you can start by increasing the gRPC server timeout and keep-alive settings in the Milvus configuration file. Adjusting parameters such as grpc.server_keepalive_time_ms and grpc.server_keepalive_timeout_ms ensures the connection remains active during prolonged insert operations. Additionally, reducing the batch size for data insertions can help alleviate server overload; while 10,000 records may work initially, lowering it to a smaller size, like 5,000, can prevent bottlenecks over time. Optimizing your insertion process with parallelization can further improve efficiency, but ensure each thread or process uses an independent connection to avoid overwhelming the server. Monitoring the Milvus server’s resource utilization is crucial; inadequate CPU, RAM, or network bandwidth can contribute to timeouts, so scaling up hardware resources or deploying Milvus in a distributed setup may be necessary. Implement robust error handling to catch and retry failed insertions with an exponential backoff strategy, which prevents immediate retries from overwhelming the server. Reviewing Milvus server logs and monitoring system metrics will help identify specific constraints or misconfigurations contributing to the issue, enabling a targeted resolution.