Project shows how to construct a functioning CI/CD pipeline which uses a Jenkins open-source automation server to deploy CodeBuild artifacts with CodeDeploy. it also shows how to build the deployment infrastructure and automatically deploy application version changes from GitHub to your production environment.

We have used this python project to execute CI/CD pipeline using Jenkins on AWS environment with AWS Devops tools

Checks your test results metadata into github, commit-bound. Acts as a bot. You'll need a GitHub App to use it.

Django web application deployed to AWS via Cloudformation templates, with an infrastructure as code approach following the AWS architecture best practices. The application is a sample blog-like website which can be used as a personal portfolio.

Real world application of Manipulating Excel Sheet using python.

Real-time anomaly detection system for GitHub activity using Airflow, MLflow, and Terraform

This repository focuses on cloud computing and demonstrates how to set up virtual machines, S3, and other services using LocalStack. It provides a comprehensive guide to simulating AWS services locally for development and testing purposes.

An implementation of Grundy's game using minimax decision rule and alpha-beta prunning.

Build modern workflows with AWS MWAA, AWS Step Functions, AWS Glue, and AWS EMR

This project, you will build a full AI pipeline for an image classification task using Convolutional Neural Networks (CNNs). The project will cover data ingestion, preprocessing, model training, deployment, and CI/CD integration using GitHub Actions, Docker, and AWS.

AegisFlow is a threat-aware CI/CD pipeline that integrates real-time threat intelligence (AlienVault OTX), MITRE ATT&CK-based static analysis, and SBOM-driven CVE detection to automate secure software delivery.

A comprehensive guide to Docker – covering core concepts, engine components, image lifecycle, Dockerfile structure, registries, containers, use cases, and visual workflow with Mermaid.

Substitutes git submodules and provides an easy way to manage microservices under a single unified platform.

Unlock the future of cricket scores with Cricket-Prophet's AI-powered predictions.

The **AWS SageMaker + Snowflake ML Pipeline** is a fully production-grade, end-to-end machine learning workflow designed to ingest large-scale data from Snowflake, perform feature engineering with Apache Spark, and train, tune, and deploy models on AWS SageMaker—all orchestrated and versioned with CI/CD, Terraform, and Ansible.

RedBricks is a FastAPI web app for tweet sentiment analysis using a pre-trained LSTM model. It provides an API for sentiment prediction and is deployed on Koyeb with an automated CI/CD pipeline via GitHub Actions. For deployment details, refer to the linked Medium article.

A simple python application for managing assets

The scene-assets-library is a structured directory that houses all assets related to scene creation and management for a large-scale project.