{
  "id": 13399605,
  "title": "5 Mistakes That Make LLM Streaming Break on a Flaky Network",
  "url": "https://urgent.news/2026/10/10/5-mistakes-that-make-llm-streaming-break-on-a-flaky-network",
  "topic": "ai",
  "section": "AI",
  "published": "2026-10-10T11:51:38.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/michael_maurice/5-mistakes-that-make-llm-streaming-break-on-a-flaky-network-30a1"
  },
  "original_language": "en",
  "account": "The article titled \"5 Mistakes That Make LLM Streaming Break on a Flaky Network\" outlines common issues that arise when implementing live language model streaming over unreliable networks. Five key mistakes are identified and explained:\n\n1. Tying generation to the HTTP request - Generating responses should be separated from the HTTP request. Starting generation in a registry and returning a 202 response with a stream ID allows generation to continue even if the subscriber disconnects. This prevents wasted computation when the connection is lost and the model restarts.\n\n2. Lack of sequence IDs - Without unique sequence IDs, reconnecting causes the client to restart the entire generation process. Including an append-only stream log with sequence numbers enables clients to replay only the missed events after reconnecting.\n\n3. Naming error events - Using \"error\" as an event name can cause confusion with the default EventSource error handler. The article recommends using a distinct \"failed\" event name with a user-friendly error message and an errorId for debugging.\n\n4. Silent streams and lack of a stop button - Proxies and load balancers can leave SSE connections idle, leading to disconnections. Implementing heartbeats while work is in progress and providing a cancellation endpoint allows users to cancel the model generation and prevents unnecessary token usage.\n\n5. Incomplete API implementation - The \"quick stream\" implementation provided is not suitable for production. The article lists several additional features and best practices for a robust streaming API, including sequence IDs, cancellation, heartbeats, owner authentication, sticky sessions, and the use of HTTP/2 or HTTP/3.\n\nThe article emphasizes that flaky networks are not an edge case and recommends implementing a complete resumable streaming solution before considering a project complete. The author provides the complete source code and detailed implementation in a separate package available to subscribers.",
  "summary": "Your chat UI looks fine on the office Wi-Fi. Then someone joins from a train, the SSE connection drops mid-sentence, and either the answer restarts from scratch or the model keeps burning tokens while nobody is listening. Same feature, different network. I spent a stretch of time turning a \"works in demos\" stream into something that survives reconnects. The full working project (ASP.NET Core 10,…",
  "key_points": [
    "Tying generation to the HTTP request causes wasted computation when the connection is lost.",
    "Lack of sequence IDs prevents clients from reconnecting and resuming the generation process.",
    "Using \"error\" as an event name can confuse the default EventSource error handler."
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}