Tell about a challenging task from your work experience — API integration and solving timeout issues.
sobes.tech AI
Answer from AI
In one of the projects, there was a task to integrate with an external API that often returned timeouts due to high load and network instability. To solve this problem, I implemented several approaches:
-
Retry mechanism with exponential backoff. This allowed automatically retrying requests at increasing intervals, reducing load and giving the API time to recover.
-
Asynchronous request processing. Instead of blocking calls, I used
CompletableFuturefor parallel request sending, which improved system responsiveness. -
Timeout settings at the HTTP client level. I set reasonable connection and read timeout values to avoid waiting too long and to free resources.
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Response caching. For repeated requests, I stored results for some time to reduce the number of API calls.
Example code using HttpClient and retries:
HttpClient client = HttpClient.newHttpClient();
public CompletableFuture<HttpResponse<String>> sendWithRetry(HttpRequest request, int retries) {
return client.sendAsync(request, HttpResponse.BodyHandlers.ofString())
.handleAsync((response, ex) -> {
if (ex != null && retries > 0) {
try {
Thread.sleep((long) Math.pow(2, 3 - retries) * 1000); // exponential delay
} catch (InterruptedException e) {
Thread.currentThread().interrupt();
}
return sendWithRetry(request, retries - 1).join();
}
return response;
});
}
This approach significantly increased integration stability and reduced failures due to timeouts.