What is CAST AI?
CAST AI is an intelligent Kubernetes automation platform that revolutionizes cloud infrastructure management. The platform delivers comprehensive solutions for cloud cost optimization, Kubernetes monitoring, and container security across major cloud providers including AWS, Azure, and GCP.
Through continuous monitoring and real-time optimization, CAST AI implements automated scaling, provisioning, and bin packing to maximize efficiency. The platform offers seamless integration with existing infrastructure, requiring minimal setup time, while providing robust security features and detailed cost visibility across all Kubernetes operations.
Features
- Cloud Cost Optimization: Automated scaling and provisioning for 50%+ cost reduction
- Kubernetes Cost Monitoring: Real-time expense tracking and breakdown
- Container Security: Automated security remediation and compliance
- AI Enabler: Optimized LLM deployment and model selection
- Container Live Migration: Zero-downtime migration for stateful workloads
- Multi-Cloud Support: Compatible with AWS, Azure, and GCP
- Automated Scaling: 24/7 workload optimization
Use Cases
- Kubernetes cost reduction
- Cloud infrastructure optimization
- Container security management
- DevOps automation
- Multi-cloud management
- LLM deployment optimization
- Resource utilization improvement
FAQs
-
How much can I save using CAST AI?
CAST AI typically helps organizations cut their cloud costs by 50% or more through automated optimization and resource management. -
Which cloud providers does CAST AI support?
CAST AI supports Kubernetes on AWS/EKS, Azure/AKS, and GCP/GKE platforms. -
How long does it take to implement CAST AI?
Implementation is quick, requiring just one script to get started, with an average proof of concept taking approximately one week. -
Does CAST AI require a credit card for the free plan?
No, you don't need a credit card to use the free tools. You can sign up and connect your cluster immediately.
Related Queries
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CAST AI Uptime Monitor
Average Uptime
100%
Average Response Time
212 ms
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