We’re hitting a wall with the Genesys Cloud Java SDK in our distributed tracing pipeline. We have a high-throughput service that fires off Data Action calls to enrich call metadata before injecting the trace context into the conversation. The goal is to keep the latency under 50ms per call.
The problem is that after about 200 concurrent requests, the SDK starts throwing 503 Service Unavailable errors. We’re using the standard PlatformClient initialization, but we suspect the underlying HTTP client isn’t handling connection pooling correctly for this burst pattern. The stack trace points to java.net.SocketException: Connection reset, which usually means the pool is drained or the idle connections are being killed by the load balancer before the SDK can reuse them.
Here’s how we’re initializing the client in our Spring Boot service:
@Configuration
public class GenesysConfig {
@Bean
public PlatformClient platformClient() throws Exception {
ApiClient apiClient = ApiClient.defaultApiClient();
// We thought this would help, but it seems to be ignored or overridden
apiClient.setHttpClient(HttpClient.newBuilder()
.connectionPoolSize(50)
.build());
return PlatformClient.create(apiClient);
}
}
We’ve tried tweaking the connectionPoolSize, but the Java SDK docs are sparse on how to properly configure the underlying OkHttpClient for thread-safe, high-concurrency scenarios. Is there a way to inject a custom OkHttpClient with a tuned ConnectionPool directly into the PlatformClient? Or are we missing a configuration flag in the ApiClient builder?
We’re running this in Asia/Manila, so the latency to the US East region is already a factor. We can’t afford to wait for new TCP handshakes on every request. The OTel spans are showing the time spent in the SDK’s HTTP layer is skyrocketing once the pool hits ~40 active connections.
Any ideas on how to force the SDK to use a persistent, pooled connection strategy that survives rapid burst traffic?