Building real-time data pipelines that keep logistics systems fast, scalable, and reliable In logistics, data doesn’t arrive in neat batches—it flows continuously. Vehicles send GPS updates every few seconds Temperature sensors report changes in cold storage Engines and fuel systems generate performance data Alerts and events happen in real time Trying to handle this with traditional systems (like simple APIs or batch jobs) quickly becomes messy. 👉 Systems slow down 👉 Data gets delayed 👉 Real-time decisions become impossible This is exactly where Apache Kafka shines. In this article, we’ll walk through how to use Kafka to stream sensor data in logistics applications—step by step, in a clear and practical way. 🚀 Why Kafka for Logistics? Let’s put things into perspective. Imagine a fleet of 2,000 vehicles: Each sends data every 5 seconds That’s 24,000 messages per minute Now add: Temperature sensors Fuel data Driver behavior 👉 You’re dealing with high-volume, real-time data streams.…