}
    
    return null;  // No witness service found
}

private boolean isWitnessServiceAvailable(InetAddress address) {
    try (Socket socket = new Socket()) {
        socket.connect(new InetSocketAddress(address, 135), 5000);  // RPC endpoint
        return true;
    } catch (IOException e) {
        return false;
    }
}

## Prerequisites

Configure and install casdoor server by following [Casdoor Server Installation](https://casdoor.org/docs/basic/server-installation).
For a quick installation, docker-compose reference configs are also available on the [Casdoor Try with Docker](https://casdoor.org/docs/basic/try-with-docker).

### Configure Casdoor

- Go to Applications
  - Create or use an existing Casdoor application
  - Edit the application

import org.opensearch.search.aggregations.bucket.filter.FilterAggregationBuilder;
import org.opensearch.search.aggregations.bucket.global.GlobalAggregationBuilder;
import org.opensearch.search.aggregations.bucket.histogram.HistogramAggregationBuilder;
import org.opensearch.search.aggregations.bucket.missing.MissingAggregationBuilder;
import org.opensearch.search.aggregations.bucket.range.IpRangeAggregationBuilder;

# The RBE machine itself has older kernel mode driver, and it requires
# nvidia driver to be installed.
nvidia-driver-580-open
# TODO(b/445248346): The Docker image shouldn't have cuda-compat installed.
# However, hermetic CUDA forward-compatibility mode is still missing some
# libraries.

 * @param largeElementSplitFunction the function used to further split the large element into smaller pieces
 * @param smallElementAggregateFunction the function used to aggregate tiny elements into a large bucket
 * @param expectedBucketNumber the return value's size should be expectedBucketNumber
 */
fun <T, R> splitIntoBuckets(
    list: LinkedList<T>,
    toIntFunction: (T) -> Int,

import org.opensearch.search.aggregations.bucket.filter.FilterAggregationBuilder;
import org.opensearch.search.aggregations.bucket.global.GlobalAggregationBuilder;
import org.opensearch.search.aggregations.bucket.histogram.HistogramAggregationBuilder;
import org.opensearch.search.aggregations.bucket.missing.MissingAggregationBuilder;
import org.opensearch.search.aggregations.bucket.range.IpRangeAggregationBuilder;

import org.opensearch.search.aggregations.bucket.filter.FilterAggregationBuilder;
import org.opensearch.search.aggregations.bucket.global.GlobalAggregationBuilder;
import org.opensearch.search.aggregations.bucket.histogram.HistogramAggregationBuilder;
import org.opensearch.search.aggregations.bucket.missing.MissingAggregationBuilder;
import org.opensearch.search.aggregations.bucket.range.IpRangeAggregationBuilder;

   */
  open fun dnsEnd(
    call: Call,
    domainName: String,
    inetAddressList: List<@JvmSuppressWildcards InetAddress>,
  ) {
  }

  /**
   * Invoked just prior to initiating a socket connection.
   *
   * This method will be invoked if no existing connection in the [ConnectionPool] can be reused.
   *
   * This can be invoked more than 1 time for a single [Call]. For example, if the response to the

							endpoints[i].Hostname()), endpoints[i].Hostname(), logger.ErrorKind)
					}

					continue
				}

				// return err if not Docker or Kubernetes
				// We use IsDocker() to check for Docker environment
				// We use IsKubernetes() to check for Kubernetes environment
				isLocal, err := isLocalHost(endpoints[i].Hostname(),
					endpoints[i].Port(),
					globalMinioPort,
				)

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML