SSH server ready to be deployed into Cloud Run.

Ultimate WordPress setup on (GCP) Cloud Run, Cloud SQL & GCS buckets

Cloud Run packet capturing sidecar

A Flask app running GraphRAG for healthcare, made with Vertex AI and Neo4j, to be deployed in a container (Cloud Run or ECS).

An AI-powered backend empowering the visually impaired through image recognition, OCR, and audio transcription

This is the Backend of Mental Health Assistant which capable of mental state of patient and suggests treatments to the mental health Problems

An example micro service written in Zig using the Zap Web Framework. Container images are built using the Chainguard Images ready for deployment to Google Cloud Run.

Basic authentication module with 2FA, made with NestJS and Twilio Service and database I used Google Cloud Firestore. I used swagger for api documentation.

Is a small project where I practice my backend skills with NestJS Framework and implements third party services in this case I integrated the twilio service for create a two factor authentication

Bash script to rename Google Cloud Run default template files.

LearnSphere is an AI-powered full-stack MERN application designed to assist educators. It integrates Google Cloud services like Calendar, Gmail, Meet, and Sheets to automate assignments, schedule classes, check student submissions, and analyze performance. Deployed on GCP Cloud Run, it uses OAuth 2.0 for secure access

Create a Backend Web Service (API) for Skin Cancer prediction

Pruebas y aprendizaje con Google Cloud Run para desplegar aplicaciones serverless

Frontend code for the ATS Resume scorer web Application. Most updated versions available.

Fullstack twitter clone with MERN stack

This repository contains machine learning models designed to identify diseases in various plants, specifically focusing on tomatoes, mangoes, and chilies. Each model is trained on a dataset tailored to its respective plant, ensuring accurate disease detection.

This project is designed to scrape the latest news articles related to plant care and management from Google News. The scraper is implemented as a Google Cloud Function that is triggered by Pub/Sub messages. The scraped data is stored in a Firestore database for easy access and retrieval.

This project implements a weather data service using the Model Context Protocol (MCP), designed to be consumed by intelligent agents (e.g., LLM agents). It's built with Python, containerized with Docker, and deployed to Google Cloud Run with continuous deployment configured from GitHub.