}
	return lockCopy
}

func (l *localLocker) Close() error {
	return nil
}

// IsOnline - local locker is always online.
func (l *localLocker) IsOnline() bool {
	return true
}

// IsLocal - local locker returns true.
func (l *localLocker) IsLocal() bool {
	return true
}

- Fixed issue on Windows when calculating cpu limits on nodes with more than 64 logical processors ([#114231](https://github.com/kubernetes/kubernetes/pull/114231), [@mweibel](https://github.com/mweibel))

  It specifies if the cluster internal traffic should be routed to all endpoints or node-local endpoints only.
  "Cluster" routes internal traffic to a Service to all endpoints.
  "Local" routes traffic to node-local endpoints only, and traffic is dropped if no node-local endpoints are ready.

Klaus Post <******@****.***> 1759093161 +0200

Klaus Post <******@****.***> 1759093161 +0200

Klaus Post <******@****.***> 1756435188 +0200

  passed a file which contains RBAC roles, rolebindings, clusterroles, or
  clusterrolebindings, this command computes covers and adds the missing rules.
  The logic required to properly apply RBAC permissions is more complicated
  than a JSON merge because you have to compute logical covers operations between
  rule sets. This means that we cannot use `kubectl apply` to update RBAC roles
  without risking breaking old clients, such as controllers.

        logger.debug(indent + artifact + " (not setting artifactScope to: " + ignoredScope + "; local artifactScope "
                + artifact.getScope() + " wins)");

        // TODO better way than static? this might hide messages in a reactor
        if (!ignoredArtifacts.contains(artifact)) {
            logger.warn("\n\tArtifact " + artifact + " retains local artifactScope '" + artifact.getScope()

> **NOTE:** Do **NOT** run `gradle build` on the local development environment,
> even if you have Gradle or Develocity build caching enabled for the project.
> The Gradle Build Tool repository is massive, and it will take ages to build on
> a local machine without necessary parallelization and caching.

        `data_service_ops.distribute`. Users can specify `"AUTO"`, `"ANY"`, or
        `"LOCAL"` (case insensitive). If `"AUTO"`, tf.data service runtime
        decides which workers to read from. If `"ANY"`, TF workers read from any
        tf.data service workers. If `"LOCAL"`, TF workers will only read from
        local in-processs tf.data service workers. `"AUTO"` works well for most