I'm Khwaja Nawaz, a DevOps & Cloud Engineer currently pursuing my
🎓 MSc in Cloud Computing – Newcastle University, United Kingdom
🎓 B.Tech in Computer Science & Engineering – India (Completed)

I love working on:

• 🚀 CI/CD pipelines that take code from commit → test → deploy with zero friction
• ☁️ Cloud-native architectures on AWS (and exploring Azure)
• 🐳 Containers + Kubernetes for scalable, self-healing systems
• 🛡 DevSecOps practices that keep everything secure end-to-end

I’m obsessed with automation, reliability, and real-world problem solving – from backend pipelines to full-stack apps like VoiceShield.

• 🏗 Building CI/CD pipelines with Jenkins, GitHub Actions, and AWS CodePipeline
• ☁️ Designing AWS architectures with EC2, S3, EKS, VPC, ALB, Auto Scaling
• 🐳 Running Dockerized applications and deploying them on Kubernetes
• 📊 Setting up Prometheus + Grafana dashboards for metrics & alerting
• 📚 Deep-diving into Terraform, DevSecOps, and multi-cloud (AWS + Azure)

AWS	Azure	Linux	Ubuntu	Windows

Git	GitHub	Jenkins	GitHub Actions	Docker	Kubernetes	Helm

Terraform	Ansible

Python	Bash	Shell Scripting

Prometheus	Grafana	Maven

Tech: Kubernetes, MicroK8s, Docker, Prometheus, Grafana, Node Exporter, kube-state-metrics, Python, YAML, Linux

• Deployed a complete Kubernetes benchmarking environment using MicroK8s.
• Implemented a Java-based benchmark application exposed via NodePort.
• Built a custom load generator to generate continuous traffic and simulate real workload.
• Configured Prometheus to scrape metrics from Node Exporter and kube-state-metrics.
• Visualised CPU, memory, and system performance in real time using Grafana dashboards.
• Automated load testing lifecycle with start, stop, and status shell scripts.
• Demonstrated clear performance impact under load and recovery after load termination.

📊 Key Outcomes: Real-time observability of application and node-level metrics, validated performance behaviour under sustained load, and a reproducible monitoring + benchmarking workflow.

Tech: AWS CodePipeline, EC2, S3, GitHub, Node.js

• End-to-end CI/CD pipeline for a Node.js application
• Automated builds, tests & deployments with minimal downtime
• Integrated version control, artifact storage, and environment promotion

Tech: IoT, Docker, MQTT/EMQX, RabbitMQ, Python, Machine Learning, TensorFlow Lite

• Built a full IoT data pipeline across Edge → Cloud with real-time PM2.5 processing
• Implemented data injector, preprocessing, ML prediction, and edge inference
• Used Docker microservices, EMQX, RabbitMQ for messaging, and Prophet/TensorFlow Lite for ML
• Visualized air-quality trends & predictions with Matplotlib
• Designed a scalable, modular architecture for real-time IoT analytics

• 🎓 MSc in Cloud Computing – Newcastle University, United Kingdom
• 🎓 B.Tech in Computer Science & Engineering – Dr. M.G.R. Educational & Research Institute, Chennai, India

• 🇬🇧 English (Fluent)
• 🇮🇳 Hindi, Tamil (Fluent)
• 🇵🇰 / 🇮🇳 Urdu (Mother Tongue)
• 🕋 Arabic (Reading)

• 📧 Email: khwajanawaz82@gmail.com
• 💼 GitHub: github.com/khwajanawaz
• 🔗 LinkedIn: Khwaja Nawaz

“Driven by purpose. Empowered by automation. Building secure, scalable cloud systems that actually ship to production.”