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Graph/retry-connection-stall

AntiPattern

Retry and Connection Stall

retry-connection-stall

Network clients stall or hang while retrying or waiting for responses because errors block progress callbacks, sockets are not reused, or listeners stop while servers hold connections open, inflating fallback/timeout rates and breaking timely UX or ingestion.

Node Details

Public graph metadata

Updated7/6/2026

Connections

30 linked nodes

MATCHESSolution

Prevent or debounce user interactions until hydration completes — before hydration completes. Tension: especially in slow networks.

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Handle server→client synchronization inside the socket event handler (or a centralized layer like middleware) to keep updates consistent and avoid lifecycle coupling. Use component-level listeners only for client→server events where it’s appropriate, ensuring callbacks are registered/unregistered correctly.

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handle a scenario when the code is fine but backend went offline — prefetching data with usePrefetchQuery. Tension: prefetch works.

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maybe you can swap your post to axios, because it has a timeout property — if you only want to do this once. Tension: some requests take too long to download content (about a minute). Outcome: can you in anyway batch your requests, so you are sending more requests in order to receive smaller responses?

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post-start failures. Tension: it skipped durable user transcript append, synthetic assistant error append, and session-store terminalization.

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Disable retry — If the issue persists. Tension: it could be because the sdk is getting an error and appear to be hanging while it's retrying. Outcome: You could try disabling the retry and check if there is an error.

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And HTTP Client errors (if you're using `HttpClient` or `HttpClientFactory`) — On ASP.NET Core. Tension: you just need to opt-in. Outcome: options.CaptureFailedRequests = true;.

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try reducing Sentry's http_connect_timeout and http_timeout options — If you do need it, and slow connections happen randomly. Tension: slow connections happen randomly. Outcome: Sentry\init([ 'http_connect_timeout' => 2, // The default is two seconds. 'http_timeout' => 5 // Reduce these values and test if Sentry still sends events. ]);.

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Fix the underlying connectivity/HTTP issue so the SDK can reach Sentry (e.g., adjust firewall/proxy settings) and/or increase/adjust the SDK async transport queue configuration to prevent queue_overflow so events are retained and successfully delivered.

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Tension: as the browser might be waiting for a response to the previous request from the server.

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Ensure the server yields to the asyncio event loop while processing (e.g., add an `await asyncio.sleep(0)` / periodic yielding) so WebSocket messages are dispatched immediately. Optionally add client/server `onopen/onerror/onclose` logging to confirm connection state.

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any time you have an I/O bound process with lots of idle time — waiting for user input, waiting for a TLS handshake. Tension: wrapping it in an async task can let other code run.

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Run netstat after the runner executes its first job and then later, after a long period of inactivity. — Windows machine. Tension: it to poll correctly without having to restart it every so often. Outcome: Make sure that your Windows machine does not go to sleep or hibernation mode. Also make sure that your network supports long running connections.

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adding Celery to your project — handling Stripe webhooks. Tension: This would allow for the processing of the webhook event payload to fail once (or more). Outcome: retry the operation.

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making sure you pace your requests to stay below those limits — API rate limits. Tension: allowing room for your normal operations, too. Outcome: handle any 429 responses gracefully to retry.

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keep a singleton client and configure a connection pool using `https.Agent` — Instead of creating a new S3Client on every request. Tension: prevents socket reuse. Outcome: Keeps sockets alive for reuse under high concurrency.

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bound it with a "progress ceiling" — a process emitting bytes but making NO semantic progress. Tension: a process emitting bytes but making NO semantic progress (livelock) would be shielded forever. Outcome: re-arms recovery after a long no-progress window even while bytes flow.

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implementing this retry behavior all over the place — axiosInstance.js. Tension: handle the retry logic. Outcome: you could try using a response interceptor to abstract and handle the retry logic.

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could re-call just the endpoint. Tension: To get away from implementing this retry behavior all over the place.

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Increasing the timeout, pool size and pooling in the connection string helped in my case. — I faced the same issue where the first connection attempt or a connection after a longer period would immediately time out. Outcome: I added these parameters: `Timeout=60;Command Timeout=60;Pooling=true;MinPoolSize=1;MaxPoolSize=200`.

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Use virtual threads for blocking DB/IO work to improve scalability under the same small pool, or switch to a reactive database driver/event-loop model to avoid blocking carrier threads; adjust concurrency/throttling accordingly (semaphore/backpressure) rather than assuming the current JDBC + thread pool design remains optimal.

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You can disable infinite retries using: — spring.kafka.producer.retries=1. Outcome: Handle the Send Failure via `Callback`.

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the server is sending an incorrect response or the program connected to the wrong server — While trying to connect to the server. Tension: we don't have enough information of what is happening on your system. Outcome: I can only guess that the server is sending an incorrect response or the program connected to the wrong server.

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I am seeing an increase in latencies in requests that do succeed — I have a logic of the sort :. Tension: none of them enforce a timeout on the total duration of the request. Outcome: Then properly close the connection in a finally / try-resource block.

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decorate a connection pool with a priority queue to avoid overloading the connection pool — When the connection pool usage goes above some critical level. Tension: start throttling requests and maybe even drop low priority requests from the queue all together.

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If you start the server and wait several minutes before visiting any pages — does it still take several minutes for that first page? Tension: long startup in general or something request specific. Outcome: Figuring out if it is a long startup in general or something request specific could be a good spot to start.

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Fixed 30s retry on 429 keeps hammering. — when clearly rate-limited. Tension: keeps hammering. Outcome: Exponential backoff + hard rejection during cooldown.

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Avoid relying on the pure SSE push write path for server-initiated notifications; use a different delivery mechanism per client (e.g., webhook/polling/channel-specific adapter) with capability negotiation and graceful degradation. Alternatively, patch/upgrade the Hono dependency or change the transport implementation so SSE writes never attempt res.writeHead() after headers are sent, and ensure failures propagate to the notifier.

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Don't build per-client adapters. — client capabilities change with updates. Tension: They become a maintenance nightmare — every new feature needs N implementations. Outcome: one delivery function that degrades.

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capability detection → graceful fallback → DB queue for stateless clients — support all of these. Tension: There's no single mechanism that works everywhere. Outcome: capability negotiation is the only viable pattern.

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