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docker-compose

A security-focused project designed to identify, analyze, and manage Common Vulnerabilities and Exposures (CVEs) in software systems. It evaluates the severity of known vulnerabilities, monitors security issues, and provides actionable remediation recommendations to help developers and security teams strengthen system security, minimize potential threats, and reduce the risk of cyberattacks.

-This focuses on improving software security by helping users discover and address known vulnerabilities before they can be exploited.

-Vulnerability Identification: Identifies known security weaknesses in software using CVE records.

-Vulnerability Analysis: Examines identified vulnerabilities to understand their potential impact and severity.

-Severity Assessment: Helps prioritize vulnerabilities based on their risk level, allowing critical issues to be addressed first.

-Security Issue Tracking: Keeps track of known vulnerabilities so teams can monitor and manage them effectively.

-Remediation Recommendations: Suggests corrective actions, such as applying security patches, updating software, or changing configurations.

-Risk Reduction: Helps prevent potential security breaches by encouraging timely detection and resolution of vulnerabilities.

A self-hosted AI platform: inference, tool use, browser automation, image generation, speech synthesis, transcription, object storage, agentic code execution, and more, behind a single OpenAI-compatible endpoint. One docker-compose up.

Lightweight object storage that speaks S3 (boto3/AWS SDK compatible), plain HTTP, and MCP. SQLite for metadata, flat files on disk.

Docker-based sandbox for running OpenCode with optional MCP services, including a Python CLI wrapper, persistent config/data volumes, and CI checks for tests and container startup.

Configurations and scripts to deploy tileserver-gl with varnish caching using docker-compose

Health-aware Docker Compose deployments

An orchestrator for Docker Swarm and Compose deployments with device targeting and automated NFS storage provisioning

NestJS + TypeORM + PostgreSQL API for a truck tire and wheel store: catalog, faceted filters, cart and orders, CSV price-list import, JWT auth, admin CMS endpoints. Restored 2024 archive.

NestJS 10 + PostgreSQL REST API and headless CMS: content modules, JWT auth with group-based access, lead capture, image uploads, and Telegram review moderation via inline callbacks.

Un site web de visionnage/recherche de bibliothèque Calibre, avec des affichages spécifiques pour liseuse, smartphone et PC. Permet aussi de créer des index en ePub, à télécharger et distribuer. Disponible sous Windows, Linux, Docker-compose. Licence EUP-GPL

NestJS 10 platform service behind the Mammoth Dev site: CMS content, product catalog, cart and orders, contact leads, Telegram bot, SendGrid email, Swagger. Archived — no live instance.

REST API for the Everdime website: headless CMS string storage, investor lead capture, JWT admin auth. NestJS 9 + TypeORM + MariaDB + Swagger. Restored 2024 archive with migrations and content seed.

NestJS 10 + TypeORM + PostgreSQL API of the Lotus Manzara Büyükçekmece villa site: lead capture, CMS content, JWT auth, uploads. Restored 2024 archive with a working Docker/nginx deploy reference.

A production-grade machine learning system for classifying celestial objects — stars, galaxies, and quasars — from 500,000 photometric observations sourced from the Sloan Digital Sky Survey (SDSS DR18). The pipeline covers LOF-based outlier detection, SMOTEENN class balancing, and SelectKBest feature selection, with six classifier configurations benchmarked against each other. Random Forest achieved the highest accuracy at ~99.51%, while LightGBM was selected for deployment due to its faster inference, smaller footprint, and clean ONNX export path. The system is fully containerized with Docker, backed by a CI/CD pipeline, and served live via a Gradio interface on Hugging Face Spaces.

Turn-key Docker TrinityCore 3.3.5 WotLK server

An easy-to-setup and secured Traefik based reverse proxy using docker compose to host multiple docker based project on the same machine.

Sistema de predicción de enfermedades cardíacas usando Machine Learning

PHP Symfony Project in Symfony 5 PHP 8 for learning purpose : PHP, Symfony, CI/CD

Open Source Embedded C/C++ Project Template with dockerized development environment and MISRA C/C++ support.