// When: Encoding input
            message.encode_in(mockNdrBuffer);

            // Then: Should encode null referent and access mask
            verify(mockNdrBuffer).enc_ndr_referent(null, 1);
            verify(mockNdrBuffer, never()).enc_ndr_string(anyString());
            verify(mockNdrBuffer).enc_ndr_long(123);
        }

        @Test

## Running on Startup { #running-on-startup }

In most cases, when you create a web API, you want it to be **always running**, uninterrupted, so that your clients can always access it. This is of course, unless you have a specific reason why you want it to run only in certain situations, but most of the time you want it constantly running and **available**.

### In a Remote Server { #in-a-remote-server }

type repeatedByte struct {
	off int64
	b   byte
	n   int64
}

// rleBuffer is a run-length-encoded byte buffer.
// It's an io.Writer (like a bytes.Buffer) and also an io.ReaderAt,
// allowing random-access reads.
type rleBuffer struct {
	buf []repeatedByte
}

func (r *rleBuffer) Size() int64 {
	if len(r.buf) == 0 {
		return 0
	}
	last := &r.buf[len(r.buf)-1]
	return last.off + last.n
}

            } catch (RuntimeException e) {
                // Accept runtime exceptions that might be thrown due to closed state
                assertTrue(e.getMessage() != null, "Exception should have a message: " + e.getClass().getSimpleName());
            }
        }

        @Test
        @DisplayName("Should handle concurrent access during key wiping")
        void testConcurrentAccessDuringWipe() throws Exception {

			name:   "create key as user with no resources specified want success",
			method: http.MethodPost,
			path:   kmsKeyCreatePath,
			query:  map[string]string{"key-id": "new-test-key"},
			asRoot: false,

			policy: `{"Effect": "Allow",
				"Action": ["kms:CreateKey"] }`,

			wantStatusCode: http.StatusOK,
		},
		{
			name:   "create key as user set policy to allow want success",
			method: http.MethodPost,

import org.junit.jupiter.api.AfterEach
import org.junit.jupiter.api.Assumptions.assumeFalse
import org.junit.jupiter.api.BeforeEach
import org.junit.jupiter.api.Disabled
import org.junit.jupiter.api.Test

/**
 * Access every type, function, and property from Kotlin to defend against unexpected regressions in
 * modern 4.0.x kotlin source-compatibility.
 */
@Suppress(
  "ASSIGNED_BUT_NEVER_ACCESSED_VARIABLE",
  "UNUSED_ANONYMOUS_PARAMETER",

    }
  }

  /**
   * Returns an iterator across all key-value map entries, used by {@code entries().iterator()} and
   * {@code values().iterator()}. The default behavior, which traverses the values for one key, the
   * values for a second key, and so on, suffices for most {@code AbstractMapBasedMultimap}
   * implementations.
   *
   * @return an iterator across map entries
   */
  @Override

    *   Pod Security Policy can now manage access to specific FlexVolume drivers.([#53179](https://github.com/kubernetes/kubernetes/pull/53179),[ @wanghaoran1988](https://github.com/wanghaoran1988))
    *   To prevent unauthorized access to CHAP Secrets, you can now set the secretNamespace storage class parameters for the following volume types:

		//     spark.sparkContext.hadoopConfiguration.set("fs.s3a.endpoint", "http://minio-lb:9000")
		//     spark.sparkContext.hadoopConfiguration.set("fs.s3a.path.style.access", "true")
		//     spark.sparkContext.hadoopConfiguration.set("fs.s3a.access.key", "minioadmin")
		//     spark.sparkContext.hadoopConfiguration.set("fs.s3a.secret.key", "minioadmin")
		//
		//     val df = spark.read.json("s3a://testbucket/s3.json")
		//

Federated Jobs that are automatically deployed to multiple clusters
are now supported. Cluster selection and weighting determine how Job
parallelism and completions are spread across clusters. Federated Job
status reflects the aggregate status across all underlying cluster
jobs.

#### [alpha] Federated Horizontal Pod Autoscaling (HPA)

Federated HPAs are similar to the traditional Kubernetes HPAs, except