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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 (3rd), Cloud Management (4th), Virtualization Management Tools (4th), IT Financial Management (1st), IT Operations Analytics (5th), Cloud Analytics (1st), AIOps (11th)
 

Mindshare comparison

As of February 2026, in the Cloud Cost Management category, the mindshare of CAST AI is 1.5%, up from 1.5% compared to the previous year. The mindshare of IBM Turbonomic is 6.3%, down from 14.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Cost Management Market Share Distribution
ProductMarket Share (%)
IBM Turbonomic6.3%
CAST AI1.5%
Other92.2%
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."
"Turbonomic helps us right-size virtual machines to utilize the available infrastructure components available and suggest where resources should exist. We also use the predictive tool to forecast what will happen when we add additional compute-demanding virtual machines or something to the environment. It shows us how that would impact existing resources. All of that frees up time that would otherwise be spent on manual calculation."
"Rightsizing is valuable. Its recommendations are pretty good."
"On-premises, one advantage I find particularly appealing is the ability to create policies for automatic CPU and memory scaling based on demand."
"We have VM placement in Automated mode and currently have all other metrics in Recommend mode."
"We have seen a 30% performance improvement overall."
"I only deal with the infrastructure side, so I really couldn't speak to more than load balancing as the most valuable feature for me. It provides specific actions that prevent resource starvation. It always keeps things in perfect balance."
"It became obvious to us that there was a lot more being offered in the product that we could leverage to ensure our VMware environment was running efficiently."
"The ability to monitor and automate both the right-sizing of VMs as well as to automate the vMotion of VMs across ESXi hosts."
 

Cons

"The documentation of CAST AI can definitely be improved for first-time users."
"There are a few things that we did notice. It does kind of seem to run away from itself a little bit. It does seem to have a mind of its own sometimes. It goes out there and just kind of goes crazy. There needs to be something that kind of throttles things back a little bit. I have personally seen where we've been working on things, then pulled servers out of the VMware cluster and found that Turbonomic was still trying to ship resources to and from that node. So, there has to be some kind of throttling or ability for it to not be so buggy in that area. Because we've pulled nodes out of a cluster into maintenance mode, then brought it back up, and it tried to put workloads on that outside of a cluster. There may be something that is available for this, but it seems very kludgy to me."
"Additional interfaces would be helpful."
"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 one point is the reporting. We do have reports out of it, but they're not the level of graphical detail I would like."
"I like the detail I get in the old user interface and will miss some of that in the new interface when we perform our planned upgrade soon."
"It would be good for Turbonomic, on their side, to integrate with other companies like AppDynamics or SolarWinds or other monitoring softwares. I feel that the actual monitoring of applications, mixed in with their abilities, would help. That would be the case wherever Turbonomic lacks the ability to monitor an application or in cases where applications are so customized that it's not going to be able to handle them. There is monitoring that you can do with scripting that you may not be able to do with Turbonomic."
"Some features are only available via changes to the deployment YAML, and it would be better to have them in the UI."
"The old interface was not the clearest UI in some areas, and could be quite intimidating when first using the tool."
 

Pricing and Cost Advice

Information not available
"What I can advise is to trial the product, taking advantage of the Turbonomic pre-sales implemention support and kickstart training."
"I'm not involved in any of the billing, but my understanding is that is fairly expensive."
"The pricing is in line with the other solutions that we have. It's not a bargain software, nor is it overly expensive."
"The product is fairly priced right now. Given its capabilities, it is excellently priced. We think that the product will become self-funding because we will be able to maximize our resources, which will help us from a capacity perspective. That should save us money in the long run."
"If you're a super-small business, it may be a little bit pricey for you... But in large, enterprise companies where money is, maybe, less of an issue, Turbonomic is not that expensive. I can't imagine why any big company would not buy it, for what it does."
"IBM Turbonomic is an investment that we believe will deliver positive returns."
"I don't know the current prices, but I like how the licensing is based on the number of instances instead of sockets, clusters, or cores. We have some VMs that are so heavy I can only fit four on one server. It's not cost-effective if we have to pay more for those. When I move around a VM SQL box with 30 cores and a half-terabyte of RAM, I'm not paying for an entire socket and cores where people assume you have at least 10 or 20 VMs on that socket for that pricing."
"It's worth the time and money investment if you can afford it."
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Top Industries

By visitors reading reviews
No data available
Financial Services Firm
10%
Computer Software Company
10%
Manufacturing Company
9%
Insurance Company
6%
 

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: January 2026.
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