NVIDIA - MinIO Blog

MinIO AIStor with NVIDIA GPUDirect® RDMA for S3-Compatible Storage: Unlocking Performance for AI Factory Workloads

Rakshith Venkatesh Rakshith Venkatesh on NVIDIA | 12 February 2026

In large-scale AI, every watt, core, and microsecond is a competitive edge. GPUs drive the economics of training and inference, making it increasingly important for data paths and faster networks to scale alongside more demanding workloads. NVIDIA has changed the game with GPUDirect RDMA for S3-compatible storage, a breakthrough that preserves the universal S3 API and ecosystem that AI teams

Supercharging Inference for AI Factories: KV Cache Offload as a Memory-Hierarchy Problem

Rakshith Venkatesh Rakshith Venkatesh on NVIDIA | 12 February 2026

Reduce tail-latency spikes from KV cache eviction/recompute, raise effective concurrency per GPU, and improve unit economics (tokens/sec per dollar, cost per token, tokens/sec per watt) while keeping latency predictable under bursty, multi-tenant demand.

AIStor Integration with NVIDIA NIM™

Dileeshvar Radhakrishnan

Dileeshvar Radhakrishnan on NVIDIA | 17 March 2025

Building upon AIStor's robust AI capabilities, MinIO's PromptObject has been enabling users to interact with their data through natural language queries as described here. PromptObject transforms how users interact with stored objects by allowing them to ask questions about their data's content and extract information using natural language—eliminating the need to write complex

Enterprise AI Infrastructure Made Easy with AIStor and NVIDIA GPUs

Dileeshvar Radhakrishnan

Dileeshvar Radhakrishnan on NVIDIA | 17 March 2025

Enterprise AI Infrastructure Made Easy with AIStor and NVIDIA GPUs

Modern enterprises seeking to leverage AI capabilities often face a significant hurdle: the complex deployment and management of GPU infrastructure in their Kubernetes environments. MinIO's AIStor addresses this challenge head-on by integrating the NVIDIA GPU Operator, revolutionizing how organizations deploy and manage GPU resources for AI workloads. Through automated GPU setup, driver management, and resource optimization, this integration