Deploy Spark Operator & Airflow on Kubernetes with GitOps | Service Foundry Tutorial

Description

In this video, you’ll learn how to deploy the Spark Operator and Apache Airflow on a Kubernetes cluster using Service Foundry. We walk through the full GitOps-based workflow — from application installation, job namespace configuration, and Argo CD sync, to triggering Spark applications via Airflow DAGs. You’ll see how Service Foundry automates Helm-based deployments, generates Argo CD application manifests, and connects Git repositories with Airflow to orchestrate Spark jobs using the SparkKubernetesOperator. ✅ What you’ll learn: • Installing Spark Operator with GitOps • Setting up Airflow and DAG folders • Managing applications in Argo CD • Triggering Spark workloads via Airflow UI 🔧 Tools used: Kubernetes • Helm • Argo CD • Apache Airflow • Spark Operator • GitHub • Service Foundry Console 📌 Don’t forget to like, subscribe, and check out the rest of our Service Foundry playlist for more DevOps tutorials.