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Short experience with CAST AI
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.
Cost-efficient Kubernetes optimization using AI
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.
A solution that cuts costs and reduce operational overhead by optimising Kubernetes resources
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
- 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.
Centralized Monitoring and Cost Savings for solutions using k8s multi-tenancy
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
A powerful solution for K8s cost optimization, best suited for cloud-native apps at scale.
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.
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).
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.
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.
CastAi Review
What do you like best about the product?
Easy to use UI. Consolidation of things at one place. Good cost savings and hibernation concept is really good.
What do you dislike about the product?
Some machine types are not supported. So, we need to select different machine types for our products. Build an overall platform not for just gcp but include other future of cloud as well such as db optimisations etc.
What problems is the product solving and how is that benefiting you?
Our costs have reduced significantly. Support is good, we get the response pretty fast if something goes wrong.
CAST AI Tool review
What do you like best about the product?
CAST AI helps organizations in managing cloud resources and optimizing the costing part with high availability at low cost . Their consulting team is very dependable and are available anytime almost.
Integration to CAST AI is super easy and we have connect our cluster to CAST AI tool and using node templates and resource allocation the machine type and resources were scheduled to the pods in the Google Kubernetes Engine cluster.Even we can define the region where to spawn our pods.
We used terraform script to connect our clusters to CAST AI tools.The CAST AI team is very helpful in the integration part by providing the documentation to connect our cluster to CAST AI.
Integration to CAST AI is super easy and we have connect our cluster to CAST AI tool and using node templates and resource allocation the machine type and resources were scheduled to the pods in the Google Kubernetes Engine cluster.Even we can define the region where to spawn our pods.
We used terraform script to connect our clusters to CAST AI tools.The CAST AI team is very helpful in the integration part by providing the documentation to connect our cluster to CAST AI.
What do you dislike about the product?
Sometimes there are some issues that popup like machine types that might not supported by apps we provisioned by CAST AI tool which really annoys me.
What problems is the product solving and how is that benefiting you?
CAST AI helps us in reducing the costing part for cloud resource maintenance and they also helps us to rightsize the workloads in gke
Smooth Journey with CASTAI
What do you like best about the product?
CAST AI is an easy tool to onboard the kubernetes clusters.It provides the easy dashbords to understand the CPU and RAM utilization of the Node and workloads.It is easy to implement the things with the help of CAST.Quick action on the issues with the 24X7 customer support. Schedule rebalacing is the great feature provided by CAST with which we can schedule the rebalancing with the flexible timings.We from our organization will be frequently viewing the console.It also provides the slack configurations and alerts on the metrics.
What do you dislike about the product?
CAST AI should improve on the below features like proving the logs for the workload autoscalers,Audit logs has to be improved for more understanding of the onboardings.
What problems is the product solving and how is that benefiting you?
The main problem CAST solved me is that we have been spending alot of credits on the kuberneties clusters in our organization but with the help of the CAST we have seen huge savings.
Amazing service that save a lot of unnecessary cloud expense
What do you like best about the product?
The support engineers and it's easy to use.
What do you dislike about the product?
The UI can be improved and reports also.
What problems is the product solving and how is that benefiting you?
Instead of checking how much resources do I need on any point of time, CastAI adjust it automatically by VPA and HPA which lead to select the optimal compute family according to usage, this save us a lot of cost.
Maximizing Cloud Savings Through Kubernetes Automation
What do you like best about the product?
CAST AI made Kubernetes cost optimization effortless.
We saw immediate results, with significant savings and zero downtime during implementation.
Main key points:
- advanced node automation for node management and spot instance utilization
- simplicity usage with maximum savings in one package
We saw immediate results, with significant savings and zero downtime during implementation.
Main key points:
- advanced node automation for node management and spot instance utilization
- simplicity usage with maximum savings in one package
What do you dislike about the product?
I don't have any significant complaints about CAST AI.
They have been a reliable partner throughout our collaboration.
They have been a reliable partner throughout our collaboration.
What problems is the product solving and how is that benefiting you?
The ability to automatically scale and optimize workloads has not only reduced our Kubernetes costs but also freed up our DevOps team to focus on innovation rather than infrastructure management.
By automating complex optimization tasks, CAST AI helps us avoid overspending on unused resources while maintaining seamless application performance.
By automating complex optimization tasks, CAST AI helps us avoid overspending on unused resources while maintaining seamless application performance.
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