Python

Example scripts for different environments to build and manage Versa Networks products

TEAF Light — Official Reference Implementation

The official lightweight implementation of the Temporal Enterprise Architecture Framework (TEAF) — an AI-native approach to enterprise architecture focused on intent, knowledge, decisions, automation, execution, observation, and continuous learning.

Designed for practical adoption by SMEs and organizations seeking an AI-ready, observable, traceable, and evolutive information system architecture.

This repository provides the reference foundation for experimenting with TEAF through lightweight Proofs of Concept and operational implementations.

TEAF — From strategic intent to observable execution.

Self-hosted Flask/CUPS service for receiving PDFs via REST or web UI and forwarding them to IPP printers. Multi-architecture Docker images and GitLab CI/CD.

Découverte de ce monde (Data / ML) via un projet perso. Basés sur des relevés météo de différentes sources, avec des outils comme Pandas, Dask, Spark, Polars, ..., du ML et du DL. Une couche de visualisation via PowerBI.

Production‑ready, geo‑distributed NATS messaging backbone with clustering, gateways, leafnodes, JWT authentication, and mutual TLS

Run the GitLab Environment Toolkit (GET) in a VS-Code Dev Container

I designed and published a professional focused on pipeline reusability, security, and code quality. The project demonstrates real-world DevOps practices such as semantic versioning, reusable CI components, secure container builds with Kaniko, and standardized linting for Python and Django applications. This initiative reflects my approach to building scalable, maintainable CI/CD architectures in enterprise environments.

Key Features:

Native GitLab CI/CD Components Semantic versioning with pinned releases No privileged runners required Enterprise-ready defaults Configurable inputs without pipeline duplication

Included Components:

Kaniko – Secure, daemonless container image builds Pylint – Python static analysis Pylint Django – Django-specific linting rules Flake8 – Python style and code quality checks DjLint – Django template linting and formatting Yamllint – YAML validation and formatting Pytest – Unit testing and code coverage ...

A Terraform module to create and manage a Lambda function that can be invoked with a function URL. Sample Lambda function that can be used with the URL is included.

Author: Eder Ramos for PLAYTRAK AI official repository.

Terraform module to manage a file upload infrastructure using S3 presigned URLs and Lambda.

ElderConnect is a voice care companion for elderly individuals, powered by Amazon Nova Sonic on Amazon Bedrock. It combines real-time bidirectional voice AI with a Reachy Mini robot to create a physical, empathetic presence that helps seniors manage medications, track health concerns, and stay connected with caregivers.

Production style cloud native backend service featuring JWT authentication, health check endpoints, observability metrics, containerized deployment with Docker, and infrastructure as code provisioning using Terraform for scalable AWS ECS environments

MineLogX AI Framework

MineLogX is an AI-powered framework designed to modernize and optimize operations in the mining industry and beyond. The framework provides tools, reference architectures, and development guides that enable scalable data ingestion, analytics, and automation.

Key Features:

📊 AI & Data Processing — Build intelligent workflows for real-time and batch mining data. ☁️ Cloud-Native Setup — Deploy across AWS, Azure, or GCP with ready-to-use infrastructure guides. 🛠️ Developer-Friendly — Includes usage examples, architecture documentation, and contribution guidelines. 🔒 Secure & Scalable — Designed with enterprise-grade security and modular scalability.

This repository contains:

Project documentation (/docs) Contribution and licensing guidelines Reference architectures and cloud setup guides

Whether you’re setting up a proof of concept or extending AI-driven solutions, MineLogX provides the foundation for sustainable, intelligent mining innovation.

Atlas Architect: Your AI Co-pilot for Secure Cloud Infrastructure

This project is an AI-powered DevSecOps agent that lives within GitLab. It proactively analyzes Infrastructure-as-Code (IaC) files, specifically Terraform, to automatically visualize, secure, and optimize a developer's Google Cloud architecture before it's ever deployed.

When a developer submits a Merge Request with Terraform changes, a CI/CD pipeline triggers the agent to post a detailed analysis back as a comment. This provides instant visibility and governance, helping teams build better, safer cloud infrastructure, faster.

Key Features:

AI-Powered Visualization: Generates architecture diagrams from Terraform code using Google's Vertex AI. Security & Cost Analysis: Identifies security vulnerabilities and cost inefficiencies based on best practices. Intelligent Remediation: Automatically suggests code changes to fix identified issues. Vector-Powered Knowledge Base: Uses a MongoDB Atlas Vector Search index of official Google Cloud documentation to provide highly relevant, context-aware explanations for its recommendations.

Core Technologies:

Platform: GitLab CI/CD, Google Cloud Platform (GCP), MongoDB Atlas Services: Google Cloud Run, Google Cloud Build, Google Vertex AI, MongoDB Atlas Vector Search Frameworks & Languages: Python, Flask, Gunicorn

Real-time market data processing and analytics demonstration

Building a Real-World AWS Data Analytics Pipeline: From E-commerce Orders to Machine Learning Recommendations

GCP Dataflow Pipeline