*/
  @SuppressWarnings("nullness") // Unsafe, but we can't do much about it now.
  public final Optional<@NonNull E> firstMatch(Predicate<? super E> predicate) {
    return Iterables.<E>tryFind((Iterable<@NonNull E>) getDelegate(), predicate);
  }

  /**
   * Returns a fluent iterable that applies {@code function} to each element of this fluent
   * iterable.

   */
  @SuppressWarnings("nullness") // Unsafe, but we can't do much about it now.
  public final Optional<@NonNull E> firstMatch(Predicate<? super E> predicate) {
    return Iterables.<E>tryFind((Iterable<@NonNull E>) getDelegate(), predicate);
  }

  /**
   * Returns a fluent iterable that applies {@code function} to each element of this fluent
   * iterable.

* Ensure traffic between mesh workloads is securely encrypted with an Istio identity.
* Be lightweight enough to not limit adoption.
  * This puts a much tighter budget on CPU, memory, latency, and throughput requirements than traditional Istio sidecars.

Ztunnel was not designed to be a feature-rich data plane.

 *       does it offer a way to batch multiple events from a single producer together.
 *   <li>It doesn't support backpressure and other features needed for resilience.
 *   <li>It doesn't provide much control of threading.
 *   <li>It doesn't offer much monitoring.
 *   <li>It doesn't propagate exceptions, so apps don't have a way to react to them.
 *   <li>It doesn't interoperate well with RxJava, coroutines, and other more commonly used

Your server(s) is (are) a **resource**, you can consume or **utilize**, with your programs, the computation time on the CPUs, and the RAM memory available.

How much of the system resources do you want to be consuming/utilizing? It might be easy to think "not much", but in reality, you will probably want to consume **as much as possible without crashing**.

  All of these operations will produce their own unique errors in the absence of
  a coordinated offline strategy. In addition, efforts to unite these failing
  behaviors behind a consistent user interface is much, much more difficult if
  the system can't tell whether it has access to the network required by these
  operations.

  Offline mode really means anticipating a lack of network connectivity, and as

This way, containers consume **little resources**, an amount comparable to running the processes directly (a virtual machine would consume much more).

Containers also have their own **isolated** running processes (commonly just one process), file system, and network, simplifying deployment, security, development, etc.

## What is a Container Image

but that should be extremely rare.

GODEBUG settings added for compatibility will be maintained
for a minimum of two years (four Go releases).
Some, such as `http2client` and `http2server`,
will be maintained much longer, even indefinitely.

When possible, each GODEBUG setting has an associated
[runtime/metrics](/pkg/runtime/metrics/) counter
named `/godebug/non-default-behavior/<name>:events`

   * and use that list instead.
   */
  public List<Long> asList() {
    /*
     * Typically we cache this kind of thing, but much repeated use of this view is a performance
     * anti-pattern anyway. If we cache, then everyone pays a price in memory footprint even if
     * they never use this method.
     */
    return new AsList(this);
  }

      // timed out. e.g. if we weren't event able to grab the lock within the timeout we would never
      // even check the guard. I don't think we care too much about this use case but it could lead
      // to a confusing error message.
      throw new TimeoutException("Timed out waiting for " + this + " to reach the RUNNING state.");
    }
  }

  @Override