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CAST AI vs IBM Kubecost 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
13th
Average Rating
8.6
Reviews Sentiment
7.4
Number of Reviews
8
Ranking in other categories
No ranking in other categories
IBM Kubecost
Ranking in Cloud Cost Management
24th
Average Rating
9.4
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of August 2026, in the Cloud Cost Management category, the mindshare of CAST AI is 1.9%, down from 2.0% compared to the previous year. The mindshare of IBM Kubecost is 2.7%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Cost Management Mindshare Distribution
ProductMindshare (%)
CAST AI1.9%
IBM Kubecost2.7%
Other95.4%
Cloud Cost Management
 

Featured Reviews

DeepakReddy - PeerSpot reviewer
Sr.Devops engineer at Scaler
Automated cost controls have cut cloud waste and free our team to focus on new projects
CAST AI can be improved in that automation policies require careful tuning. Sometimes it can be confusing for non-technical people or managers who are not familiar with technical details. However, it is good for technical people who are already into DevOps or cloud engineering. Spot strategies may need adjustment for sensitive workloads. The reporting and UI part can be somewhat better. Technical support can also be improved. Documentation is somewhat unclear sometimes, but not everywhere. There are many pros here, including easy onboarding, simple deployment, and excellent Kubernetes visibility, strong spot instance automation, and automated right-sizing. These features are very good for our organization because they reduce a lot of cost and reduce a lot of manual effort. However, some things can be improved, such as automation policies that require careful tuning and may need somewhat more help. Spot strategies can be improved, and some UI and documentation can also be improved.
DIRK UYTTERHOEVEN - PeerSpot reviewer
Senior Enterprise Architect at DV Consulting
Identifies and eliminates overprovisioning of expensive resources like storage, highly scalable and offers performance
I like the overall product because I can select what monitoring should be enabled and whatnot. In our case, we really focus on performance because it's clear that the price is related to most performance setups. So the more performance, the more expensive. So we look into the performance that the customer needs, and then based upon that feedback from the remote control, we change the parameters. And even the end user will not notice it is not using it, so we just make money without any impact on the end users.

Quotes from Members

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

Pros

"In terms of cost savings, we have currently reduced our costs by 30 to 40%, and it saves time while managing infrastructure because it continuously monitors and provides the nodes to the application, so we don't need to do anything ourselves."
"In the last Q2 result, because of using CAST AI, we have reduced our manpower, money, and cost by 20 to 30%, which indicates substantial funding reduction."
"Since using CAST AI, we have achieved approximately 30 to 40 percent reduction in our Kubernetes infrastructure cost."
"Since adopting CAST AI, we achieved approximately 30-40% reduction in Kubernetes infrastructure costs."
"CAST AI positively impacted our organization by leading the migration of a very high number of pre-production environments from VMs to Kubernetes."
"CAST AI monitors the workloads in the cluster and optimizes the number of nodes needed, their CPU and their memory so that we pay as little as possible."
"CAST AI's machine learning algorithms that listen to the data generated by the cluster in order to optimize the workloads are among the best features offered."
"Overall, CAST AI has been a valuable addition to our Kubernetes platform operations."
"The price is reasonable, considering the value it delivers."
"I mostly like the dashboards."
"It offers a detailed examination of your cluster, including the types of instances utilized, allocated CPU and RAM, and resource distribution for specific applications."
 

Cons

"The limitations of CAST AI include reporting and customization options."
"CAST AI can be improved in that automation policies require careful tuning."
"CAST AI could be improved by adding some AI agent capabilities."
"Perhaps improving the documentation a little would allow it to reach that rating, which has benefited me regarding that specific focus."
"I would like to see CAST AI improved with deeper and more intelligent answers and solutions, along with additional optimization and customization options."
"CAST AI can be improved by managing the role-based access control better."
"I would like to see more granular reporting, deeper cost allocation insights, and additional customization options for optimization policies in CAST AI."
"To improve CAST AI, I would like to see more granular reporting, deeper cost allocation insights, and additional customization options for optimization policies."
"Faster monitoring could potentially improve overall stability in the production environment."
"There is a significant potential for enhancing it through the incorporation of advanced technologies like AI and generative AI."
"The integration with other solutions could be improved."
 

Pricing and Cost Advice

Information not available
"The real savings come from using Kubecost features like autoscaling and serverless functions to optimize your resource usage. If you treat it like a data center migration without fine-tuning, it might cost more."
"The cost of the tool may seem nominal compared to the potential savings in infrastructure expenses."
"The cost is cheap. Kubecost has an open-source core."
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Top Industries

By visitors reading reviews
Outsourcing Company
26%
Energy/Utilities Company
12%
Construction Company
9%
Educational Organization
8%
Financial Services Firm
15%
Construction Company
14%
Manufacturing Company
11%
Insurance Company
11%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business10
Midsize Enterprise3
Large Enterprise3
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for CAST AI?
My experience with pricing, setup cost, and licensing was that the proposal they shared with us included an ongoing monthly cost. There was a one-time setup cost as well, but all that we spent with...
What needs improvement with CAST AI?
CAST AI can be improved by managing the role-based access control better. I think it would be better for CAST AI to improve how access permissions are handled for developers. That would be a benefi...
What is your primary use case for CAST AI?
My main use case was to migrate development and staging environments to Kubernetes using CAST AI, and with them, we created these environments. We moved them from virtual machines to Kubernetes clu...
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Comparisons

 

Also Known As

No data available
Kubecost - Amazon EKS cost monitoring
 

Overview

Find out what your peers are saying about CAST AI vs. IBM Kubecost and other solutions. Updated: August 2026.
909,725 professionals have used our research since 2012.