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Spring / Spring gRPC Interview Questions

How does backpressure work in gRPC streaming, and how would you handle a slow consumer?

gRPC relies on HTTP/2's built-in flow control, but on the server side you can also cooperate with it explicitly using a ServerCallStreamObserver. Before writing each message you can check isReady(); if the client hasn't caught up yet, you hold off on further onNext() calls rather than buffering unboundedly.

You can also register a callback via setOnReadyHandler(), which fires once the observer is ready to accept more data, letting you resume sending exactly when capacity frees up. This prevents a fast producer from overwhelming memory when paired with a slow consumer, which is the streaming equivalent of what reactive backpressure operators do for reactive streams.

What method on ServerCallStreamObserver lets you check if it's safe to send more data without buffering unboundedly?
What underlying protocol mechanism does gRPC streaming rely on for flow control?

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