For uninterrupted computing services
Shentong Express faced massive, high‑risk cross‑cluster migration challenges and, by adopting Alibaba Cloud's ACK One MultiClusterService, reduced an expected one‑year migration to a few months with zero code changes, controlled risk, and seamless traffic flow.
This guide walks you through deploying the Qwen 3.5‑plus model on Alibaba Cloud ACK/ACS using the ACS Agent Sandbox, creating a CoPaw sandbox, configuring model access, integrating with DingTalk, and optionally using the sandbox’s pause‑and‑wake features.
Kubernetes introduced mutable PersistentVolume node affinity to enable flexible online volume management, allowing administrators to adjust node selectors when storage moves across zones or upgrades, but the feature remains alpha, requires careful coordination, and may introduce scheduling race conditions.
In the cloud‑native era, Alibaba Cloud’s CSI‑based hierarchical storage combines local NVMe SSD performance with cloud‑disk durability, offering a three‑layer design, operational simplicity, and up to 100× IOPS gains for database and AI workloads.
This guide details how to deploy the open‑source Qwen 3.5‑397B‑A17B multimodal LLM on Alibaba Cloud ACK using the RoleBasedGroup (RBG) engine, covering model preparation, Kubernetes resources, role‑based orchestration, performance tuning, and benchmark testing.
This article explains how Kubernetes VolumePopulator can automatically transfer AI training data from low‑cost OSS storage to high‑performance CPFS volumes, enabling on‑demand model loading, cost‑effective hot‑cold data management, and fully automated lifecycle handling in cloud‑native AI workloads.
This article explains how GlobalElasticQuotaTree extends Kubernetes native elastic quota to multi‑cluster environments, providing hierarchical quota structures, Min/Max borrowing, cluster‑level control, and workload‑type support to improve resource utilization for AI platforms.
By integrating Alibaba Cloud ACK’s Kubernetes VolumePopulator with Argo Workflows, this guide shows how to pre‑populate independent high‑performance volumes for each parallel task, eliminating I/O contention, ensuring data isolation, and enabling scalable, serverless‑accelerated pipelines for large‑scale data processing.
This guide walks through preparing the Kimi 2.5 model, uploading it to OSS, configuring persistent storage, and using SGLang, RoleBasedGroup, and Openclaw to deploy a production‑grade inference service on Alibaba Cloud Kubernetes with step‑by‑step commands and YAML examples.
Kimi built a high‑performance, low‑cost AI Agent infrastructure by combining Alibaba Cloud ACK node pools and the ACS Agent Sandbox, addressing challenges of instant sandbox response, state continuity, massive concurrency, cost efficiency, security isolation, and search‑memory integration for production‑grade agents.
