Project: Real-Time Stock Data Application on AWS EKS

Overview

This project showcases the deployment of a Python Flask application on AWS Elastic Kubernetes Service (EKS), utilizing Kubernetes, EKS clusters, and Docker containerization. The live URL has been suspended at this time for cost purposes.

Key Features

• AWS EKS Deployment
• Kubernetes Expertise: Demonstrated experience in managing Kubernetes resources, including pods, deployments, and services.
• Docker Containerization: Creation of a Docker image for the Flask application, ensuring portability and consistency across environments.

Technologies Used

• AWS EKS: For managing and scaling the application infrastructure.
• Kubernetes: As the container orchestration platform.
• Docker: For creating a container image for the kubenetes service to use
• Python & Flask: The core language and framework for the application.

Highlights

1. EKS Cluster Setup: Configured an EKS cluster using eksctl and AWS CLI, streamlining the deployment process.
2. Docker Image Creation: Developed a Docker image of the Flask application, optimized for Kubernetes deployment.
3. Kubernetes Configurations: Utilized Kubernetes best practices for creating and managing namespaces, deployments, services, and ingress resources.
4. Load Balancing: Integrated AWS Load Balancer with Kubernetes, facilitating efficient traffic management.
5. Service Accounts and IAM: Leveraged Kubernetes service accounts and AWS IAM roles for secure and efficient access control.