Cloud-Native Platform Engineering • DevOps • Observability • AI-Enabled Operations

Engineer with background in embedded systems, IoT, and real-time systems, currently focused on cloud-native backend and DevOps-oriented engineering.

I am building hands-on systems around cloud infrastructure, platform engineering, containerized deployment, telemetry pipelines, observability, automation, and AI-assisted operational workflows.

Currently working with:

• Cloud-native backend and observability platforms
• Infrastructure as Code using Terraform
• AWS cloud infrastructure and EC2 deployment workflows
• Dockerized multi-service application stacks
• Kubernetes and container orchestration fundamentals
• Prometheus/Grafana monitoring and telemetry systems
• GitHub Actions CI workflows
• Linux-based cloud deployment and networking environments

End-to-end cloud-native telemetry and observability platform with MQTT-based ingestion, REST APIs, PostgreSQL persistence, Prometheus/Grafana monitoring, Infrastructure as Code using Terraform, and cloud deployment on Amazon EC2.

• MQTT-based telemetry ingestion using AWS IoT Core
• Serverless telemetry processing using AWS Lambda and Amazon S3
• FastAPI backend for REST-based telemetry ingestion and retrieval
• PostgreSQL persistence for historical sensor data
• Prometheus metrics collection and Grafana dashboards
• Docker Compose deployment of multi-container services
• Infrastructure as Code workflows using Terraform for AWS EC2 provisioning and security group configuration
• Local Kubernetes deployment workflow
• AWS EC2 cloud deployment on Ubuntu Linux
• GitHub Actions CI/CD pipeline for validation and Docker image builds
• AI-assisted telemetry analysis using Ollama and FastAPI
• Automated operational summaries generated from historical telemetry data
• AI observability dashboard integration through REST APIs

The platform integrates a self-hosted AI observability assistant using Ollama and FastAPI.

Telemetry data stored in PostgreSQL is analyzed by an open-source LLM to generate operational summaries, identify abnormal trends, and provide human-readable insights directly through the dashboard and REST APIs.

Key capabilities:

• Historical telemetry analysis
• Automated operational summaries
• AI-assisted anomaly identification
• Self-hosted LLM deployment using Ollama

🔗 https://github.com/umair95-prog/iot-cloud-platform

Currently expanding knowledge in:

• Advanced Kubernetes deployment workflows
• Automated cloud deployment pipelines
• Platform engineering practices
• Cloud-native scalability and orchestration
• AI-assisted observability and operational intelligence
• AIOps and intelligent monitoring workflows
• Secure cloud networking and infrastructure hardening

• Email: umairrao95@gmail.com
• Location: Germany