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Cast AI’s Decision Engine & Automation Right-Sizing Are Standout Features
What do you like best about the product?
Decision Engine & Automation Right-Sizing is the best features by Cast AI
What do you dislike about the product?
Storage optimization, not support Cloud-native container (ECS, etc)
What problems is the product solving and how is that benefiting you?
Over-provisioned Nodes & Pods on current organization. After using Cast AI, it can reduce number of Over-provisioned Nodes & Pods and direct impact to our Cloud Cost.
Effortless Cost Management and Automatic Scaling
What do you like best about the product?
I really like the simplicity of setting up CAST AI; it was super easy and took less than an hour. We just followed the docs, and within minutes, everything was running smoothly. One of the standout benefits for us has been the cost reduction. We've managed to reduce our costs by a huge 60% since using it. I appreciate how CAST AI ensures that pod limits and requests align with real usage thanks to rightsizing. Previously, managing node pools manually was a hassle. With CAST AI, it's fully automatic, so we don't have to worry about manually creating new node pools to match our resource needs anymore.
What do you dislike about the product?
We had a small glitch at some point where the cluster scaled up because of a poorly configured workload but it didn't scale down automatically which end-up augmenting our costs a lot. We definitely need a way to have alerting when the daily price is more than x% of the previous days.
What problems is the product solving and how is that benefiting you?
CAST AI reduces our infrastructure costs by efficiently using resources, automatically scaling on demand, and utilizing preemptible VMs. It's easy to set up, taking under an hour, and saves us 60% on costs. Previously, node pools were managed manually; now, everything is automated, freeing us from resource management.
Great tool for K8 cost savings and cluster optimization
What do you like best about the product?
It helps us optimize our K8 clusters and reduce costs. The UI is great and clearly shows how much we’ve saved so far, as well as what can still be improved within our cluster. The workload optimizer is also a really useful feature.
What do you dislike about the product?
It’s hard to find logs for certain things, and it’s also hard to understand why something isn’t working when an issue comes up. For example, recently my scheduled rebalancing wasn’t working correctly, and even the support team couldn’t figure out why at first. After a lot of digging, we found it was because one machine was stuck in a weird state after a previous rebalancing. It wasn’t easy to track down what caused this, and it seemed like support wasn’t able to identify the issue right away either.
What problems is the product solving and how is that benefiting you?
It helped us scale our cluster while also reducing costs by almost 50%.
Excellent Node Autoscaler That Fits Our Needs Perfectly
What do you like best about the product?
The node autoscaler is a great replacement for the one on GCP, and it works really well for our needs. It also lets us mix different types of machines, which makes it much easier to tailor the setup to what we want.
What do you dislike about the product?
So far, the workload autoscaler for our Java workload hasn’t been working as well as we expected.
What problems is the product solving and how is that benefiting you?
GCP’s node autoscaler wasn’t able to provide a solution that lets us mix both the machine kind and the instance type (spot or on-demand). Because of that, we couldn’t get a setup that’s close to our needs while still benefiting from an interesting discount.
Cast AI Delivers Fast Kubernetes Cost Savings with Smart Automation
What do you like best about the product?
Its ability to automatically optimize Kubernetes costs without sacrificing performance stands out. The automation around workload rightsizing and intelligent autoscaling saves a significant amount of time and greatly reduces manual effort. I also appreciate the clear visibility into cluster performance and cost metrics, which makes it easier to make informed decisions and stay on top of usage. Overall, the platform is user-friendly, integrates smoothly with existing cloud environments, and delivers measurable cost savings quickly. setup was guided by the support team and we are frequenlty using this to create nodegroups etc
What do you dislike about the product?
One downside of Cast AI is that the initial setup and fine-tuning can take some time, particularly in more complex Kubernetes environments. Although the automation is powerful, it can take a while to fully understand and configure all of the optimization features, and there may be a learning curve for teams that are new to Kubernetes cost management. In addition, having deeper customization options and more detailed reporting in certain areas would make the platform even stronger overall.
What problems is the product solving and how is that benefiting you?
Cast AI solves cloud cost waste and infrastructure management pain. It continuously optimizes resource usage, autoscaling, and spot instance management, reducing unnecessary spending. This means you spend less time manually tuning clusters and more time on real work, while keeping performance and reliability high. The automation also improves operational efficiency and frees up DevOps capacity for higher-value tasks.
Efficient Cost Optimization for Multi-Cloud
What do you like best about the product?
I like the valuable cost insights dashboard that helps us track and analyze our cluster expenses over time along with future cost predictions, making it easier to set and maintain our cost goals. The node recommendations by CAST AI ensure workloads run efficiently. If a node is over-provisioned, it suggests the right sized instances. I enjoy the integration with multiple clouds, including AWS, Azure, and GCP, as the onboarding experience with CAST AI has been extremely smooth. Additionally, I appreciate that many teams in our organization have switched to CAST AI because it is efficient and saves time for our team.
What do you dislike about the product?
Sometimes the suggestions are too aggressive for nodes and it may lead to workload discrepancy.
What problems is the product solving and how is that benefiting you?
I use CAST AI for easy k8s cost optimization, efficient infrastructure management, and smooth multi-cloud integration. It helps track expenses, predict costs, and optimize node provisioning, saving our team time and effort compared to our previous manual process.
Intuitive, Accurate Cost Management with CAST AI
What do you like best about the product?
I like CAST AI for its easy-to-navigate UI/UX and the data granularity, which helps in specifically tracking instance types. It gives me near-accurate costing and provides forecasted costs, which really helps with managing cloud accounts and their costs. The initial setup was straightforward, and we adopted CAST AI because of the UI-UX.
What do you dislike about the product?
none as of now
What problems is the product solving and how is that benefiting you?
I use CAST AI to manage cloud accounts and their cost. It gives me near-accurate costing and forecasts. The easy UI/UX helps navigate accounts, and data granularity aids in specific instance type tracking.
Excellent Resource Allocation, High Cost Barrier
What do you like best about the product?
I love CAST AI's ability to let me right-size the instance type based on its findings and recommendations. It helps us identify where we over-provision our EC2 fleet and adjust it optimally to reduce AWS spending. The initial setup was pretty easy.
What do you dislike about the product?
We're running into infrastructure drift that we have to manage outside of CAST AI. Infrastructure drift is a huge issue for us since what we see in our source controls (GitHub) is different from what actually is running in AWS/EKS. Also, from a budget perspective, CAST AI is cost prohibitive.
What problems is the product solving and how is that benefiting you?
Using CAST AI, I right-size workloads and dynamically scale with recommendations, helping identify over-provisioning in our EC2 fleet, which optimizes and reduces AWS spending.
Streamlined Node Management & Cost Optimization with CAST AI
What do you like best about the product?
I use CAST AI primarily for node management and workload optimization within our Kubernetes clusters. I like its ability to automatically select the most cost-effective nodes for our workloads, taking a lot of guesswork out of infrastructure management. The intelligent instance selection feature dynamically chooses the optimal mix based on performance requirements and cost efficiency. Additionally, I appreciate its recommendations for right-sizing workloads, which help to save resources. The setup is also quick and easy, and onboarding clusters onto CAST AI is straightforward, with Terraform assisting in managing CAST AI resources.
What do you dislike about the product?
One area that could be improved is dynamic workload right-sizing. While it's useful, it heavily relies on past actual usage to forecast and adjust resource requests and limits. It works, but in cases where traffic spikes unusually, it doesn't always adapt quickly enough.
What problems is the product solving and how is that benefiting you?
I use CAST AI for node management and workload optimization in Kubernetes clusters. It helps with cluster capacity management, auto scales, and optimizes resource allocation to prevent overprovisioning and high costs. Its intelligent instance selection and dynamic recommendations improve cost efficiency and right-sizing.
Effortless Scaling with Impressive Cost Savings
What do you like best about the product?
I like that CAST AI helps us to save costs with minimal effort and provides great bin packing of nodes. The one-click deployment was very smooth, making it easy to get started. I also appreciate the one script installation and the great support if there is any issue.
What do you dislike about the product?
We miss their new feature updates sometimes, and an in-person update via Slack would help. We do have a general channel for communication, but specifically tagging the POC and notifying would help, and a demo session would be beneficial.
What problems is the product solving and how is that benefiting you?
I use CAST AI for automating infrastructure scaling and workload management. It helps solve node bin packing, workload autoscaling, and cost-saving with minimal effort.
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