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CAST AI vs PerfectScale comparison

Why PeerSpot?
 

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
PerfectScale
Ranking in Cloud Cost Management
22nd
Average Rating
9.4
Reviews Sentiment
1.7
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of September 2026, in the Cloud Cost Management category, the mindshare of CAST AI is 2.1%, down from 2.1% compared to the previous year. The mindshare of PerfectScale is 1.9%, up from 0.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Cloud Cost Management Mindshare Distribution
ProductMindshare (%)
CAST AI2.1%
PerfectScale1.9%
Other96.0%
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.
reviewer2750058 - PeerSpot reviewer
DevOps & FinOps Engineer at a tech vendor with 501-1,000 employees
Gain visibility into Kubernetes clusters and optimize resource allocation based on historical data
I think they should focus more on Kubernetes features that allow on-the-fly resource allocation without the need to restart services. They should implement this in their autoscaler to make it more useful in scenarios that require immediate scaling up or down. They should also offer more options for visualizing graphs in different ways, such as tabular views.

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."
"Since using CAST AI, we have achieved approximately 30 to 40 percent reduction in our Kubernetes infrastructure cost."
"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."
"CAST AI has reduced approximately 40% of our AWS bills and AWS cloud bills, really impacting our organization positively and enabling us to use our cloud better."
"Overall, CAST AI has been a valuable addition to our Kubernetes platform operations."
"Since adopting CAST AI, we achieved approximately 30-40% reduction in Kubernetes infrastructure costs."
"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 positively impacted our organization by leading the migration of a very high number of pre-production environments from VMs to Kubernetes."
"PerfectScale made our Kubernetes optimization effortless; it found wasted resources, lowered our cloud costs, and improved performance almost instantly."
"The cluster and workload autoscaler gives us the ability to have control over all the workloads' resources instead of managing them one by one."
"Automated resource optimization using different policies based on the environment enabled the organization to achieve infrastructure cost savings."
 

Cons

"CAST AI could be improved by adding some AI agent capabilities."
"The reason I did not give it a perfect score is that I would still prefer to see more advanced cost reporting and workload-level analytics."
"CAST AI can be improved in that automation policies require careful tuning."
"I would like to see more granular reporting, deeper cost allocation insights, and additional customization options for optimization policies in CAST AI."
"The limitations of CAST AI include reporting and customization options."
"Perhaps improving the documentation a little would allow it to reach that rating, which has benefited me regarding that specific focus."
"To improve CAST AI, I would like to see more granular reporting, deeper cost allocation insights, and additional customization options for optimization policies."
"CAST AI can be improved by managing the role-based access control better."
"I think they should focus more on Kubernetes features that allow on-the-fly resource allocation without the need to restart services."
"With their in-place optimisations, stateful set optimisation would be a great addition."
"At the beginning, the support was not very impressive."
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Top Industries

By visitors reading reviews
Outsourcing Company
26%
Energy/Utilities Company
12%
Financial Services Firm
9%
Construction Company
8%
Insurance Company
30%
Construction Company
25%
Comms Service Provider
10%
Healthcare Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business10
Midsize Enterprise3
Large Enterprise4
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...
What needs improvement with PerfectScale?
With their in-place optimisations, stateful set optimisation would be a great addition.
 

Comparisons

 

Overview

Find out what your peers are saying about CAST AI vs. PerfectScale and other solutions. Updated: August 2026.
911,602 professionals have used our research since 2012.