Cast AI - EKS fully automated cost optimization and monitoring

What do you like best about the product?

CAST AI offers robust Kubernetes cost monitoring, providing clear visibility into resource usage and expenses across clusters. Its actionable cost recommendations are particularly helpful, guiding users on how to optimize or reduce spending with specific, practical steps. Additionally, CAST AI supports org-level cluster monitoring, making it easy for organizations to manage and analyze the cost and performance of multiple clusters in one place. Overall, CAST AI is an effective tool for enterprises looking to gain better control over their Kubernetes costs and efficiency.

What do you dislike about the product?

While CAST AI offers powerful cost optimization features, there are a few areas that could be improved. The initial setup and integration with existing Kubernetes environments can be complex and may require substantial time and expertise. Some users have reported a learning curve when navigating the UI and understanding the full range of functionalities. Additionally, as a third-party platform, there may be concerns around data security and handing over cluster management. Pricing could also become a consideration for smaller teams or organizations with limited budgets.

What problems is the product solving and how is that benefiting you?

CAST AI is solving the problem of high and unpredictable Kubernetes cloud costs by providing real-time cost monitoring, intelligent optimization, and actionable recommendations. It helps identify inefficiencies, unused resources, and overprovisioning in my clusters, allowing me to automate scaling and adjust workloads for maximum cost efficiency. This results in significant cost savings, better resource allocation, and improved visibility across the organization’s clusters, making cloud infrastructure management much simpler and more predictable.

What do you like best about the product?

CAST AI's ability to automatically optimize Kubernetes workloads for cost and performance is incredibly powerful. I particularly appreciate the autoscaling and rightsizing features that reduce our cloud bill without manual intervention. The interface is intuitive, and integration with AWS and GCP was seamless. The real-time cost visibility and actionable recommendations help us stay on top of resource usage.

What do you dislike about the product?

There’s a learning curve during the initial setup, especially if you're new to Kubernetes internals. Additionally, I would like to see more documentation around custom policy configurations for companies with unique infrastructure needs. While support is helpful, response time could be a bit faster during critical issues.

What problems is the product solving and how is that benefiting you?

CAST AI is solving the challenge of managing cloud costs and performance in Kubernetes environments. Manually optimizing workloads, scaling clusters, and choosing the right mix of instances across multiple cloud providers is time-consuming and error-prone. CAST AI automates these processes, enabling our team to focus on development rather than infrastructure tuning. Since implementation, we've seen a significant reduction in cloud spend—especially by replacing on-demand nodes with spot instances—and improved cluster efficiency with minimal manual effort.

What do you like best about the product?

- 30% cloud cost savings over our whole compute
- Increase in my team’s productivity: a task that took seven days now gets done in three or four days
- We also unlocked extra cost savings from Spot Instances thanks to automated instance selection

What do you dislike about the product?

No complaints, the Cast support is great

What problems is the product solving and how is that benefiting you?

Reliability and scalability are important to use. But as we scaled, our infrastructure got more complex and expensive. Cast helps us scale efficiently, cut costs, and reduce manual work without losing reliability. Features like rebalancing and the Workload Autoscaler take care of optimization automatically, so we can focus on what matters.

What do you like best about the product?

For a platform that uses k8s multi-tenancy , monitoring and optimizing costs easily across many clusters and namespaces is very important. Cast gives us a easy way to achive this.

What do you dislike about the product?

For un-even workloads across Pod-s in one Deployment or StatefulSet auto-scaling does not always yield the best results, but this is true for all k8s auto-scaling options out there. With cast.ai you can manually tweak the requests/limits

What problems is the product solving and how is that benefiting you?

Cost monitoring and optimization across a large number of k8s clusters , each cluster with many namespaces

What do you like best about the product?

CAST AI automatically rightsizes workloads, removes underutilized nodes, and selects the most cost-effective instances in real time—saving up to ~ 60% on cloud bills without sacrificing performance.
Their autoscaler is fast and responsive, scaling workloads vertically and horizontally with minimal delay, and supports real-time bin-packing.
Built-in security scanning and real-time insights about vulnerabilities and misconfigurations across your clusters are helpful for compliance.
With policies, teams can enforce governance (e.g., disallowing GPU usage, or restricting instance types), which is useful in large or shared environments.
Especially for organizations with dynamic or spiky workloads, CAST AI’s automation leads to substantial cost reductions.
• Simplicity and Speed:
The UI is clean, onboarding is relatively quick, and node replacements happen in minutes.
• Great for SRE/Platform Teams:
Offloads the pain of managing autoscaling, provisioning, and node selection.

What do you dislike about the product?

• Learning Curve on Governance:
Policy setup and interpretation of some recommendations require a bit of learning, especially for teams new to Kubernetes internals.
• Limited Documentation Depth:
Some users may find the documentation lacking for advanced use cases, particularly when integrating with non-standard setups (e.g., GKE workload identity federation, custom networking).

What problems is the product solving and how is that benefiting you?

• Significant Cost Savings:
Especially for organizations with dynamic or spiky workloads, CAST AI’s automation leads to substantial cost reductions.
• Simplicity and Speed:
The UI is clean, onboarding is relatively quick, and node replacements happen in minutes.
• Great for SRE/Platform Teams:
Offloads the pain of managing autoscaling, provisioning, and node selection.