Cast.ai
Autonomous application performance automation for cloud-native environments
À propos de Cast.ai
Cast.ai is an AI-powered platform that automates application performance optimization, reducing cloud costs and eliminating manual interventions. It monitors SLO signals, predicts issues, and self-heals operations in real time, ensuring high performance without over-provisioning.
FAQ
Cast AI reduces cloud costs by continuously optimizing infrastructure in real time based on actual workload behavior. It automatically adjusts CPU and memory requests, scales nodes, and manages spot instances, eliminating over-provisioning without risking performance.
Cast AI provides highly responsive support. Testimonials mention that support is a high point, with the team being extraordinarily responsive and dedicated to resolving issues, no matter the time of day or night.
Cast AI is designed to work with the tools you already use. It offers integrations with AWS, Azure, and Google Cloud, and provides Terraform Modules to enable seamless integration into Infrastructure as Code workflows.
Cast AI emphasizes enterprise-grade security. It provides performance observability and intelligence with real-time visibility into resource utilization and application performance, ensuring secure and optimized operations.
Cast AI can start optimizing your infrastructure in minutes. You can deploy it to your Kubernetes clusters in minutes, start in read-only mode, and begin analyzing workload behavior immediately without requiring infrastructure changes.
No, Cast AI is designed to automate optimizations without manual intervention. It uses AI Agents to fix real issues, remediate drift, update container images, auto-heal failures, and enforce policies, all without requiring manual fixes.
Companies using Cast AI have reported significant results, such as 40-70% cloud savings, reduced engineer workload, and improved performance. For example, Akamai achieved 40-70% cloud savings, and Yotpo cut 40% in cloud costs.
Yes, Cast AI is trusted by over 2100 companies globally and is recognized for its performance and reliability. It is designed to handle large-scale enterprises with advanced predictive models trained on massive datasets from thousands of clusters.
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