 95th percentile of the hourly value over the last 30 days is computed for CPU to generate the configuration of the target virtual machine or instance type. 90% of spikes in the CPU utilization within the hour are considered.

Utilization of memory and storage is computed by considering the 95th percentile of the average hourly values over the last 30 days.

This optimization behavior requires the server to be instrumented to collect the granular or detailed metrics. For VMware vSphere, the server need not be instrumented because the vSphere Service ETL collects data at less than one minute granularity.

Conservative

CPU utilization in the server is computed by considering the 95th percentile value of hourly samples. Then, 95th percentile of the hourly value over the last 30 days is computed for CPU to generate the configuration of the target virtual machine or instance type. 95% of spikes in the CPU utilization within the hour are considered.

Utilization of memory and storage is computed by considering the 95th percentile of the average hourly values over the last 30 days.

This optimization behavior requires the server to be instrumented to collect the granular or detailed metrics. For VMware vSphere, the server need not be instrumented because the vSphere Service ETL collects data at less than one minute granularity.

The computed resource utilization values are stored in the demand indicators (CPU Demand, Memory Demand, and Storage Demand). For more information, see Indicators Open link .

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.

For information about the data sources that enable you to collect metrics for the optimization behaviors, see Data source requirements for VM resizing.

Other recommendation details

  • The recommendation is assigned an efficiency level (high, medium, or low) based on the amount of estimated cost savings per month.

    You can define thresholds to configure the efficiency level of a recommendation in the Optimizer rule (Conditions section).

    Thresholds with default valuesHow-to resource
    • Mark as 'high' efficiency if the estimated monthly cost savings exceed = $50
    • Mark as 'medium' efficiency if the estimated monthly cost savings exceed = $25

    Based on the default settings, a recommendation is assigned an efficiency level as explained in the following table:

    Efficiency levelEstimated savings amount (in $) per month
    high$50 or more
    mediumBetween $25 - $49
    lowLess than $25
    Configuring and managing Optimizer rules Open link

Where to go from here

For instructions about viewing the overallocated VM recommendations, see Analyzing the overallocated VMs in your multi-cloud infrastructure.

Related topics

Optimizing multi-cloud costs with out-of-the-box recommendations

Recommendation types

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