*
 * The task runner is also responsible for releasing held threads when the library is unloaded.
 * This is for the benefit of container environments that implement code unloading.
 *
 * Most applications should share a process-wide [TaskRunner] and use queues for per-client work.
 */
class TaskRunner(
  val backend: Backend,
  internal val logger: Logger = TaskRunner.logger,
) : Lockable {
  private var nextQueueName = 10000

            // Cached subject is copied and visible via getSubject()
            Subject copySubj = copy.getSubject();
            assertNotNull(copySubj);
            assertSame(cachedOrig, copySubj, "Clone should share the cached Subject reference");

            // Refreshing the original must not clear the clone's cached subject
            orig.refresh();
            // Clone should retain its cached Subject

   * The maximum number of requests for each host to execute concurrently. This limits requests by
   * the URL's host name. Note that concurrent requests to a single IP address may still exceed this
   * limit: multiple hostnames may share an IP address or be routed through the same HTTP proxy.
   *
   * If more than [maxRequestsPerHost] requests are in flight when this is invoked, those requests
   * will remain in flight.
   *

        for (NetworkInterfaceInfo info : response.getInterfaces()) {
            if (info.isUsableForChannel()) {
                remoteInterfaces.add(info);
            }
        }

        // Sort by score (best interfaces first)
        remoteInterfaces.sort((a, b) -> Integer.compare(b.getScore(), a.getScore()));

        log.debug("Discovered {} remote network interfaces", remoteInterfaces.size());
    }

public void testRdmaLargeFileTransfer() throws Exception {
    CIFSContext context = getTestContext();
    context.getConfig().setProperty("jcifs.smb.client.useRDMA", "true");
    
    SmbFile file = new SmbFile("smb://server/share/largefile.dat", context);
    
    // Measure RDMA transfer performance
    byte[] data = new byte[10485760];  // 10MB
    Arrays.fill(data, (byte)0x42);
    
    long start = System.currentTimeMillis();
    

        int totalWeight = 0;
        for (ChannelInfo channel : channels) {
            totalWeight += channel.getScore();
        }

        if (totalWeight == 0) {
            // All channels have zero score, pick randomly
            List<ChannelInfo> list = new ArrayList<>(channels);
            return list.get(ThreadLocalRandom.current().nextInt(list.size()));
        }

        // Weighted random selection

## Caveat { #caveat }

If you need to perform heavy background computation and you don't necessarily need it to be run by the same process (for example, you don't need to share memory, variables, etc), you might benefit from using other bigger tools like <a href="https://docs.celeryq.dev" class="external-link" target="_blank">Celery</a>.

* The ability to use kubectl scale jobs is deprecated. All other scale operations remain in place, but the ability to scale jobs will be removed in a future release.  ([#60139](https://github.com/kubernetes/kubernetes/pull/60139), [@soltysh](https://github.com/soltysh))

- Reload() of MinIO server arguments without fully restarting the process.

- Expanding 1 node at a time by automating the process of creating a new pool
  and decommissioning to provide a functionality that smaller deployments
  care about.

But first, let's check some small concepts.

## In a hurry? { #in-a-hurry }

If you don't care about any of these terms and you just need to add security with authentication based on username and password *right now*, skip to the next chapters.

## OAuth2 { #oauth2 }