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Kubernetes-Based Course Delivery System

Objective:

To develop a scalable, resilient, and cloud-native platform for delivering online courses using Kubernetes for container orchestration, ensuring high availability and efficient resource utilization.

Why Choose This Project:

  • Provides automated scaling and management of course delivery services.

  • Ensures seamless access for a large number of concurrent learners.

  • Integrates cloud-native architecture, containerization, and DevOps practices, which are essential for modern e-learning platforms.

  • Reduces downtime and enables faster deployment of course updates.

Key Features:

Feature Description
Containerized Services Each module (video streaming, quizzes, analytics) runs in isolated Docker containers.
Automated Scaling Kubernetes automatically scales pods based on user demand.
High Availability Ensures uninterrupted access with replicas and load balancing.
Continuous Deployment Supports CI/CD pipelines for fast deployment of course updates.
Monitoring & Logging Collect metrics and logs from all containers for performance and troubleshooting.
Multi-Tenant Support Host multiple courses or institutions on the same cluster securely.
Cloud Integration Deployable on AWS EKS, Azure AKS, or GCP GKE for cloud-native scaling.

Technology Stack:

  • Frontend: HTML, CSS, JavaScript, React.js / Angular.

  • Backend: Node.js (Express) or Python (Django / Flask).

  • Containerization: Docker for packaging microservices.

  • Orchestration: Kubernetes (K8s) for deployment, scaling, and management.

  • Database: MySQL / PostgreSQL / MongoDB.

  • CI/CD Tools: Jenkins, GitLab CI/CD, or GitHub Actions for automated deployments.

  • Monitoring & Logging: Prometheus, Grafana, and ELK Stack (Elasticsearch, Logstash, Kibana).

  • Cloud Platform: AWS EKS, Azure AKS, or GCP GKE.

Working Flow:

  1. Course Content Deployment

    • Course services (video streaming, quizzes, assignments) are packaged as Docker containers.

  2. Kubernetes Cluster Deployment

    • Containers are deployed as pods in Kubernetes clusters.

    • Load balancing distributes traffic among pods.

  3. Auto-Scaling & Resource Management

    • Kubernetes monitors CPU/memory usage and scales pods automatically.

  4. Continuous Updates

    • CI/CD pipelines deploy updated course content without downtime.

  5. Monitoring & Logging

    • Prometheus and Grafana track metrics; ELK stack collects logs for analysis.

  6. Student Access

    • Learners access courses through a web interface, while Kubernetes ensures stable and fast delivery.

Main Modules:

  1. Course Content Service Module (video, quizzes, assignments)

  2. User Authentication & Access Module

  3. Kubernetes Deployment & Scaling Module

  4. CI/CD Deployment Module

  5. Monitoring & Logging Module

  6. Analytics & Reporting Module

Security Features:

  • Role-based access control for students, teachers, and admins.

  • Secure communication using HTTPS and TLS.

  • Network policies in Kubernetes to isolate services.

  • Encrypted storage for course content and user data.

This Course Fee:

₹ 2799 /-

Project includes:
  • Customization Icon Customization Fully
  • Security Icon Security High
  • Speed Icon Performance Fast
  • Updates Icon Future Updates Free
  • Users Icon Total Buyers 500+
  • Support Icon Support Lifetime
Secure Payment:
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