For uninterrupted computing services
This article details the design and implementation of a fully automated, 24‑hour feedback handling system that classifies, clusters, analyzes logs, and even generates code fixes using Qoder CLI, dramatically reducing manual effort and response time while maintaining human oversight for final code review.
This guide explains how to dramatically reduce latency for batch semantic search, RAG multi‑path retrieval, and multimodal vector queries by running multiple OSS Vectors embed requests in parallel using CLI‑based, xargs, shell background jobs, Python asyncio, and SDK‑level concurrency techniques.
At the 2026 Open AI Infra Summit, Alibaba Cloud showcased the evolution of the UALink 2.0 protocol and its integration with CXL, detailing new specifications, in‑network compute capabilities, and ecosystem developments that aim to overcome scale‑up bottlenecks in AI training and inference.
This guide walks through setting up Alibaba Cloud OSS Vector Buckets, installing the necessary SDKs, uploading image datasets, creating vector indexes, generating embeddings with the Bailei multimodal model, writing vectors, performing semantic searches, and visualizing results via a Gradio web UI.
This guide explains how to build a secure, multi‑tenant data lake on Alibaba Cloud by combining OSS Access Points with VPC Gateway Endpoints, covering architecture overview, step‑by‑step configuration, policy examples, and best‑practice considerations for private‑network access.
This article explains how to create and use Jar Skills in the Qoder JetBrains plugin to embed SKILL.md files inside Java JARs, extract them with the skillsjars‑maven‑plugin, and leverage these skills—along with @openFiles—to enhance AI‑assisted coding, provide best‑practice documentation, and improve code generation for internal and third‑party libraries.
This guide explains how to use slash commands in the Qoder AI coding assistant to bypass project scanning and web searches, saving time and tokens while delivering precise answers, and provides concrete command examples, implementation details, and best‑practice tips for developers.
The article analyzes the retirement of Ingress NGINX, explains the security flaws, architectural debt, and community constraints that led to its end‑of‑life, and compares migration paths—including staying with NGINX, moving to Gateway API, or adopting Alibaba Cloud ALB Ingress—so engineers can make an informed decision.
Agentic reinforcement learning is evolving from simple text generation to complex, scalable agents, but large‑scale deployment faces challenges like massive parallel rollout scheduling and reproducible environments; this article presents a decoupled T‑architecture that separates high‑level RL logic (Verl) from execution orchestration (Argo Workflows) to address these issues.
This article details how a leading autonomous‑driving company tackled multi‑tenant resource contention, low GPU utilization, and distributed task dead‑locks on a heterogeneous Kubernetes cluster by adopting Koordinator’s ElasticQuota, Reservation, Gang and Device‑Share features, achieving higher allocation rates, better fairness, and significantly improved GPU efficiency.
