A guide to running Airflow on Kubernetes

:snowflake: :whale: Awesome tools and libs for AI, Deep Learning, Machine Learning, Computer Vision, Data Science, Data Analytics and Cognitive Computing that are baked in the oven to be Native on Kubernetes and Docker with Python, R, Scala, Java, C#, Go, Julia, C++ etc

Bare minimal Airflow on Kubernetes (Local, EKS, AKS)

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Kubernetes for Generative AI Solutions, published by Packt

Run Airflow on Kubernetes. This repository contains scripts to 1) run a multinode kubernets cluster on local machine using KinD, 2) prepare Dockerfile for your airflow dags 3) Minimal helm chart required to run airflow on kubernetes using Kubernetes Executor

Source code for guide to run Apache Airflow on Kubernetes

Accompanying code examples for webinar and blog post "three ways to run airflow on kubernetes"

Integrate Airlock WAF in a Kubernetes or OpenShift Environment

A comprehensive collection of AI/ML tools, frameworks, and resources in the Kubernetes ecosystem

Setup Apache Airflow on Kubernetes

Library which aim to generate kubernetes yamls templates from an Airflow dag using the Airflow Kuberntes Pod Operator

In this project, we build an Apache Airflow pipeline to load, train, and evaluate a ML model, store it, and use it for inferencing by deploying the model with a sleek Streamlit UI, Docker, and auto-scale it with Kubernetes as container orchestration tool 🎓

Simple Airflow on Kubernetes (GKE)

A simple sample on how to use Airflow with KubernetesPodOperator

Repo del taller Airflow en Kubernetes para el taller "Airflow en Kubernetes" @ PyConAr 2020

A working airflow-on-k8s deployment for demos

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An AI-powered travel itinerary planner web app uses LLMs and real-time search to generate personalized day-by-day itineraries based on user preferences, destinations, and travel style, showcasing an end-to-end LLMOps pipeline.

The AI Powered Job Analyzer is a cloud-native application that leverages GPT-4 to automatically screen resumes against job descriptions for hiring accuracy. Deployed on a Kubernetes cluster, it integrates a full ELK stack (Filebeat, Logstash, Elasticsearch, Kibana) to provide robust, real-time logging and system observability.

Airflow DAGs to install and test OpenShift Clusters

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Using function calling to improve ai reliability when working with kuberetes

deploy airflow cluster into kubernetes cluster with CeleryExecutor

A Kubernetes security scanner powered by Generative AI (GenAI) for detecting, analyzing, and remediating security risks in Kubernetes pods. It leverages AWS Bedrock’s Large Language Models (LLMs) to analyze pod configurations and identify vulnerabilities in real-time.

Apache Airflow IDE with Kubernetes Operator capabilities

Manifests for AI Workload on Kubernetes

Airflow helm chart for GKE with KubernetesExecutor

An AI-driven DevOps platform that enables autonomous fault detection and recovery in Kubernetes environments. Uses anomaly detection and predictive failure modeling to identify system instability, trigger automated remediation, optimize resource allocation, and enhance production reliability at scale.