How I Designed a Real-Time Dashboard Using Kafka, Socket.IO, and a BFF

The architecture of Flux, as described, highlights several key principles that make it resilient, user-friendly, and efficient. Here are the main takeaways:

1. Separation of Data Types: The system distinguishes between snapshot data (data that should be shown immediately on reconnect) and stream data (live updates). This distinction allows for more intentional handling of reconnections and ensures a smoother user experience.

2. Optional Cache with Resilience: Using an optional cache like Valkey (an open-source Redis fork) accelerates the system by providing fast hydration upon reconnects, but it's designed to work without cache if necessary. This approach avoids making the system fragile due to reliance on non-essential components.

3. Selective Fan-Out: Leveraging Socket.IO rooms for selective event delivery ensures that only relevant data is sent to specific clients, optimizing bandwidth and reducing unnecessary frontend filtering.

4. Hydration Strategy: Upon reconnects, the system prioritizes providing immediate snapshot data to ensure a seamless user experience without waiting for live streams to naturally update again.

5. Frontend Architecture Flexibility: While aiming for clean separation of concerns (hooks handle subscriptions and components render), there's room for practical adjustments when necessary. For example, using

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