Dzone iconDzoneSep 4, 2026

Handling Large API Responses Without Freezing the Client: A Practical Architecture With Temporal, Kafka, and RAG

A large API response becomes a client problem long before it becomes a network problem. A browser can receive hundreds of megabytes and still become unresponsive while buffering bytes, parsing one enormous JSON document, retaining duplicate object graphs, and rendering too much state on the main thread.

Handling Large API Responses Without Freezing the Client: A Practical Architecture With Temporal, Kafka, and RAG

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Useful takeaways from this story.

A large API response becomes a client problem long before it becomes a network problem.

It is to stop treating the response as a synchronous document and start treating it as a durable, observable job whose data arrives in bounded pieces.

A browser can receive hundreds of megabytes and still become unresponsive while buffering bytes, parsing one enormous JSON document, retaining duplicate object graphs, and rendering too much state on the...

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The useful part

A large API response becomes a client problem long before it becomes a network problem. A browser can receive hundreds of megabytes and still become unresponsive while buffering bytes, parsing one enormous JSON document, retaining duplicate object graphs, and rendering too much state on the main thread. It is to stop treating the response as a synchronous document and start treating it as a durable, observable job whose data arrives in bounded pieces.

How it works

  • Browser streams support incremental consumption and backpressure, while background workers allow long-running processing to remain independent of user-interface scripts.

Details worth keeping

The reliable solution is not a larger timeout.

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