📊 Employee Task Management System

Overview

The Employee Task Management System is a robust web application developed using Python and Django, designed to streamline employee task management. It enables efficient task assignment, tracking, and provides analytical insights through an interactive dashboard using Matplotlib. Anaconda is recommended for an isolated and secure development environment.

✨ Key Features

• 🐂 Task Management: Assign, track, and update employee tasks with ease.
• 🔒 User Authentication: Secure login and role-based access control for employees and administrators.
• 📊 Analytical Dashboard: Gain insights into task completion and performance metrics with Matplotlib.
• 📁 Reporting: Generate detailed reports on employee efficiency and task progress.
• 🛠️ Admin Interface: Manage users, tasks, and system settings through Django Admin.

🌟 Project Glimpse

🎥 Video Demonstration

DockerProfile for Image: Image

Check out the video demonstration: Watch Video

🚀 Installation Guide

1️⃣ Clone the Repository

git clone https://github.com/yourusername/EmployeeTaskManagementSy.git
cd EmployeeTaskManagementSy

2️⃣ Set Up Anaconda Environment

conda create --name task_management_env python=3.8
conda activate task_management_env

3️⃣ Install Dependencies

pip install -r requirements.txt

4️⃣ Configure Database

python manage.py makemigrations
python manage.py migrate

5️⃣ Create Admin Superuser

python manage.py createsuperuser

6️⃣ Collect Static Files

python manage.py collectstatic

7️⃣ Run the Development Server

python manage.py runserver

Access the application at: http://127.0.0.1:8000/

🐳 Deployment with Minikube, Kubernetes & Podman

1️⃣ Install Required Tools

• Enable WSL: Install WSL
• Enable Hyper-V: Run the following command in PowerShell (Admin):

  Enable-WindowsOptionalFeature -Online -FeatureName Microsoft-Hyper-V-All

• Podman: Download Podman
• Minikube: Install Minikube
• Kubernetes CLI: Install via Chocolatey:

  choco install kubernetes-cli -y

2️⃣ Initialize Podman Machine

podman machine init
podman machine init --name employee-task-machine --cpus 2 --memory 2200 --disk-size 20
podman machine start employee-task-machine

3️⃣ Build and Export Docker Image as TAR

cd EmployeeTaskManagementSy
podman build -t employeetaskmanager:latest .
podman save -o employeetaskmanager.tar employeetaskmanager:latest

4️⃣ Load TAR File into Minikube

minikube start --driver=docker
minikube image load employeetaskmanager.tar
minikube ssh
docker images | grep employeetaskmanager

5️⃣ Deploy to Kubernetes

Apply the deployment:

kubectl apply -f deployment.yaml

Verify the deployment:

kubectl get pods
kubectl get services

Access the application:

minikube service employee-task-app --url

ℹ️ Additional Information

• Technologies Used: Python, Django, Matplotlib, Anaconda, Minikube, Kubernetes, Podman
• License: © [Gajal Rathore, Kushi Verma, Darshana Partidar, Ashmeet Singh]. Usage permitted with consent.

💎 Alternative Setup (Without Podman)

If you want to deploy directly using Docker instead of Podman:

1️⃣ Install Docker & Minikube

• Download Docker
• Install Minikube

2️⃣ Build and Load Image into Minikube

docker build -t employeetaskmanager:latest .
minikube image load employeetaskmanager:latest

3️⃣ Deploy to Kubernetes

Apply the deployment:

kubectl apply -f deployment.yaml

Check the deployment:

kubectl get pods
kubectl get services