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建立時間： 2026-05-23 來源： https://x.com/devopscube/status/2052249151405007119
Summary
A promotional post from DevOpsCube pointing to their guide on Apache Airflow running on Kubernetes, covering DAGs, executors, GitSync configuration, and Day 2 operations. Airflow 3 is highlighted as a major redesign targeting complex AI/ML and near real-time workloads. The post notes 80,000 organizations use Airflow, with over 30% for MLOps and 10% for GenAI workflows.
這篇文章介紹 Apache Airflow on Kubernetes 的教學資源，涵蓋 DAG、執行器、GitSync 設定。重點是 Airflow 3 的全面改版，支援 AI/ML 與近即時資料工作負載。目前 80,000 個組織使用 Airflow，其中逾 30% 用於 MLOps。
Key Points
- Airflow is an open-source workflow and data pipeline orchestrator
- DAG concepts transfer directly to Kubeflow and similar platforms
- Airflow 3 redesigned for AI/ML and near real-time workloads
- 30%+ of users run MLOps workloads; 10% for GenAI workflows
Insights
The overlap between Airflow DAG concepts and Kubeflow pipelines means Airflow knowledge transfers to the broader ML platform ecosystem. As GenAI workloads grow (currently 10%), Airflow 3’s near real-time support positions it as a potential orchestration layer for mixed batch+streaming AI data pipelines.
Connections
Raw Excerpt
Key Insight: 80,000 organizations use Airflow, with over 30% of users running MLOps workloads and 10% using it for GenAI workflows.