12.0 Project

Learning Objectives

By the end of this capstone project, you will be able to:

  • Code a complete Python application that integrates with a Large Language Model (LLM) service

  • Integrate all DevOps concepts learned throughout the course into a real-world application

  • Design and implement a complete CI/CD pipeline for a cloud-native application

  • Deploy applications to production using containers, Kubernetes, and cloud platforms

  • Apply infrastructure as code principles for reproducible and scalable deployments

  • Implement monitoring, logging, and security best practices for production systems

  • Demonstrate collaborative development workflows using Git, code reviews, and documentation

  • Troubleshoot and optimize real-world deployment issues and performance bottlenecks

  • Present technical solutions effectively to stakeholders and receive constructive feedback

Build and deploy a complete Python application with LLM integration in the cloud

Project purpose

Note

This project is optional!

If you choose to do this project you will supplement the theoretical knowledge gained during the course with practical experience that will help you a lot in understanding how and when you can apply the knowledge learned in this course.

Project Prerequisites

This capstone project integrates all the DevOps concepts you’ve learned throughout the course. The project is structured as progressive tasks that will give you insight into real-world DevOps workflows.

Course Foundation Required:

Before starting this project, you should have completed the course modules covering:

  • Linux system administration and scripting

  • Git version control and collaboration workflows

  • Python programming and application development

  • Containerization with Docker

  • Kubernetes orchestration and deployment

  • CI/CD pipeline design and implementation

  • Infrastructure as Code (Terraform/Ansible)

  • Cloud platforms and services

  • Monitoring, logging, and security practices

Why This Project Matters:

DevOps work focuses on helping development teams be more productive through automation, reliable infrastructure, and streamlined processes. This project will make you a well-rounded developer who understands the complete software delivery lifecycle.

Project Overview

Note

This project is optional but highly recommended!

This capstone project allows you to apply the theoretical knowledge gained during the course in a practical, real-world scenario. You’ll build a complete application that demonstrates your mastery of DevOps principles and practices.

What You’ll Build:

You need to create a complete Python application (or challenge yourself with Go, Ruby, JavaScript, or Scala) that integrates with a Large Language Model (LLM) service of your choice.

Project Scope:

Building an LLM-integrated microservice involves multiple phases:

  1. Planning & Setup: Environment configuration and project structure

  2. Development: Application logic and LLM service integration

  3. Testing: Automated testing and quality assurance

  4. Deployment: Containerization and cloud deployment

  5. Operations: Monitoring, maintenance, and documentation

LLM Service Options:

You can choose from any of the following LLM services (or others):

Application Ideas:

If you need inspiration, consider building one of these applications:

  • Conversational Chatbot: Web-based chat interface with context memory

  • Document Analysis Tool: Upload and analyze documents with AI insights

  • Code Assistant: Help developers with code review, generation, or debugging

  • Content Generator: Create blogs, articles, or creative writing with AI assistance

  • Q&A System: Domain-specific question answering (e.g., technical support, education)

  • Translation Service: Language translation with additional context or features

  • Custom Solution: Any other LLM-powered application that solves a real problem

Quality Standards:

Your application must be production-ready with proper architecture, comprehensive error handling, structured logging, and an intuitive user interface.

Learning Path:

This project builds upon everything you’ve learned: Linux server management, dependency automation, application development, architecture design, testing, packaging, and deployment across Linux, Docker, Kubernetes, and cloud platforms.

Timeline & Reviews

Project Timeline:

  • Start: Any time during the course

  • Completion: By the end of the course

  • Peer Review: Required before instructor review

  • Final Review: Schedule with course instructors

Review Process:

Before scheduling your final instructor review, you must:

  1. Complete all project requirements (see checklist below)

  2. Obtain at least one peer review from a fellow student

  3. Address any feedback from the peer review

  4. Prepare your project demonstration and documentation

Project Requirements Checklist

Use this checklist to track your progress and ensure you meet all requirements before your final review.

Application Architecture

Core application components and design

  1. Web Application: Build a complete web application with both frontend and backend components

    • Frontend: Interactive user interface (web-based)

    • Backend: RESTful API or similar service architecture

    • Database: Optional but recommended for data persistence

    • Authentication: User login/authentication system required

  2. LLM Integration: Successfully integrate with at least one Large Language Model service

    • Choose from OpenAI, Anthropic Claude, Google Gemini, or Hugging Face

    • Implement proper API handling and error management

    • Include rate limiting and cost management considerations

  3. Internet Accessibility: Application must be publicly accessible

    • Deploy to a cloud platform (AWS, Azure, GCP, or similar)

    • Configure HTTPS/SSL certificates for secure communication

    • Implement proper domain and DNS configuration

Development & Testing

Code quality and development workflow practices

  1. Code Quality: Follow professional development standards

    • Use proper code structure and design patterns

    • Implement comprehensive error handling and logging

    • Include unit tests and integration tests

    • Follow coding standards and best practices for chosen language

  2. Version Control: Demonstrate professional Git workflows

    • Use meaningful commit messages and proper branching strategy

    • Implement code review process with pull requests

    • Maintain clean project history and documentation

Deployment & Operations

Infrastructure, containerization, and automation

  1. Containerization: Package application using Docker

    • Create optimized Dockerfiles for each component

    • Use multi-stage builds where appropriate

    • Implement proper container security practices

  2. Orchestration: Deploy to Kubernetes cluster

    • Create Kubernetes manifests or Helm charts

    • Implement proper resource limits and requests

    • Configure services, ingress, and persistent volumes as needed

  3. Infrastructure as Code: Automate infrastructure provisioning

    • Use Terraform, Ansible, or similar IaC tools

    • Create reproducible and version-controlled infrastructure

    • Document infrastructure dependencies and requirements

  4. CI/CD Pipeline: Implement automated build and deployment

    • Automated testing on code commits

    • Automated building and packaging of applications

    • Automated deployment to staging and production environments

    • Include rollback capabilities for failed deployments

Monitoring & Security

Production readiness and operational excellence

  1. Observability: Implement comprehensive monitoring

    • Application logging with structured logs

    • Health checks and readiness probes

    • Performance metrics and monitoring dashboards

    • Alerting for critical issues

  2. Security: Follow security best practices

    • Secure secret management (no hardcoded secrets)

    • Vulnerability scanning in CI/CD pipeline

    • Implement proper authentication and authorization

    • Follow OWASP security guidelines

Documentation & Presentation

Communication and knowledge sharing

  1. Documentation: Create comprehensive project documentation

    • Architecture overview and design decisions

    • Setup and deployment instructions

    • API documentation and user guides

    • Troubleshooting and maintenance procedures

  2. Project Presentation: Prepare final project demonstration

    • Live demo of working application

    • Explanation of technical choices and trade-offs

    • Discussion of challenges faced and solutions implemented

    • Q&A session with technical reviewers

Success Tips

Start Early: Begin planning and setting up your development environment as soon as possible.

Iterate Frequently: Build your application incrementally, testing each component as you go.

Document Everything: Keep detailed notes of your decisions, challenges, and solutions.

Ask for Help: Use the course community and instructors when you get stuck.

Focus on Learning: The goal is to demonstrate your understanding of DevOps concepts, not to build the perfect application.