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CAST AI vs IBM Turbonomic comparison

 

Comparison Buyer's Guide

Executive Summary

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

CAST AI
Ranking in Cloud Cost Management
19th
Average Rating
8.0
Reviews Sentiment
9.2
Number of Reviews
1
Ranking in other categories
No ranking in other categories
IBM Turbonomic
Ranking in Cloud Cost Management
1st
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
205
Ranking in other categories
Cloud Migration (6th), Cloud Management (5th), Virtualization Management Tools (4th), IT Financial Management (1st), IT Operations Analytics (5th), Cloud Analytics (1st), AIOps (11th)
 

Mindshare comparison

As of January 2026, in the Cloud Cost Management category, the mindshare of CAST AI is 1.8%, up from 1.6% compared to the previous year. The mindshare of IBM Turbonomic is 6.2%, down from 14.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Cost Management Market Share Distribution
ProductMarket Share (%)
IBM Turbonomic6.2%
CAST AI1.8%
Other92.0%
Cloud Cost Management
 

Featured Reviews

RA
Global Head - DevOps and AIOps Startegist at a manufacturing company with 10,001+ employees
Automation has optimized Kubernetes costs and right-sizing cuts manual cluster work
CAST AI helps us with automated node provisioning, workload right-sizing, intelligent auto-scaling, and overall cost visibility of the containerized systems that we have on the cloud. The best features CAST AI offers are the Kubernetes auto-scaling mechanism, continuous analysis of the pod-level CPU and memory usage, and ensuring that workload right-sizing is being done and our nodes are not over-provisioned. Identifying inaccuracies in the resource request is what we find quite useful with CAST AI. It definitely saves time and money as well, along with peace of mind because CAST AI continuously analyzes the pod-level CPU and memory usages. This helps us to optimize the request and the limits adjustments on our usage pattern, and overall, right-sizing improves the packing and reduces the wasted compute that we have in the cloud. In terms of overall impact on the organization, CAST AI has definitely helped us optimize our Kubernetes resources and given us automation capabilities. It is definitely helping us reduce the manpower and overall compute which is wasted. We can definitely save these using CAST AI. We will be notified upfront and proactively about any wastages that are happening, or any cost leakages that are happening in our system.
Dan Ambrose - PeerSpot reviewer
Infrastructure Engineer 4 at a tech vendor with 1,001-5,000 employees
Helps visibility, bridges the data gap, and frees up time
We use IBM Turbonomic in a hybrid cloud environment. Although it supports multi-cloud capabilities, we currently operate in a single-cloud setting. Turbonomic offers visibility into our environment's performance, spanning across applications, underlying infrastructure, and protection resources. The visibility and analytics help to bridge the data gap between disparate IT teams such as applications and infrastructure. This is important for awareness collaboration, cost saving, and helping to design and improve our application. Enhanced visibility and data analytics have contributed to a significant reduction in our mean time to resolve. Tools like Turbonomic provide crucial visualization and insights, empowering us to make data-driven decisions instead of relying on assumptions as we did before. This newfound transparency translates to a massive improvement, going from complete darkness to having a clear 100 percent view of the situation. Although our applications are not optimized for the cloud we have seen some improvement in response time. IBM Turbonomic empowers us to achieve more with fewer people thanks to automation. Previously, customers frequently contacted us requesting resource increases to resolve issues. Now, we have a tool that allows us to objectively assess their needs, leading to a deeper understanding of our applications. This solution also generates significant cost savings in the cloud and optimizes hardware utilization within our data centers. Its AI algorithm intelligently allocates servers on hosts, maximizing efficiency without compromising performance. By fine-tuning resource allocation without causing performance bottlenecks, Turbonomic extends the lifespan of existing hardware, postponing the need for new purchases. This effectively stretches our capital expenditure budget. We started to see the benefits of IBM Turbonomic within the first 60 days. IBM is a fantastic partner. Their tech support has been outstanding, and the product itself is excellent - a very solid offering. By automating resource management with Turbonomic, our engineers are freed up to focus on more strategic initiatives like innovation and ongoing organizational projects. Previously, manually adding resources was a time-consuming process that interrupted workflows. Now, automation handles scaling efficiently, saving us thousands of man-hours and significant costs. It has illuminated the need for SetOps. It has highlighted areas of overspending, and the actions we've taken have demonstrated significant cost savings. IBM Turbonomic has positively impacted our overall application performance. IBM Turbonomic has helped reduce both CAPEX and OPEX. It has also significantly reduced cloud build times.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"We observed a 20 to 30% reduction in Kubernetes infrastructure cost, node utilization is improved, and we could see a 60 to 70% reduction in our manual cluster optimization efforts that we used to put initially."
"I have the ability to automate things similar to the Orchestrator stuff. I do have the ability to have it do some balancing, and if it sees some different performance metrics that I've set not being met, it'll actually move some of my virtual machines from, let's say, one host to another. It is sort of an automation tool that helps me. Basically, I specify the metric, and if I get a certain host or something being over-utilized, it'll automatically move the virtual machines around for me. It basically has to snap into my vCenter and then it can make adjustments and move my virtual machines around. It also has some very nice reporting tools built around virtual machines. It tells you how much storage, memory, or CPU is being used monthly, and then it gives you a very nice way to be able to send out billing structure to your end users who use servers within your environment."
"The most valuable features are the cluster utilization reports and the resource capacity planning. We can simulate how much capacity we can add to the current resources. The individual DM reports and VM-facing recommendations report are also helpful."
"I like Turbonomic's built-in reporting. It provides a ton of information out of the box, so I don't have to build panels for the monthly summaries and other reports I need to present to management. We get better performance and bottleneck reporting from this than we do from our older EMC software."
"The feature for optimizing VMs is the most valuable because a number of the agencies have workloads or VMs that are not really being used. Turbonomic enables us to say, 'If you combine these, or if you decide to go with a reserve instance, you will save this much.'"
"Turbonomic can show us if we're not using some of our storage volumes efficiently in AWS. For example, if we've over-provisioned one of our virtual machines to have dedicated IOPs that it doesn't need, Turbonomic will detect that and tell us."
"The solution has a good optimization feature."
"The tool provides the ability to look at the consumption utilization over a period of time and determine if we need to change that resource allocation based on the actual workload consumption, as opposed to how IT has configured it. Therefore, we have come to realize that a lot of our workloads are overprovisioned, and we are spending more money in the public cloud than we need to."
"My favorite part of the solution is the automation scheduling. Being able to choose when actions happen, and how they happen..."
 

Cons

"The documentation of CAST AI can definitely be improved for first-time users."
"Turbonomic doesn't do storage placement how I would prefer. We use multiple shared storage volumes on VMware, so I don't have one big disk. I have lots of disks that I can place VMs on, and that consumes IOPS from the disk subsystem. We were getting recommendations to provision a new volume."
"The implementation could be enhanced."
"After running this solution in production for a year, we may want a more granular approach to how we utilize the product because we are planning to use some of its metrics to feed into our financial system."
"It can be more agnostic in terms of the solutions that it provides. It can include some other cost-saving methods for the public cloud and SaaS applications as well."
"The reporting needs to be improved. It's important for us to know and be able to look back on what happened and why certain decisions were made, and we want to use a custom report for this."
"The issue for us with the automation is we are considering starting to do the hot adds, but there are some problems with Windows Server 2019 and hot adds. It is a little buggy. So, if we turn that on with a cluster that has a lot of Windows 2019 Servers, then we would see a blue screen along with a lot of applications as well. Depending on what you are adding, cores or memory, it doesn't necessarily even take advantage of that at that moment. A reboot may be required, and we can't do that until later. So, that decreases the benefit of the real-time. For us, there is a lot of risk with real-time."
"It would be nice for them to have a way to do something with physical machines, but I know that is not their strength Thankfully, the majority of our environment is virtual, but it would be nice to see this type of technology across some other platforms. It would be nice to have capacity planning across physical machines."
"The management interface seems to be designed for high-resolution screens. Somebody with a smaller-resolution screen might not like the web interface. I run a 4K monitor on it, so everything fits on the screen. With a lower resolution like 1080, you need to scroll a lot. Everything is in smaller windows. It doesn't seem to be designed for smaller screens."
 

Pricing and Cost Advice

Information not available
"We felt the pricing was very fair for the product. It is in no way prohibitive for larger deployments, unlike other similar product on the market."
"You should understand the cost of your physical servers and how much time and money you are spending year over year on expanding your virtual farm."
"We see ROI in extended support agreements (ESA) for old software. Migration activities seem to be where Turbonomic has really benefited us the most. It's one click and done. We have new machines ready to go with Turbonomic, which are properly sized instead of somebody sitting there with a spreadsheet and guessing. So, my return on investment would certainly be on currency, from a software and hardware perspective."
"IBM Turbonomic is an investment that we believe will deliver positive returns."
"Contact the Turbonomic sales team, explain your needs and what you're looking to monitor. They will get a pre-sales SE on the phone and together work up a very accurate quote."
"I know there have been some issues with the billing, when the numbers were first proposed, as to how much we would save. There was a huge miscommunication on our part. Turbonomic was led to believe that we could optimize our AWS footprint, because we didn't know we couldn't. So, we were promised savings of $750,000. Then, when we came to implement Turbonomic, the developers in AWS said, "Absolutely not. You're not putting that in our environment. We can't scale down anything because they coded it." Our AWS environment is a legacy environment. It has all these old applications, where all the developers who have made it are no longer with the company. Those applications generate a ton of money for us. So, if one breaks, we are really in trouble and they didn't want to have to deal with an environment that was changing and couldn't be supported. That number went from $750,000 to about $450,000. However, that wasn't Turbonomic's fault."
"The pricing is in line with the other solutions that we have. It's not a bargain software, nor is it overly expensive."
"I consider the pricing to be high."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
11%
Computer Software Company
11%
Manufacturing Company
9%
Insurance Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
By reviewers
Company SizeCount
Small Business41
Midsize Enterprise57
Large Enterprise147
 

Questions from the Community

What is your experience regarding pricing and costs for CAST AI?
In terms of setup cost, licensing, and pricing, I find the experience good. It's enterprise-grade, and the pricing is usage-based with no heavy upfront setup cost, which makes the onboarding straig...
What needs improvement with CAST AI?
The documentation of CAST AI can definitely be improved for first-time users. When we are onboarding a new user, the team needs some time to tune the policies and build confidence in automation bec...
What is your primary use case for CAST AI?
Our main use case for CAST AI is that we use it as a cloud provider and for Kubernetes clusters. We are using secure access roles and all those requirements for right-sizing the containers' workloa...
What is your experience regarding pricing and costs for Turbonomic?
It offers different scenarios. It provides more capabilities than many other tools available. Typically, its price is set as a percentage of the consumption of some of our customers' services. The ...
What needs improvement with Turbonomic?
The implementation could be enhanced.
What is your primary use case for Turbonomic?
We use IBM Turbonomic to automate our cloud operations, including monitoring, consolidating dashboards, and reporting. This helps us get a consolidated view of all customer spending into a single d...
 

Also Known As

No data available
Turbonomic, VMTurbo Operations Manager
 

Interactive Demo

Demo not available
 

Overview

 

Sample Customers

Information Not Available
IBM, J.B. Hunt, BBC, The Capita Group, SulAmérica, Rabobank, PROS, ThinkON, O.C. Tanner Co.
Find out what your peers are saying about IBM, Nutanix, Apptio and others in Cloud Cost Management. Updated: December 2025.
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