Forum Discussion
Built a Real-Time Azure AI + AKS + DevOps Project – Looking for Feedback
Hi everyone,
I recently completed a real-time project using Microsoft Azure services to build a cloud-native healthcare monitoring system. The key services used include:
- Azure AI (Cognitive Services, OpenAI)
- Azure Kubernetes Service (AKS)
- Azure DevOps and GitHub Actions
- Azure Monitor, Key Vault, API Management, and others
The project focuses on real-time health risk prediction using simulated sensor data. It's built with containerized microservices, infrastructure as code, and end-to-end automation.
GitHub link (with source code and documentation): https://github.com/kavin3021/AI-Driven-Predictive-Healthcare-Ecosystem
I would really appreciate your feedback or suggestions to improve the solution.
Thank you!
2 Replies
Below are some suggestions:
Area
Suggestion
Observability
Consider integrating Azure Application Insights for deeper telemetry and distributed tracing across services.
Model Lifecycle
Add versioning and retraining workflows for your AI models using ML Ops (e.g., Azure Machine Learning pipelines).
Data Simulation
Include a script or service that mimics realistic sensor data patterns (e.g., spikes, anomalies) to better test prediction accuracy.
Documentation
Expand your README with architecture diagrams, setup instructions, and a flowchart of how data moves through the system.
Security Hardening
Add role-based access control (RBAC) and network isolation (e.g., private AKS cluster with Azure Private Link).
Thank you so much for your thoughtful suggestions! These are very actionable and I am already planning the next iteration to include Application Insights, RBAC, and MLOps features. I will share the updated version soon and would love your thoughts again. Really appreciate your time and feedback!
