Sold by: Cast AI
Deployed on AWS
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Get EKS monitoring and automated cost optimization in one easy-to-use platform. We show you how much you spend on EKS, and then we reduce your cost by 50 to 75% automatically. With active smart and automated rightsizing and pricing arbitrage, your cluster is continuously efficient.
4.6
Overview
Stay on top of your EKS Kubernetes clusters without spending hours handling repetitive tasks. Cast AI automates Kubernetes cost and active optimization in one easy-to-use platform. No more rightsizing recommendations, we replace them by automation.
You will immediately benefit from features like cost monitoring. We will keep your cloud costs in check with smart and powerful Kubernetes automation, including the fastest autoscaling, bin packing, rightsizing, pricing arbitrage, and spot instance management.
Proven with clients around the world, we will bring 50 to 75% average savings. The best thing: it comes with full AI automation so that you don't need to do it.
Highlights
- NEW: Migrate live Kubernetes containers- including those running stateful workloads - with zero downtime. Eliminate resource fragmentation, ensure maximum resource utilization and optimal instance selection, while driving substantial cost savings.
- Get realtime cost monitoring by namespace, workload, or any other tags by application + get active and automated cost optimization.
- We replace recommendations by automation, with the fastest cluster autoscaler that includes real-time rightsizing and pricing arbitrage of AWS instances.
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Details
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Delivery method
Deployed on AWS
Features and programs
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Free trial
Try this product free according to the free trial terms set by the vendor.
Pricing is based on the duration and terms of your contract with the vendor, and additional usage. You pay upfront or in installments according to your contract terms with the vendor. This entitles you to a specified quantity of use for the contract duration. Usage-based pricing is in effect for overages or additional usage not covered in the contract. These charges are applied on top of the contract price. If you choose not to renew or replace your contract before the contract end date, access to your entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
Free | Get unlimited Kubernetes monitoring and cost reduction insights. | $0.00 |
Growth | Up to 4 managed clusters. Up to 500 CPU (charged based on usage) | $1,000.00 |
GrowthPro | Unlimited managed clusters. Up to 2000 CPU (charged based on usage) | $1,000.00 |
Enterprise | Unlimited managed clusters. Unlimited CPU (charged based on usage) | $5,000.00 |
Growth 700 CPUs | Up to 5 managed clusters. Up to 700 CPU (charged based on usage) | $1,000.00 |
Cost Monitoring | Analyze your Kubernetes spending with detailed breakdowns across workloads, namespaces, and allocation groups. | $200.00 |
Dimension | Cost/unit |
|---|---|
Additional hourly charge per managed CPU as defined at cast.ai/pricing | $0.00694444 |
Vendor refund policy
We do not currently offer refunds.
Custom pricing options
Request a private offer to receive a custom quote.
Legal
Vendor terms and conditions
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Support
Vendor support
Support via dedicated Slack channel. https://castai-community.slack.com/ or support@cast.ai
Service Level Agreement:
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Real-time Cost Monitoring
Cost monitoring and visibility by namespace, workload, and custom tags with application-level granularity
Automated Cluster Autoscaling
Fastest cluster autoscaler with real-time rightsizing and pricing arbitrage across AWS instance types
Workload Migration with Zero Downtime
Live Kubernetes container migration capability including stateful workloads with zero downtime and resource fragmentation elimination
Bin Packing and Resource Optimization
Automated bin packing and resource utilization optimization to ensure maximum instance efficiency
Spot Instance Management
Automated spot instance management and pricing arbitrage for cost optimization across instance purchasing options
Automated Resource Optimization
Automatic deployment of optimal blend of spot instances, reserved instances, and on-demand compute for autoscaling applications without manual tuning
Container and Kubernetes Infrastructure Management
Serverless infrastructure for Kubernetes, EKS, and ECS with automatic scaling, bin-packing, and right-sizing of pods
Reserved Instance and Savings Plan Optimization
Lifecycle management of reserved instances and savings plans using machine learning and automation to maximize portfolio value and minimize on-demand costs
Cloud Cost Analytics and Visibility
Granular cost analytics with integration capabilities for financial accountability and cost optimization tracking
Automated Pod Resource Optimization
Continuously analyzes container compute usage and vertically scales Kubernetes pods to meet demand during runtime with zero disruption
Node Cost Optimization
Identifies opportunities to remove under-provisioned nodes, replace expensive nodes with cheaper alternatives, and consolidate pods onto more efficient compute resources
Real-Time Resource Adjustment
Automatically adjusts compute resources in response to real-time changes in workload demand
Read-Only to Automated Scaling Progression
Supports graduated deployment model starting from read-only recommendations and progressing to continuous automatic optimization
Standard contract
No
No
Customer reviews
Udit Parekh
Automation has optimized our kubernetes costs and continuously improves cluster efficiency
Reviewed on Jun 10, 2026
Review from a verified AWS customer
What is our primary use case?
Our main use case for CAST AI is Kubernetes cost optimization, automated node provisioning, and improving cluster efficiency.
I can provide a specific example of how we use CAST AI for Kubernetes cost optimization and cluster efficiency. Before implementation, we were manually handling all of these tasks. After implementing CAST AI, we are able to see the cost of each pod and node, and based on the reports from CAST AI, we can determine how to optimize our costs.
In day-to-day operations, we use CAST AI to monitor all workloads running on our cluster and evaluate how our nodes and pods are performing. We can determine if we need to resize the nodes and pods or if we are spending too much money on pods, which can be optimized through CAST AI's platform.
How has it helped my organization?
CAST AI has positively impacted our organization because we are now able to control our Kubernetes costs, and the automated node provisioning continuously monitors our application usage to select which node to provision, ensuring the application has sufficient compute power and improving our cluster efficiency.
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. This is a fully automated process. Additionally, manual intervention has decreased significantly because this is a completely automated process.
What is most valuable?
The best features that CAST AI offers, in my experience, are automated scaling, intelligent node selection, cost recommendations, and workload right-sizing.
The biggest feature that has made a difference for our team is that the platform continuously analyzes our cluster's user-based pattern and makes practical optimization suggestions, which saves our team significant time while helping us control cloud expenses.
CAST AI also helps us reduce the manual effort involved in managing infrastructure while ensuring applications always have the resources they need, which is very valuable.
What needs improvement?
The limitations of CAST AI include reporting and customization options. I think they can improve in these areas, especially when some advanced settings require a learning curve, particularly for teams new to Kubernetes optimization. More detailed documentation and deeper visibility into certain optimization decisions would also be helpful.
For how long have I used the solution?
We have been using CAST AI for six to eight months.
What do I think about the stability of the solution?
CAST AI is 100% stable.
What do I think about the scalability of the solution?
CAST AI is 100% scalable. You don't have to do anything in terms of scaling because it is a SaaS platform that will scale automatically, no matter if you have 100 or thousands of Kubernetes clusters running. CAST AI can handle all the loads you have.
How are customer service and support?
The customer support is very good. I have raised queries numerous times as a new user and found the customer support excellent. I would rate the customer support 10 out of 10.
Which solution did I use previously and why did I switch?
We haven't used any different solutions prior to this.
How was the initial setup?
The setup process is relatively straightforward. Integrating CAST AI with a Kubernetes cluster and cloud environments doesn't take very long, so the setup is very easy.
What was our ROI?
We have seen a return on investment, with money saved equating to approximately 30 to 40% ROI. I consider it a very good investment, and the overall ROI is approximately 20 to 30%.
What's my experience with pricing, setup cost, and licensing?
In terms of pricing, I believe the pricing is reasonable because of the amount of savings and operational efficiency it delivers, making it easier to justify the investment. Organizations with larger Kubernetes footprints are likely to see the most value.
Which other solutions did I evaluate?
We haven't evaluated other options before choosing CAST AI.
What other advice do I have?
CAST AI delivers strong value through automation and cost optimization, but there are still a few areas where usability and reporting could be improved. Overall, it has a positive impact on our infrastructure management.
Their governance is compliant with all frameworks, and in terms of security, I believe they are very secure.
Their accuracy is approximately 80 to 90%, and in terms of reliability, it is the same—approximately 80 to 90% reliable for the output it provides.
Teams struggling with Kubernetes costs, especially larger teams with multiple Kubernetes clusters or workloads, should consider using CAST AI. It offers a very good return on investment while saving both operational time and money. I would rate this review an 8 out of 10.
Sowmya B.
Easy, Effective Cloud Cost Optimization
Reviewed on Jun 04, 2026
Review provided by G2
What do you like best about the product?
Great tool for cloud cost optimization. Easy to use and very effective.
What do you dislike about the product?
Nothing major to dislike. Minor UI improvements could help.
What problems is the product solving and how is that benefiting you?
Helps reduce cloud infrastructure costs significantly with automated optimization.
Pradeep G.
Effortlessly Cut Cloud Costs with CAST AI
Reviewed on May 26, 2026
Review provided by G2
What do you like best about the product?
I really like the user experience in CAST AI, especially the easy-to-use console. It allows us to manage clusters easily, see which policies are attached to which workload, and enable or disable workloads. This usability is one of the best parts for me.
What do you dislike about the product?
No such things
What problems is the product solving and how is that benefiting you?
I find CAST AI optimizes our infrastructure, reducing our monthly cloud costs from $32,000 to $20,000 while considering security with GPU metrics.
Financial Services
Cast AI Cut Our Kubernetes Cloud Spend by 50% with Seamless Autopilot Scaling
Reviewed on May 19, 2026
Review provided by G2
What do you like best about the product?
Cast AI is an outstanding Kubernetes cost optimization platform that has genuinely transformed how we manage our cloud infrastructure. The automated cost optimization is incredibly effective, reducing our cloud spend by over 50% without any manual effort. The AI-driven right-sizing of workloads is spot on, and the autopilot feature handles scaling seamlessly. The UI is intuitive and clean, making it easy to navigate and understand resource usage at a glance. Integration with our existing cloud providers (AWS, GCP, Azure) was smooth and took only minutes. The real-time cost visibility and recommendations are actionable and easy to implement. The support team is world-class and always responsive.
What do you dislike about the product?
Honestly, it is very hard to find anything to dislike about Cast AI. The product is so comprehensive that there is very little room for improvement. If I had to nitpick, I would say that the initial setup documentation could have a few more visual guides, but the support team more than compensates for this. Everything else — from onboarding to daily use — has been a pleasure. The platform keeps getting better with every update, and the team is clearly listening to user feedback and continuously improving the product.
What problems is the product solving and how is that benefiting you?
Before Cast AI, we struggled with unpredictable cloud costs and over-provisioned Kubernetes clusters that were wasting significant resources. Cast AI solved this completely. It automatically right-sizes our nodes, eliminates wasted capacity, and has reduced our monthly cloud bill by more than 50%. We no longer need to manually tune resource requests and limits — Cast AI handles it all intelligently. The ROI has been remarkable: within the first month, we recouped the cost of the subscription many times over. Our engineering team now spends less time on infrastructure optimization and more time building features, which has accelerated our product development considerably.
Sodyam B.
Cost-Effective, Easy Setup
Reviewed on Apr 13, 2026
Review provided by G2
What do you like best about the product?
I use CAST AI for cost optimization, cost monitoring, and checking anomalies. The main thing I appreciate about CAST AI is its visibility in a common dashboard for cost monitoring and CPU and memory usage per pod. I love the workload autoscaler because it provides the right sizing of pods. It learns from the usage pattern over the last seven days of data, which helps us save resources. The autoscaler automatically rightsizes the pods based on the resource and limits provided, eliminating the need for manual tasks. It also manages the Replica count, HPA, and VPA intelligently. The classic console provides much ease of use. Setting up CAST AI was very easy, and with the mentioned steps, a cluster can be onboarded in no time.
What do you dislike about the product?
Sometimes the cluster has to be reconciled to enable rebalancing. While it connects efficiently to AWS, Azure, and GCP, the integration with Oracle needs to be added.
What problems is the product solving and how is that benefiting you?
I use CAST AI for cost optimization and monitoring, providing visibility in a common dashboard. It saves costs via workload autoscaling by right-sizing pods based on usage patterns, which eliminates manual tasks like managing replicas, HPA, and VPA.