Tagged articles

AgenticFS

4 articles · Page 1 of 1

Sep 30, 2026 · Cloud Computing

Alibaba Cloud Launches Agentic Storage Matrix for AI & Agent Workloads

Alibaba Cloud unveiled its full-stack Agentic Storage product matrix at the 2026 Yunqi Conference, spanning AI Native storage for trillion-parameter model training and inference, and Agent Native storage for million-agent concurrency, featuring CPFS, KVCacheStore, AgenticFS, and vector memory services with concrete performance gains.

AI infrastructureAgentic StorageAgenticFS

0 likes · 9 min read

Alibaba Cloud Launches Agentic Storage Matrix for AI & Agent Workloads

Alibaba Cloud Infrastructure

Aug 29, 2026 · Cloud Native

How AgenticFS Redefines Storage for AI Agents: From Shared Directories to Independent Workspaces

The article analyzes the limitations of traditional NAS for AI agents—scale ceiling, isolation gaps, and security blind spots—and explains how AgenticFS redesigns the storage paradigm by giving each agent an independent, zero‑trust workspace that scales linearly across regions.

AI storageAgenticFScloud native storage

0 likes · 13 min read

How AgenticFS Redefines Storage for AI Agents: From Shared Directories to Independent Workspaces

Alibaba Cloud Infrastructure

Aug 28, 2026 · Cloud Computing

How Alibaba Cloud’s New Storage Stack Powers AI Training, Inference, and Agents

The article analyzes how Alibaba Cloud’s CPFS, KVCacheStore, AgenticFS, OSS Agent and CDE Agent together address exploding AI data scales, accelerate model training and inference, and support massive AI Agent workloads with concrete performance numbers and architectural details.

AI infrastructureAgenticFSAlibaba Cloud

0 likes · 12 min read

How Alibaba Cloud’s New Storage Stack Powers AI Training, Inference, and Agents

Baidu Intelligent Cloud Tech Hub

Aug 27, 2026 · Big Data

PFS L3 Architecture Deep Dive: Redesigning Parallel File Storage for AI Production Workloads

Baidu's PFS L3 rearchitects parallel file storage for AI production loads with a hybrid data engine (Aries + BlockServer), scalable metadata foundation (MetaDB), high-performance client (RapidFC), RDMA network tuning, transparent tiering to object storage, and AgenticFS for multi-tenant Agent workloads, proven in RL training saving 30k GPU-hours weekly.

AI storageAgenticFSAries

0 likes · 29 min read

PFS L3 Architecture Deep Dive: Redesigning Parallel File Storage for AI Production Workloads