What approaches are there to handle unstable integration that may not respond from a minute to a day?
sobes.tech AI
Answer from AI
To work with unstable integration that may respond with a delay from a minute to a day, several approaches are used:
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Asynchronous processing and message queues: Instead of synchronous calls, use a queue (e.g., Kafka, RabbitMQ) to send requests and process responses as they arrive.
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Retry with exponential backoff: On errors or timeouts, retry requests with increasing delays to avoid overwhelming the integration.
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Caching and idempotency: Store request results and ensure idempotency of operations to prevent duplication on retries.
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Monitoring and alerts: Set up monitoring for delays and errors to respond promptly to issues.
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Splitting requests into smaller parts: If possible, break large requests into smaller ones to reduce load and speed up processing.
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Using callback/webhook: If supported by the integration, use callback notifications instead of polling continuously.
Example of using a queue with asynchronous processing in Java with CompletableFuture:
CompletableFuture.supplyAsync(() -> callExternalService())
.thenAccept(response -> processResponse(response))
.exceptionally(ex -> { logError(ex); return null; });
Thus, the system is non-blocking and can process responses as they arrive.