{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring"}],"enrichment":{"capability":"Integrates Apache Airflow with Kubernetes, enabling orchestration of containerized workloads and cluster operations through Airflow DAGs.","skillfed_tags":["airflow-provider","kubernetes-integration","container-orchestration"],"use_cases":["Run containerized data processing jobs (ML training, ETL pipelines) on Kubernetes from Airflow DAGs.","Orchestrate multi-container applications where each task runs as a Kubernetes pod with defined resource limits.","Integrate Kubernetes-native workloads into Airflow workflows without maintaining separate orchestration systems.","Execute tasks with dynamic resource allocation by leveraging Kubernetes' autoscaling and node management.","Deploy Airflow workflows across multiple Kubernetes clusters or namespaces for multi-tenant environments."],"what_it_does":"This is an Apache Airflow provider package that bridges Airflow's task orchestration engine with Kubernetes clusters. It allows you to define and execute containerized workloads as Airflow tasks, leveraging Kubernetes' native scheduling, resource management, and pod lifecycle features. The package provides operators and hooks that translate Airflow DAG definitions into Kubernetes pod specifications, handling authentication, namespace management, and async execution through its kubernetes and kubernetes_asyncio dependencies.\n\nThe provider is production-stable and actively maintained as part of the official Apache Airflow ecosystem. It requires Airflow 2.11.0 or later and supports Python 3.10 through 3.14. Installation is straightforward via pip on top of an existing Airflow setup, with no compiled dependencies. Use it when you need to run containerized jobs within Kubernetes clusters as part of larger Airflow workflows, or when you want Kubernetes' resource isolation and scheduling alongside Airflow's DAG orchestration.","worth_installing":"Yes. This is a production-stable, actively maintained official Airflow provider with no known vulnerabilities, low install friction, and permissive licensing. Install it if you run Airflow and need to orchestrate Kubernetes workloads. Verify your Airflow version meets the >=2.11.0 minimum and that you have Kubernetes cluster access before deploying."},"id":"apache-airflow-providers-cncf-kubernetes","links":{"html":"https://skillfed.io/packages/apache-airflow-providers-cncf-kubernetes","md":"https://skillfed.io/packages/apache-airflow-providers-cncf-kubernetes.md","pypi":"https://pypi.org/project/apache-airflow-providers-cncf-kubernetes/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-10","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"apache-airflow-providers-cncf-kubernetes","python_support":"supports_current","summary":"Provider package apache-airflow-providers-cncf-kubernetes for Apache Airflow"},"popularity":{"monthly_downloads":13484376,"position":1280,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"10.21.0"}