Real-Time Fleet Telemetry Streaming & Analytics: Implementing Hot & Cold Path Architecture on Azure

Why Should You Join?

In the course, we built the Real-Time Fleet Telemetry project locally using Apache Kafka and Apache Flink.

Now, we’ll take it to the cloud.

In real-world systems, streaming pipelines are deployed with proper Hot Path and Cold Path architecture — not just run locally.

In this session, we will focus on implementing the Azure-based architecture:

Hot Path → Real-time alerts and actions
Cold Path → Data lake storage, transformation, and reporting

This session is designed to help you understand how production-grade IoT and fleet analytics systems are deployed in real enterprise environments.

If you want to move from local implementation to cloud architecture, this session is for you.

Session Format

This session follows a different format:

🎥 Watch the Azure implementation recordings first:
👉 Recording Link

🕐 The live session will be a 1-hour doubt-clearing and architecture discussion session.

This is not a build-from-scratch session.

We will focus on:

• Your implementation doubts
• Azure service integration questions
• Deployment and configuration issues
• Architectural decisions and trade-offs

The discussion will be driven by your questions.

Pre-Requisites

• Complete the local Fleet Telemetry project
• Watch all Azure implementation recordings here: 👉 Recording Link
• Attempt to implement the architecture on your own
• Prepare your questions in advance

⚠️ Please come prepared. The live session will focus only on clearing doubts and architectural discussions.