Bring Karpenter to the next level
Karpenter gives you a strong foundation for EKS node autoscaling. Cast AI takes your Karpenter autoscaling further with AI-powered optimization – automatically right-size workloads, cut cloud costs, and keep your cluster stable without the manual work.
Trusted by 2100+ companies globally
Key features
Our AI agents
make Karpenter smarter and autonomous
Simple onboarding, incremental
adoption
Start optimizing in minutes, then expand at your own pace. Turn on features when you’re ready.
- Connect your cluster in two clicks and see potential savings immediately
- Enable workload optimization, Spot adoption, and other features as you need them
Advanced cluster & node optimization
Add optimization that Karpenter can’t handle. Reduce waste, improve efficiency, and cut costs automatically.
- Rebalance and migrate workloads without downtime or dropped connections
- Hibernate dev and staging clusters automatically to eliminate idle spend
Zero-downtime container live
migration
Move running workloads between nodes without interruption for stateful apps and long-running jobs.
- Enables migration of previously non-movable workloads backed by persistent storage
- Unlocks advanced bin-packing by eliminating node fragmentation and keeps critical applications running
Continuous workload rightsizing
Observe actual resources consumption and tune requests automatically to eliminate silent waste from over-requested resources.
- Reduce overprovisioning without risking application stability
- Enable tighter bin packing by giving Karpenter accurate requirements
Reliable Spot and smarter
consolidation
Keep workloads on Spot instead of defaulting to on-demand and consolidate underutilized nodes without excessive disruption.
- Predict interruptions and return workloads to Spot when capacity stabilizes
- Consolidate with workload-aware logic combined with live migration
Real-time cost visibility
Track spending as it happens and demonstrate value with granular cost monitoring across your Kubernetes infrastructure.
- Monitor compute costs by cluster, namespace, and workload in real-time
- Compare current spending against baseline costs to quantify savings from each optimization decision
Real-Time Cost Reporting
Track expenses by namespace, workload, and team. Surface optimization opportunities and measure realized savings.
Workload Rightsizing
Tune CPU and memory requests based on real consumption. Eliminate waste and improve bin packing without manual YAML changes.
Container Live Migration
Migrate running containers without restarts during consolidation, patching, and node replacement.
Workload-Aware Consolidation
Pack nodes efficiently with placement logic that respects disruption budgets and workload constraints.
Spot Interruption Prediction
Anticipate interruptions before they happen and replace at-risk nodes proactively.
Setup
Get started in three steps
Onboard your Kubernetes Clusters using a single script that deploys lightweight agents on top of Karpenter.
Enable automation and let Cast AI automatically optimize your Kubernetes Clusters without changing Karpenter configuration.
See the impact of Cast AI automation and keep your cluster constantly optimized
Case study
Akamai achieves 40-70% cloud savings, boosts engineer productivity
“I had an aha moment – an iPhone moment – with Cast. Literally two minutes into the integration, we saw the cost analytics, and I had an insight into something I had never had before and had tried to get for a very long time.”
Dekel Shavit
Sr. Director of Engineering
Case study
Yotpo automates Spot Instances, cuts 40% in cloud costs and saves time
“And with Cast AI, we didn’t do anything. Like, we didn’t do the move before, we didn’t do the move after. So there was a lot of human resources and time saved here. That was a very good experience. And again, from a cost perspective, it was highly optimized.”
Achi Solomon
Director of DevOps
Case study
Bede Gaming automatically optimizes K8s workloads with no risk to performance
“In my mind, it’s one less thing to worry about, and therefore teams can be focused on other things of potentially higher value. So having [Cast AI] just run in the background with a good level of confidence that we’re running as efficiently as we can, balancing the service that we’re providing – that’s great.”
Dan Whiteley
Chief Technology Officer
FAQ
Your questions, answered
Cast AI for Karpenter extends the open-source autoscaler with workload-level optimization, safer consolidation, Spot intelligence, and cost visibility. Karpenter continues to handle node provisioning, while Cast AI adds automation and intelligence to improve efficiency and stability.
No. Karpenter remains the node autoscaler. Cast AI works alongside it, enhancing scaling and consolidation decisions while Karpenter executes node lifecycle actions.
After connecting a cluster, Cast AI automatically detects Karpenter and evaluates workload usage, node selection, Spot behavior, and overall cluster efficiency. Cast AI applies its optimization logic while Karpenter performs the underlying node provisioning and management.
Karpenter focuses on node provisioning. Cast AI adds workload rightsizing based on real usage, safer consolidation using container live migration for many workloads, predictive Spot handling, continuous rebalancing, and visibility into cost and efficiency at the workload and team level.
No. Container live migration is used selectively where supported. It helps reduce disruption during consolidation and rebalancing for many workloads, but Cast AI can deliver value even without it.
No. It is designed for teams already running Karpenter as well as those evaluating or newly adopting it. Onboarding is simple and does not require reconfiguring existing Karpenter environments.
Cast AI can surface optimization opportunities and, when enabled, automate actions such as rightsizing, consolidation, rebalancing, and Spot handling. Teams remain in control of how much automation they apply.
Cast AI for Karpenter is primarily designed for Kubernetes clusters running on AWS, where Karpenter is most commonly adopted.
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