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Alibaba Cloud Infrastructure
Alibaba Cloud Infrastructure
Mar 23, 2026 · Backend Development

Boost Java Development with Jar Skills: A Practical Guide for Qoder

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.

AIJarSkillJava
0 likes · 8 min read
Boost Java Development with Jar Skills: A Practical Guide for Qoder
Alibaba Cloud Infrastructure
Alibaba Cloud Infrastructure
Mar 18, 2026 · Cloud Native

Why Ingress NGINX Is Retiring and How to Choose Its Successor

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.

ALB IngressGateway APIKubernetes
0 likes · 18 min read
Why Ingress NGINX Is Retiring and How to Choose Its Successor
Alibaba Cloud Infrastructure
Alibaba Cloud Infrastructure
Mar 16, 2026 · Artificial Intelligence

Scaling Agentic Reinforcement Learning with a Decoupled T‑Architecture Using Verl and Argo Workflows

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.

Argo WorkflowsDistributed SystemsScalable Reinforcement Learning
0 likes · 10 min read
Scaling Agentic Reinforcement Learning with a Decoupled T‑Architecture Using Verl and Argo Workflows
Alibaba Cloud Infrastructure
Alibaba Cloud Infrastructure
Mar 13, 2026 · Cloud Native

Boosting Autonomous Driving Data Pipelines with Koordinator’s ElasticQuota and GPU Sharing

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.

Autonomous DrivingElasticQuotaGPU Sharing
0 likes · 20 min read
Boosting Autonomous Driving Data Pipelines with Koordinator’s ElasticQuota and GPU Sharing