Foundation Level (Beginner-Friendly)
1. Serverless E-commerce Platform
Build a complete serverless e-commerce application using Azure Functions, Cosmos DB, Blob Storage, and API Gateway. This project demonstrates modern cloud-native architecture without server management overhead.
Key Components:
-
Frontend hosted on Azure Static Web Apps with React or Angular
-
User authentication using Azure Active Directory B2C
-
Product catalog stored in Azure Cosmos DB
-
Image storage using Azure Blob Storage with CDN
-
Order processing via Azure Functions triggered by HTTP requests
-
Payment integration using Azure Logic Apps
Skills Gained: Serverless architecture, NoSQL databases, API development, authentication systems
Expected Outcomes: Fully functional e-commerce platform, understanding of microservices architecture
2. AI-Powered Computer Vision Application
Develop an intelligent image analysis system using Azure Cognitive Services for object detection, text recognition, and sentiment analysis from images.
Key Features:
-
Upload images via Azure Blob Storage
-
Process images using Azure Computer Vision API for object detection
-
Extract text using Azure OCR services
-
Analyze sentiment from extracted text using Azure Text Analytics
-
Store results in Azure SQL Database
-
Create dashboard using Power BI for insights
Skills Gained: Computer vision, AI services integration, cloud storage, data analytics
Medium Level (Intermediate)
3. Multi-Tenant SaaS Application with Kubernetes
Build a scalable multi-tenant Software-as-a-Service platform using Azure Kubernetes Service (AKS) with automated deployment pipelines.
Key Components:
-
Containerized microservices architecture using Docker
-
Deploy to Azure Kubernetes Service (AKS) with auto-scaling
-
Implement tenant isolation using Kubernetes namespaces
-
Set up Azure DevOps CI/CD pipelines with Infrastructure as Code
-
Monitor performance using Azure Monitor and Application Insights
-
Implement security scanning and vulnerability assessment
Skills Gained: Kubernetes orchestration, microservices architecture, DevOps practices, security implementation
4. Real-Time IoT Data Pipeline
Create a comprehensive IoT data processing system that ingests, processes, and visualizes sensor data in real-time using Azure IoT services.
Key Features:
-
IoT device simulation using Azure IoT Device SDK
-
Data ingestion via Azure IoT Hub with message routing
-
Stream processing using Azure Stream Analytics
-
Hot path storage in Azure Cosmos DB for real-time queries
-
Cold path storage in Azure Data Lake for historical analysis
-
Real-time dashboards using Azure Time Series Insights
Skills Gained: IoT architecture, stream processing, real-time analytics, data lake management
Expert Level (Advanced)
5. Enterprise Data Lake with Advanced Analytics
Build a comprehensive enterprise data lake solution with machine learning capabilities and advanced analytics using Azure Synapse Analytics.
Key Components:
-
Data ingestion from multiple sources using Azure Data Factory
-
Raw data storage in Azure Data Lake Storage Gen2 with Delta format
-
Data processing using Azure Synapse Spark pools
-
Machine learning model training using Azure Machine Learning
-
Data visualization using Power BI with direct query
-
Implement data governance using Azure Purview
Skills Gained: Big data processing, machine learning operations, data governance, enterprise architecture
6. Multi-Cloud Disaster Recovery Solution
Implement a sophisticated disaster recovery system that spans multiple cloud providers using Azure Site Recovery and Terraform.
Key Features:
-
Infrastructure as Code using Terraform for multi-cloud deployment
-
Automated backup and replication using Azure Site Recovery
-
Cross-cloud networking with Azure Virtual WAN
-
Disaster recovery testing automation
-
Cost optimization strategies across providers
-
Security and compliance across multiple clouds
Skills Gained: Multi-cloud architecture, disaster recovery planning, infrastructure automation, cost management
