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Automation that reduces costs and simplifies the creation of pods and nodes
What do you like best about the product?
The automation that the system offers to reduce costs in our company, and the way it works in the creation of pods and nodes
What do you dislike about the product?
So far, I haven't seen any usability that I didn't like.
What problems is the product solving and how is that benefiting you?
This is helping our FinOps team reduce costs monthly.
Essential Tool for Kubernetes Efficiency and Cost Control
What do you like best about the product?
What I value most is how Cast AI turns complex Kubernetes optimization into a seamless, automated process. It consistently delivers significant cost savings (often up to 50%) by intelligently handling Spot instances and right-sizing workloads in real-time. The automated autoscaling is much more responsive than native cloud tools, and the 'set and forget' nature of the platform has effectively removed the burden of manual cluster tuning from our DevOps team.
What do you dislike about the product?
Initial Trust & Security Approval: Because Cast AI requires deep access to your cloud environment to perform automated actions (such as adding or deleting nodes), the initial security review—especially in larger organizations—can be lengthy and quite rigorous.
Learning Curve for Advanced Policies: While the “read-only” setup is fast to get up and running, getting comfortable with the more advanced automation policies—and correctly fine-tuning the “Auto-Remediation” settings—takes time and a strong understanding of Kubernetes to avoid unexpected behavior.Cast AI solves the persistent issues of cloud waste and operational complexity. Before, we spent too much time manually adjusting resources and overpaying for idle capacity. Now, the platform benefits us by automatically selecting the most cost-effective nodes without compromising performance. This hasn't just lowered our monthly bill; it has given our engineers the peace of mind and the time to focus on building features rather than managing infrastructure.
Learning Curve for Advanced Policies: While the “read-only” setup is fast to get up and running, getting comfortable with the more advanced automation policies—and correctly fine-tuning the “Auto-Remediation” settings—takes time and a strong understanding of Kubernetes to avoid unexpected behavior.Cast AI solves the persistent issues of cloud waste and operational complexity. Before, we spent too much time manually adjusting resources and overpaying for idle capacity. Now, the platform benefits us by automatically selecting the most cost-effective nodes without compromising performance. This hasn't just lowered our monthly bill; it has given our engineers the peace of mind and the time to focus on building features rather than managing infrastructure.
What problems is the product solving and how is that benefiting you?
Cast AI addresses the ongoing problem of cloud waste and the heavy, manual burden of cluster tuning. Previously, we struggled with overprovisioning and with the complexity of managing Spot instances safely.
By automating real-time selection of the most cost-effective nodes, it has reduced our cloud bill significantly while still maintaining high availability. For us, the biggest benefit is the operational peace of mind: our DevOps team no longer spends hours on infrastructure rightsizing and can instead focus on shipping better code.
By automating real-time selection of the most cost-effective nodes, it has reduced our cloud bill significantly while still maintaining high availability. For us, the biggest benefit is the operational peace of mind: our DevOps team no longer spends hours on infrastructure rightsizing and can instead focus on shipping better code.
Super Helpful Support and Incredible Savings with Minimal Effort
What do you like best about the product?
The support team is super helpful, the money saved is great, and it's a relatively low lift to start seeing incredible savings.
What do you dislike about the product?
Honestly, I don't dislike anything. The hardest part about using the workload rightsizer is really the amount of time we need to work with application teams to think about workload rightsizing which is a problem most startups will have.
What problems is the product solving and how is that benefiting you?
Node rightsizing, helps a ton by saving us money.
cast.ai Cut Our Compute Costs and Simplified Spot Instance Management
What do you like best about the product?
Cast AI removed the burden of managing spot instances and decreased the compute costs.
What do you dislike about the product?
Cast AI automated onboarding of a new environment might require extra steps.
What problems is the product solving and how is that benefiting you?
Cast AI drastically decreased computing costs, removed the burden of managing worker nodes, which allowed us to spend more time on developing features.
Reduces Costs and Enhances Node Management
What do you like best about the product?
I like CAST AI's team as they were really helpful. When we faced a learning curve during the initial setup, they guided us through automating our many clusters. Also, I think omni works especially well with CAST AI.
What do you dislike about the product?
It had a learning curve but the team helped us through the automation on our many clusters.
What problems is the product solving and how is that benefiting you?
I use CAST AI for scaling Kubernetes and spot nodes, reducing cost and overhead around rules and management of those nodes.
Cost Reduction and Efficient Automation
What do you like best about the product?
I really like the vulnerability visualization feature that CAST AI provides; it identifies vulnerabilities and shows the vulnerable images, highlighting their criticality. I also really appreciate all the information it provides and the possibility of automations, which is very important for the organization and greatly eases the daily workload.
What do you dislike about the product?
One of the areas where CAST AI needs to evolve is in the matter of multiple organizations within the same company. Today, there is no centralized management, which makes daily operations quite difficult. If you have an environment that requires an organization, you need to create another one, which makes managing these tokens more difficult. Furthermore, there is no centralization in terms of a main organization and subsidiary organizations. This ends up multiplying the users, and they need to be managed manually, complicating the management of the tool.
What problems is the product solving and how is that benefiting you?
I use CAST AI to optimize costs, improve the visualization of our Kubernetes-based environments, and automate tasks, which eases our daily workload. It solves cost issues in large environments, provides insights into container vulnerabilities, and aids in the predictability of operations.
Intelligent cost optimization in Kubernetes
What do you like best about the product?
Automate cost optimization in Kubernetes efficiently, reducing waste and operational effort, without compromising high performance and reliability.
What do you dislike about the product?
Some more advanced features still lack clearer and well-organized documentation, which may end up delaying the adoption of the tool and the resolution of problems by new users.
What problems is the product solving and how is that benefiting you?
We had difficulty with high costs in Kubernetes, but now we automatically optimize, reducing waste and cutting infrastructure costs.
Efficient Cost Optimization with CAST AI
What do you like best about the product?
I like how CAST AI is great for our Kubernetes cluster cost optimization and helps maximize CPU and memory resource usage. I appreciate its in-place pod right sizing and container live migration capabilities. With in-place right sizing, our 5xx errors have significantly decreased. The container live migration feature is beneficial for consolidating our stateful workloads. Setting up CAST AI was a straightforward process.
What do you dislike about the product?
NA
What problems is the product solving and how is that benefiting you?
I use CAST AI for Kubernetes cluster cost optimization and to maximize CPU and memory usage. It offers node consolidation and improves pod right sizing, which has significantly reduced our 5xx errors. Container live migration helps with stateful workload consolidation.
Effortless Cost Optimization and Autoscaling
What do you like best about the product?
I like CAST AI for its workload autoscaling, which helps with optimization while maintaining availability. It has helped me achieve about 70% cost optimization with better bin packing, rebalancing, and pod mutation to maintain a diverse workload. I also appreciate having a single place to manage multiple clusters and daily costing. The initial setup was very easy and well-guided by the CAST AI team.
What do you dislike about the product?
I think it could be better for handling StatefulSets in bin packing. It can handle better StatefulSets to make sure pods should handle state while eviction and reschedule in other nodes.
What problems is the product solving and how is that benefiting you?
I use CAST AI for cost optimization and autoscaling in our K8s clusters. It solved issues with node choices, better autoscaling, bin packing, and minimizing sudden cost increases. It helped achieve 70% cost optimization and provides a single place to manage clusters and daily costs.
Real Savings, but Takes Iteration to Balance Cost Cuts and Stability
What do you like best about the product?
The biggest upside is the combination of insights and automation. Cast AI makes it straightforward to identify overprovisioned resources and apply savings in a controlled way. The UI is clean, and the recommendations are easy to explain to stakeholders who just want results.
What do you dislike about the product?
Some users mention that cost savings are real, but results can vary depending on workload maturity, so it can take a few iterations to dial in the right balance between savings and stability.
What problems is the product solving and how is that benefiting you?
The benefit for us is lower cloud spend, fewer manual tuning cycles for the platform team, and faster visibility into where cost and capacity are drifting so we can correct it before it becomes a bigger issue.
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