Building Scalable AI Infrastructure: Insights from Alibaba Cloud’s AI Tech Day

On August 8, Alibaba Cloud hosted the AI Infra Solutions and Best Practices salon in Beijing, gathering 32 technical leaders from 16 AI‑focused companies.

Keynote Highlights

Wang Yongmeng emphasized that AI scale‑out demands high‑efficiency, low‑latency, elastic, and highly available infrastructure, and that AI infrastructure is now integral to business decisions.

Part 1: AI Infra Solutions and Practices

Reny Jiangbo presented resource pooling for global AI compute and data, describing how Alibaba Cloud’s Elastic Public IP, Cloud Enterprise Network (CEN), Transit Router, PrivateLink, AI‑native ALB and Global Accelerator create a unified AI network supporting massive data transfer, low‑latency inference, and secure internal services.

Chen Xiaobin discussed AI‑focused compute and container orchestration, covering ACK container intelligence, heterogeneous resource management, monitoring, fault‑tolerance, and serverless sandbox capabilities for AI agents.

Cheng Chuanjun outlined AI‑oriented storage solutions, including Storage for AI (CPFS, OSS, EBS, NAS) and AI‑enabled Storage with OSS meta‑query and vector indexing for semantic search, illustrated by smart‑home camera use cases.

Part 2: AI‑Driven Network Acceleration

Li Weixi shared practical network designs for AI workloads, addressing model training, inference, and AI agent deployment across regions, and detailing design principles for network, compute, and storage layers.

Wu Xi presented global network acceleration for AI applications abroad, highlighting global intelligent scheduling, multi‑layer security, and deterministic cross‑region latency to improve user experience for AI agents and inference services.

The closing discussion explored IaaS core capabilities, data acquisition, model optimization, AI application deployment, and infrastructure refactoring, focusing on architecture rationality, compliance, cost, and quality.