With a solid background in Management Engineering, I am currently a Digital Automation Engineering student specializing in the convergence of Industrial IoT, Distributed Systems, and Cloud-Native Infrastructure. I leverage my dual expertise to build bridge solutions that connect the physical world (Edge) to highly scalable and orchestrated environments (Cloud), always with a focus on process efficiency and data-driven decision making.
I am currently evolving my stack toward the Cloud-Native ecosystem, focusing on:
- Orchestration: Deploying and managing K8s resources (Deployments, StatefulSets, Services, Ingress).
- Security: Implementing RBAC, Secret management, and secure API Gateways with JWT & HttpOnly Cookies.
- Automation (IaC): Provisioning multi-cluster environments on AWS using Terraform.
- Observability: Building full-stack monitoring pipelines with Grafana, InfluxDB, and custom exporters.
| Domain | Tools & Technologies |
|---|---|
| Cloud & Orchestration |     |
| Backend & APIs |    |
| IoT & Edge |    |
| Data & Monitoring |    |
| Automation |   |
A stateless, multi-cluster management platform designed for granular, profile-based access to Kubernetes resources.
- Zero-Trust Architecture: Implemented a stateless authentication system using JWT to encapsulate encrypted K8s Service Account tokens, ensuring credentials never reside on the client-side.
- Dynamic Orchestration: Built with FastAPI and the Kubernetes Python Client to manage Pods, scale Deployments, and perform rollout restarts across multiple clusters through a unified API.
- Stateless Security: Integrated HttpOnly Cookies and RBAC mapping to bridge the gap between simple web interfaces and complex K8s permission structures.
- Infrastructure: Fully containerized with Docker Compose, featuring an Nginx-backed frontend and a secure Python backend.
An E2E MLOps pipeline for industrial assets, transitioning from physical simulation to a fully containerized Digital Twin environment.
- Digital Twin Engine: Developed high-fidelity Python simulators modeling ISO 10816 vibration standards and non-linear degradation curves with a built-in Chaos Engine for stress testing.
- Distributed Microservices: Engineered a decoupled architecture using MQTT (Mosquitto), FastAPI, and InfluxDB 2.x for real-time telemetry processing (100+ concurrent assets).
- MLOps Workflow: Designed an offline-to-online pipeline where Random Forest models are trained on historical InfluxDB data and hot-loaded into AWS-hosted inference services for real-time diagnostics.
- IaC & DevOps: Automated the entire AWS (EC2) ecosystem provisioning using Terraform.
A multi-site industrial data platform leveraging AWS IoT Core for secure, event-driven telemetry ingestion.
- Event-Driven Processing: Implemented an AWS Lambda Multiplexer to intercept MQTT streams, evaluate dynamic thresholds, and trigger automated SNS alerts.
- Industrial Security: Enforced X.509 certificate authentication and mTLS encryption for every simulated device, ensuring strict topic isolation and identity management via Terraform.
- Full-Stack Monitoring: Orchestrated a Dockerized analytics stack on EC2 featuring InfluxDB for time-series persistence and Grafana for real-time factory dashboards.
A full-stack ecosystem bridging ESP32 edge devices with a modular Python monolith and AI-powered interfaces.
- Edge Layer: Wrote robust C++ firmware for ESP32 with JSON-based protocols for bidirectional telemetry and remote actuator control (Servos/Fans).
- Conversational UI: Developed a Telegram Bot integrated with n8n and private Webhooks, allowing remote system orchestration and LLM-powered status queries.
- Modular Monolith: Built a scalable backend with FastAPI and Pydantic, featuring role-based Bearer Token security and InfluxDB integration.
Beyond structured projects, I maintain a continuous laboratory of autonomous workflows using n8n:
- AI Orchestration: Integrating LLMs (OpenAI/Anthropic) with STT (Speech-to-Text) and TTS (Text-to-Speech) for voice-controlled automation.
- API Mashups: Custom integrations between Telegram, Google Services, and third-party SaaS to automate data processing and alerting.
- Smart Agents: Building event-driven agents that monitor web sources and generate AI-summarized insights directly to private channels.
- Advanced K8s Networking: Deep diving into Service Meshes and advanced Ingress controllers.
- GitOps: Implementing CI/CD pipelines for automated infrastructure deployments.
- SRE Principles: Focus on scalability, reliability, and monitoring of distributed systems.
"I build resilient infrastructures for an automated future."