429 Too Many Requests on PUT /api/v2/users — how to implement proper backoff in Kotlin

We’re running a Kotlin script to bulk-update user profiles via PUT /api/v2/users/{userId}. It’s hammering the API with concurrent requests using a coroutine flow. We hit the rate limit hard. The response body returns 429 Too Many Requests with a retry-after header, but our current retry logic is just sleeping for a fixed 5s. That’s inefficient and we’re still getting throttled because the retry-after value varies.

Here’s the snippet handling the retry:

val response = httpClient.put("https://api.mypurecloud.com/api/v2/users/$id") {
 contentType(ContentType.Application.Json)
 setBody(userJson)
}

if (response.status == HttpStatusCode.TooManyRequests) {
 val retryAfter = response.headers["Retry-After"]?.toInt() ?: 5
 delay(retryAfter * 1000L)
 // retry logic here
}

The issue is that Retry-After can be a date string or a delta-seconds integer. Parsing it correctly in Kotlin without exploding is annoying. Also, should I be using an exponential backoff strategy on top of the retry-after value, or is following the header strictly enough? The docs are vague on the exact behavior for bulk operations.

Any code examples for a solid retry handler that respects the Retry-After header in a multi-threaded Kotlin context? We need to avoid blocking all coroutines while waiting for the rate limit to reset.

Fixed sleeps are basically begging for a ban. You need exponential backoff with jitter, and you definitely should parse the Retry-After header if it’s present. The Genesys Cloud platform sends that header specifically to tell you when to come back. Ignoring it is asking for trouble.

Here is a quick Node.js example using axios since the logic translates easily to Kotlin coroutines. The key is checking response.headers['retry-after'] and converting that to seconds before sleeping.

async function fetchWithBackoff(url, config, retries = 3) {
 try {
 return await axios.put(url, config.data, config);
 } catch (error) {
 if (error.response?.status === 429) {
 const retryAfter = error.response.headers['retry-after'] || 5;
 const delay = Math.min(retryAfter * 1000, 10000); // cap at 10s
 console.log(`Rate limited. Waiting ${delay}ms...`);
 await new Promise(r => setTimeout(r, delay));
 return fetchWithBackoff(url, config, retries - 1);
 }
 throw error;
 }
}

In Kotlin, you’d use delay(retryAfter * 1000) inside your retry loop. Make sure you’re not hammering the endpoint in parallel without a semaphore. Coroutines make it easy to oversubscribe. Check the RateLimit-Remaining header too if you want to be fancy.