Deploy Python AI Chatbot Using Secure CI/CD and DevOps Tools

Master CI/CD pipeline to build, secure, and deploy Python AI chatbots with Jenkins, Docker, SonarQube & OWASP tools.

What you'll learn
- Understand secure coding principles and the importance of secure software development practices in AI applications.
- Compare traditional Waterfall and modern CI/CD approaches for software development and deployment.
- Build an AI-powered Spoken English Chatbot using Python, and version control code using Git and GitHub.
- Manually deploy the chatbot on an AWS EC2 instance, set up virtual environments, install dependencies, and run the app via Streamlit.
- Set up and configure Jenkins and SonarQube in a cloud environment for continuous integration and code quality analysis.
- Install and manage essential DevOps tools in Jenkins, including Docker, JDK, SonarQube, and OWASP Dependency-Check.
- Automate cloning of repositories and installation of Python dependencies using Jenkins pipelines.
- Integrate SonarQube and OWASP into Jenkins pipelines for code analysis and security vulnerability scanning.
- Deploy the chatbot as a Docker container using Jenkins pipelines and ensure secure and optimized Docker configuration.
- Troubleshoot, validate, and finalize the chatbot deployment, including resolving permission errors and managing AWS IAM credentials securely.

Requirements
- Basic knowledge of CI/CD concepts (pipelines, build, deploy)
- AWS Account (Free Tier is sufficient for this course)
- Familiarity with Git and GitHub (clone, commit, push/pull)
- Basic command-line skills (Linux terminal or Windows CMD/PowerShell)
- A computer with internet access, preferably with 8GB+ RAM
- Ability to install tools (Python, VS Code, Jenkins, Docker, etc.)
- No advanced cloud knowledge or DevOps experience is needed — everything is taught step by step.

Description
Learn to build and securely deploy aPython-based AI Spoken English Chatbotusing real-worldDevOpstools! This hands-on course guides you from secure coding basics to setting up CI/CD pipelines withGit,Jenkins,SonarQube,Docker, andOWASP. You'll manually deploy your chatbot on AWS EC2, then automate the process using industry-standard practices.

Perfect for developers, DevOps learners, and AI enthusiasts - gain practical experience in secure coding, automation, and chatbot deployment in one complete project-based course.

Introduction and Secure Coding: Basics

Getting Started: Course Objectives & Structure

Introduction to Secure Coding

Secure Coding: Why it matters?

Development Lifecycle: Waterfall Model to CI/CD Tools

Overview of AI Spoken English Chatbot

Phases of the Waterfall Model

Drawbacks of the Waterfall Model

How CI/CD Tools Improve Waterfall Model

Getting Started: Build Your AI Chatbot and Set Up Git Workflow

Develop AI Chatbot with Python

Git Bash Setup with Repo for Chatbot Code

Push Code from Local to Repository Using Git Bash

Deployment of a Python-Based AI Chatbot Using a Manual Approach (Without DevOps)

Deploy an Ubuntu EC2 instance in AWS

Create a Python virtual environment using venv

Install project dependencies using pip

Clone Git Repo on VM

Install AWS CLI tool

Create IAM User with Permissions

Allow Port 8501 for Streamlit UI

Run Chatbot and Access via Web

SonarQube Setup for Python Chatbot CI/CD Pipeline

Overview of the Project

Set Up Virtual Machine for SonarQube

Docker Installation for SonarQube Deployment

Run SonarQube in a Docker Container

Access SonarQube Dashboard via Port 9000

Jenkins Setup for Python Chatbot CI/CD Pipeline

Provision an Ubuntu Virtual Machine for Jenkins

Install Java, Docker & Jenkins on the Server

Access the Jenkins Web UI via Browser

Configuring Jenkins for DevOps and Tool Integration

Install and Manage Jenkins Plugins

Jenkins Tool Setup: JDK, SonarQube, OWASP & Docker

Configure Jenkins Authentication with SonarQube

Configure SonarQube Server in Jenkins

Enable Sudo for Jenkins User

Python Project Setup via Jenkins Pipeline

Cloning the GitHub Repository via Pipeline

Pipeline Stage: Install Python Requirements

Add Python Dependencies File to Repo

Run Pipeline & Check Logs

Fix Issues & Re-execute Pipeline

Integrating SonarQube with Jenkins CI/CD Pipeline

Intro to SonarQube and Properties File

Install SonarScanner on Jenkins Server

Add SonarQube Analysis Stage in CI/CD Pipeline

Run the Jenkins Pipeline

Fix and Re-run Jenkins Pipeline

Integrating OWASP Dependency-Check into Jenkins CI/CD Pipeline

Overview of OWASP Dependency-Check Tool

OWASP Scan: Prerequisites Checklist

Understanding Jenkins Pipeline for OWASP Scan

Trigger the Pipeline Job

OWASP Dependency Check Report Summary

CI/CD Deployment of Chatbot with Docker

Add Pipeline Stage: Deploy Chatbot using Docker

Understanding the Dockerfile for Chatbot Deployment

Docker Access for Jenkins & Port 8501

Optimize Docker Build with .dockerignore

Trigger and Monitor Jenkins Pipeline

Access the Chatbot in Your Browser

Troubleshooting and Finalizing Chatbot Deployment

Validation Error Encountered

Create IAM User with Required Permissions

Configure AWS Credentials in Jenkins

Re-run Jenkins Pipeline and Access AI Chatbot

Last lecture

Who this course is for:
- Aspiring DevOps Engineers who want hands-on experience with Python and Jenkins CI/CD pipelines.
- QA/Test Engineers aiming to automate deployment and testing workflows.
- Software Developers looking to integrate their Python projects with automated deployment tools.
- Students & Freshers eager to build real-world projects and enhance their resumes.
- IT Professionals transitioning into DevOps or automation roles.
More Info