Kubernetes Helm Airflow

This repository contains the necessary configuration files and DAGs (Directed Acyclic Graphs) for setting up a robust data engineering environment using Kubernetes and Apache Airflow. It includes the setup for the Kubernetes Dashboard, which provides a user-friendly web interface for managing Kubernetes clusters, and Apache Airflow, a platform to programmatically author, schedule, and monitor workflows.

DAGs

hello.py: A simple example DAG to demonstrate basic Airflow concepts.

Kubernetes (k8s) Configuration

dashboard-adminuser.yaml: YAML file for setting up an admin user for the Kubernetes Dashboard.
dashboard-clusterrole.yaml: YAML file defining the cluster role for the Kubernetes Dashboard.
dashboard-secret.yaml: YAML file for managing secrets used by the Kubernetes Dashboard.
recommended-dashboard.yaml: YAML file for deploying the recommended Kubernetes Dashboard setup.
values.yaml: YAML file containing values for customizing the Kubernetes setup.

Getting Started

Prerequisites

A Kubernetes cluster
kubectl installed and configured
Helm (optional, but recommended for managing Kubernetes applications)

Setup

Deploy the Kubernetes Dashboard:

To deploy the Kubernetes Dashboard, apply the YAML files in the k8s directory:
```
kubectl apply -f k8s/ --validate=false
```
This will set up the Kubernetes Dashboard with the necessary roles and permissions.
Accessing the Kubernetes Dashboard:

To access the Dashboard, you may need to start a proxy server:
```
kubectl proxy
```
Then, access the Dashboard at http://localhost:8001/api/v1/namespaces/kubernetes-dashboard/services/https:kubernetes-dashboard:/proxy/.

Use the token generated for the admin user to log in (see dashboard-secret.yaml).
Retrieve Dashboard Token using kubectl:

If you need to access the Kubernetes dashboard and require a token for authentication, you can retrieve it using kubectl. Use the following command:
```
kubectl get secret admin-user -n kubernetes-dashboard -o jsonpath="{.data.token}" | base64 --decode > output.txt
```
After running this command, you'll find the token required for dashboard login in the output.txt file.
Deploy Apache Airflow:

You can deploy Apache Airflow using Helm or by applying custom YAML files. For Helm:
```
helm repo add apache-airflow https://airflow.apache.org
helm install airflow apache-airflow/airflow -f k8s/values.yaml --namespace airflow --create-namespace --debug
```
This will deploy Airflow with the settings defined in values.yaml.
Access Airflow Webserver via Port Forwarding:

To access the Apache Airflow webserver interface from your local machine, you can use kubectl to set up port forwarding. Execute the following command:
```
kubectl port-forward svc/airflow-webserver 8080:8080 --namespace airflow
```
Once you run this command, you can access the Airflow web UI by navigating to http://localhost:8080 in your web browser. This will route the traffic from your local machine's port 8080 to the Airflow webserver's port 8080 in the Kubernetes cluster.
Accessing Airflow:
- Login Credentials: Go to http://localhost:8080 and type the Username admin and password admin.
- Dashboard Overview: After logging in, you will see the main page displaying a DAG: hello_world.
  - Activating hello_world DAG: Toggle the start button for hello_world and click on it to view DAG details.
Uninstall Apache Airflow:

If you need to uninstall Apache Airflow, you can do so using Helm with the following command:
```
helm uninstall airflow -n airflow
```
This command removes the Airflow deployment from the specified namespace (airflow in this case).

Usage

Kubernetes Dashboard: Use the Dashboard to monitor and manage the Kubernetes cluster.
Apache Airflow: Access the Airflow web UI to manage, schedule, and monitor workflows.

georgeerol / K8sHelmFlow