Ankur Pandita

Bring Rafay Into Your AI Workflows with the Rafay MCP Server
The Rafay MCP Server brings secure, AI-assisted visibility to Kubernetes and platform operations, letting teams use natural language to inspect clusters, workloads, blueprints, and environments through MCP-compatible AI tools.
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Kubernetes v1.36 for Rafay MKS
Support for Kubernetes v1.36 (codename Haru) is now available on the Rafay Operations Platform for MKS cluster types, covering both new cluster provisioning and in-place upgrades. Every Rafay platform feature has been validated on this release, and v1.36 clusters managed by Rafay are CNCF conformant.
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No More SSH: Control Plane Overrides for Rafay MKS Clusters
Say goodbye to SSH access and manual cluster fixes. Learn how control plane overrides bring secure, centralized control to Kubernetes operations.
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Accelerating the AI Factory: Rafay & NVIDIA NCX Infra Controller (NICo)
Learn how Rafay and NVIDIA NCX Infrastructure Controller (NICO) help enterprises operationalize AI factories—turning GPU infrastructure into scalable, self-service, and governed AI platforms.
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Interact with Your Rafay Managed Kubernetes Clusters Using MCP-compatible AI clients
Learn how to securely enable AI assistants to interact with Rafay-managed Kubernetes clusters using MCP and Zero Trust Kubectl Access (ZTKA), ensuring RBAC enforcement, auditability, and zero exposed endpoints
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Kubernetes v1.35 for Rafay MKS
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Managing Environments at Scale with Fleet Plans
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Kubernetes v1.34 for Rafay MKS
Users of the Rafay platform can provision new clusters based on Kubernetes v1.34 using the supported interfaces.
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Dynamic Resource Allocation for GPU Allocation on Rafay's MKS (Kubernetes 1.34)
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Upstream Kubernetes on RHEL 10 using Rafay
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