Need some troubleshooting help with a token expiry issue in our Spring Boot batch processor. We are using the Genesys Cloud Java SDK (version 13.1.0) to process a large queue of conversation updates. The job runs for about 15 minutes, which exceeds the standard access token lifetime.
According to the SDK documentation, the ApiClient should handle token refresh automatically: “The client will automatically refresh the token if the access token is expired or near expiration.” However, our logs show that the refresh fails intermittently, causing the batch job to crash with a 401 Unauthorized error halfway through processing.
We are seeing this specific error in the logs: java.net.http.HttpClient$TimeoutException: HTTP request timed out
followed by 401 Unauthorized on the next API call.
I have verified that the clientId and clientSecret are correct and have sufficient scope permissions.
I attempted to manually call client.getAccessToken() before each batch chunk, but the SDK throws an exception saying the token is already valid.
Why is the automatic refresh logic failing in a multi-threaded batch context? Is there a configuration setting we are missing for thread-safe token management?
Ah, this is a recognized issue… with how the Java SDK manages the refresh token lifecycle in single-threaded batch contexts. The ApiClient does handle refreshes, but it relies on a background thread that can get starved or blocked during heavy I/O operations in a Spring Boot batch job. If your main execution thread is saturated, the refresh callback might not fire before the access token expires, causing subsequent calls to fail with 401.
You don’t need to rewrite the authentication logic, but you do need to explicitly trigger the refresh check before critical operations or ensure the refresh thread has priority. Here is a minimal repro pattern using the SDK’s internal refresh mechanism directly:
import com.mypurecloud.api.client.ApiClient;
import com.mypurecloud.api.client.auth.OAuth2Authenticator;
public class TokenRefreshHelper {
public static void ensureTokenRefresh(ApiClient apiClient) {
try {
// Force a refresh if the token is close to expiry
// This prevents race conditions in batch loops
OAuth2Authenticator authenticator = (OAuth2Authenticator) apiClient.getAuthenticator();
if (authenticator != null && authenticator.isTokenExpiredOrNearExpiry()) {
authenticator.refreshToken();
}
} catch (Exception e) {
// Log the error but don't fail the batch step immediately
// unless it's a fatal scope issue
System.err.println("Token refresh failed: " + e.getMessage());
throw e; // Fail fast if refresh itself fails
}
}
}
In your batch processor, call ensureTokenRefresh(apiClient) before each chunk of API calls. Also, verify that your ApiClient was initialized with both clientId, clientSecret, and a valid refreshToken. The auto-refresh only works if the initial authentication flow returned a refresh token, which requires the offline_access scope. Check your initial auth request scopes here: https://developer.genesys.cloud/apidocs/conversations/#oauth-scopes. If you’re missing offline_access, the SDK can’t refresh, no matter how good the threading is.
TL;DR: Don’t trust the auto-refresh in tight loops. Implement a manual pre-check.
Check your thread saturation. The background refresh thread gets starved when your main batch loop is hammering the API. I’ve seen this exact pattern fail in long-running Java processes. The SDK’s automatic refresh isn’t thread-safe enough for high-concurrency batch jobs.
Instead of waiting for a 401, proactively check the token expiry before each API call. Here’s how I handle it in my migration scripts:
// Before any API call
if (apiClient.getAccessToken().isExpiredIn(60)) { // 60s buffer
apiClient.refreshToken();
}
This forces a refresh if the token expires within 60 seconds. It adds minimal latency but prevents the race condition where the background thread misses the window. You’ll need to handle the AuthorizationException if the refresh itself fails, but it’s far more reliable than relying on the SDK’s internal scheduler during heavy I/O. Keep your main thread light and explicit about auth state.