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

TrueSight Cloud Cost Control provides you with actionable intelligence to handle efficiency-related issues in your infrastructure through a set of out-of-the-box recommendations. By implementing these recommendations, you can reduce your multi-cloud costs and optimally utilize the infrastructure. 

Related topics

About recommendations

A recommendation is a suggestion based on best practices about how to improve the efficiency of your infrastructure. Out-of-the-box recommendations are available for the following cloud providers and technologies:

  • Amazon Web Services (AWS)
  • Microsoft Azure (Azure)
  • On-premises
    • Hyper-V
    • VMware vSphere

Recommendations for a technology automatically start getting generated after you install TrueSight Cloud Cost Control. A recommendation is generated based on an optimizer rule that runs as per an associated schedule. You can customize the rule or create a new one to generate recommendations as per your requirements. For more information, see  Configuring alerts and recommendations .

Depending on the cloud provider (and technology in case of on-premises), configure and run the corresponding ETL modules to import data for the recommendations. For a list of ETL modules, see Collecting data

Each recommendation comprises the following elements:

  • Brief overview of the issue
  • One or more suggested actions to resolve the issue
  • Estimated monthly savings that you can achieve by performing the suggested actions

The recommendations are available in two categories. The following table lists the categories and the goals that the recommendations help you achieve:

CategoryGoals
Resource usage
  • Determine the idle or unused VMs in the infrastructure.
  • Obtain the estimated savings that can be achieved and the storage that can be reclaimed by terminating the idle VMs.
  • Determine the underutilized resources of a VM.
  • Obtain the estimated savings that can be achieved and the storage that can be reclaimed by resizing the overallocated VMs.
AWS reserved instance1Determine the number of AWS reserved instances that can be purchased to optimize your current costs

1 - Available only if you are using the AWS cloud provider. 

Resource usage recommendations

The recommendations under the Resource usage category are further classified as follows:

Idle VM

Idle VMs are virtual machines that remain running although they are not used. For example, VMs were provisioned for testing a product feature but after the testing task completed, the VMs were not decommissioned. The public cloud providers continue to charge you for the idle VMs.  

The Idle VM recommendation identifies virtual machines in your multi-cloud infrastructure that are idle or unused for a specific number of days, and also suggests actions to terminate them and the attached volumes. 

For more information about how the recommendation is generated and to know the thresholds and parameters that you can change to customize your recommendations, see Idle VM recommendation.

Overallocated VM

Overallocated VMs are virtual machines with underutilized resources (CPU, memory, or storage). Users often end up provisioning VMs with excess capacity because they are not sure of the correct size that can meet their requirements. The public cloud providers charge you for the total capacity whether you use it or not. 

The Overallocated VM recommendation identifies virtual machines in your multi-cloud infrastructure with underutilized resources, and also suggests the ideal size of the VMs so that you can reduce your costs. A VM is considered to be overallocated if the spare capacity of any of its resources is less than the specified threshold value when projected for 30 days in the future. The suggested actions in the recommendation provide the estimated savings that you can achieve by resizing the VMs. 

For more information about how the recommendation is generated and to know the thresholds and parameters that you can change to customize your recommendations, see Overallocated VM recommendation.The following video (4:50) illustrates how to use the Resource Usage page to easily identify the idle and overallocated virtual machines in your environment and use the out-of-the-box recommendations to handle them and save costs

 https://youtu.be/sfSLqh6Z80Y


To view the resource usage based recommendations 

In the navigation pane  of the TrueSight console, select Cloud Cost Control, and click the Cost Optimization tab. By default, the Resource Usage page is displayed from which you can quickly access the following recommendations:

  • Idle VMs to terminate
  • Overallocated VMs to resize

The Savings scenario with resource usage optimization section of the page provides a quick comparison between the total monthly cost of your compute resources (Compute cost) and their optimized cost.

The compute cost considers only the VMs for which utilization metrics are available. If a VM was created or powered on after the beginning of the month, its compute cost for the entire month is estimated based on the number of hours that it was utilized. For example, consider a VM was created on the 15th of the month and it has been used for two days, then the compute cost of the VM is estimated as if it was available for the entire month and the estimated monthly cost is included in the total compute cost value. By estimating the cost for the entire month, you can obtain the saving opportunities without waiting to collect data for the entire month. 

The optimized cost is discounted cost that is based on the total estimated savings that you can achieve by implementing the recommendations that are suggested on the page. The percentage value provided on the top-right corner of the Optimized cost box is the net percentage decrease in the cost after optimization. This estimated value indicates the cost-effectiveness of the optimization results.

You can filter the data on the page by using the global and page filters. To view the cost for specific providers only or for a specific month, use the global filters. Use the page filters to filter data based on domain, cost pool, and tagsFor more information about the filters, see Using filters in the TrueSight console.

You can drill down into a recommendation type for further analysis. For more information, see Analyzing the idle VMs in your multi-cloud infrastructure and Analyzing the overallocated VMs in your multi-cloud infrastructure.

AWS reserved instance recommendation

AWS reserved instances offer a significant discount compared to the on-demand pricing and also, provide a capacity reservation in a specific availability zone.  

The AWS reserved instance recommendation specifies the number of reserved instances that you must purchase to achieve cost savings. These recommendations are calculated based on the past usage of your existing AWS instances, which are charged at on-demand rates, and checks which of these on-demand instances can be reserved.

For more information about how the recommendation is generated, see AWS reserved instance recommendation.

This recommendation is available only if you are using the AWS cloud provider.

To view the AWS reserved instance recommendation

In the navigation pane  of the TrueSight console, select Cloud Cost Control, and click Cost Optimization > AWS Reserved Instances.  

The Savings scenario with AWS reserved instances section of the page provides a quick comparison between the estimated monthly cost of your AWS EC2 instances and their optimized cost.

The optimized cost is calculated based on the total estimated savings that you can achieve by purchasing the suggested number of reserved instances (AWS Reserved Instances to purchase section). The percentage value provided on the top-right corner of the Optimized cost box is the net percentage decrease in the cost after optimization. This estimated value indicates the cost-effectiveness of the optimization results.

The AWS Reserved Instances to purchase section on the AWS Reserved Instances page provides a quick overview of the number of reserved instances to be purchased and the total estimated savings that you can achieve by purchasing them. 

You can drill down into the recommendation for further analysis and details. For more information, see Analyzing recommendations for purchasing AWS reserved instances.


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