Why Not Native Bidirectionality?
3. Exploring Design Choices and Trade-offs
You might be wondering, "If it's possible to simulate bidirectionality, why doesn't Kafka just support it natively?" The answer lies in its core design principles: scalability, fault tolerance, and throughput. Adding true bidirectionality would significantly complicate the system and potentially compromise these key advantages. Think of it as building a highway. Adding too many interchanges in both direction in a single point will cause traffic jam or accident.
Kafka's design prioritizes a decoupled architecture. Producers and consumers operate independently, without direct dependencies on each other. This allows for massive scalability and resilience. If a consumer fails, it doesn't impact the producers. If a producer is overloaded, it doesn't bring down the consumers. Adding bidirectional communication would introduce tighter coupling and make the system more fragile. That's a big no-no when dealing with massive data streams.
Furthermore, managing request-response correlation in a truly distributed and fault-tolerant manner is a complex problem. Imagine a request getting lost or a response being delayed. How would you handle timeouts, retries, and duplicate messages? Kafka's creators opted for a simpler, more robust design that avoids these complexities. Remember the KISS (Keep It Simple, Stupid) principle? It applies here.
So, while you might yearn for the simplicity of a direct back-and-forth, the trade-offs in terms of scalability and reliability make a native bidirectional approach less desirable for Kafka's core purpose.
