} else {
          exchange.noRequestBody()
          if (!exchange.connection.isMultiplexed) {
            // If the "Expect: 100-continue" expectation wasn't met, prevent the HTTP/1 connection
            // from being reused. Otherwise we're still obligated to transmit the request body to
            // leave the connection in a consistent state.
            exchange.noNewExchangesOnConnection()
          }
        }
      } else {

			// with dead end because tcp-keepalive is not fired when there is data in the socket buffer.
			//    https://blog.cloudflare.com/when-tcp-sockets-refuse-to-die/
			// This is a sensitive configuration, it is better to set it to high values, > 60 secs since it can
			// affect clients reading data with a very slow pace  (disappropriate with socket buffer sizes)

    // from the plugin.xml inside a plugin.
    //
    // TODO This whole method could probably removed by injecting lifeCyclePluginAnalyzer straight into client site.
    // TODO But for some reason the whole plexus appcontext refuses to start when I try this.

    @Override
    public Set<Plugin> getPluginsBoundByDefaultToAllLifecycles(String packaging) {
        return lifeCyclePluginAnalyzer.getPluginsBoundByDefaultToAllLifecycles(packaging);
    }

package cmd

import "context"

const (
	configRRSParity      = "rrs_parity"
	configStandardParity = "standard_parity"
)

var (
	configRRSParityMD = NewGaugeMD(configRRSParity,
		"Reduced redundancy storage class parity")
	configStandardParityMD = NewGaugeMD(configStandardParity,
		"Standard storage class parity")
)

// loadClusterConfigMetrics - `MetricsLoaderFn` for cluster config

- Each pool expects each host in this pool has the same number of drives specified as any other host.
- Mixing `local-path` and `distributed-path` is not allowed, doing so would cause MinIO to refuse starting the server.
- Ellipses and bracket notation (e.g. `{1...10}`) are allowed.

			Optional:    true,
			Type:        "string",
		},
		config.HelpKV{
			Key:         ClassRRS,
			Description: `set the parity count for reduced redundancy storage class` + defaultHelpPostfix(ClassRRS),
			Optional:    true,
			Type:        "string",
		},
		config.HelpKV{
			Key:         Optimize,

		regUsersLoadStartTime := UTCNow()
		regUsersList := listedConfigItems[usersListKey]

		for {
			if len(regUsersList) < count {
				users, err := iamOS.loadUserConcurrent(ctx, regUser, regUsersList...)
				if err != nil {
					return err
				}
				for index := range regUsersList {
					if users[index].Credentials.AccessKey != "" {
						userName := path.Dir(regUsersList[index])

on the same machine by simply switching the value of `HERMETIC_PYTHON_VERSION`
between the runs. All the python-agnostic parts of the build cache from the
previous build will be preserved and reused for the subsequent builds.

### Specifying Python dependencies

During bazel build all TensorFlow's Python dependencies are pinned to their
specific versions. This is necessary to ensure reproducibility of the build.

The Gradle codebase has evolved over time and has a mixture of simple getter/setter methods, Provider API and things in between.  It can be hard to follow best practices because Gradle provided types are reused in unexpected ways and extended by third party plugins.

Given these constraints, we cannot always follow best practices.  This ADR proposes the way we should handle the use of Provider APIs in the gradle/gradle codebase.

 * {@link org.apache.maven.model.building.ModelBuilder} will add any relevant repositories to the model resolver. In
 * other words, the model resolver is stateful and should not be reused across multiple model building requests.
 *
 * @deprecated use {@code org.apache.maven.api.services.ModelBuilder} instead
 */
@Deprecated(since = "4.0.0")
public interface ModelResolver {

    /**