Business Use Case:

A company wants to provide its data scientists, analysts, and business users with powerful data visualization and exploration tools. Deploying Apache Superset on Amazon EKS offers scalable, efficient data analytics capabilities, enhancing decision-making processes and operational insights.

Overview:

This guide outlines deploying Apache Superset on an Amazon EKS cluster using Postgres as the backend database and Amazon EBS for persistent storage. It leverages Kubernetes for managing deployment, scaling, and services.

Detailed Steps:

1. Infrastructure Setup:

• VPC Creation: Set up a new VPC with public and private subnets.

• EKS Cluster: Provision an EKS cluster control plane and managed worker nodes.

• Amazon EBS: Create an Amazon EBS file system for persistent storage.

  
  

2. Docker and Container Management:

• Build Docker Images: Build and push Docker images for Superset to Amazon ECR.

• Helm Chart Deployment: Install Superset and its services on EKS using a Helm chart.

3. Exposing the Superset UI:

• Load Balancer Setup: Enable ingress and use AWS LoadBalancer Controller to provision an ALB for the Superset frontend UI.

• Accessing Superset: Retrieve the Superset UI URL from the EKS cluster and log in to the interface.

4. Data Integration and Visualization:

• Database Connection: Connect Superset to a Postgres database hosted on the Superset node.

• Data Upload: Configure the database to allow file uploads and create datasets for visualization.

Business Value:

• Scalability: Leverages Kubernetes for scalable deployment and management.

• Efficiency: Uses AWS services for optimized performance and cost-efficiency.

• Accessibility: Provides a user-friendly interface for data exploration and visualization.