server.enqueue(MockResponse(body = "A"))
    client =
      client.newBuilder()
        .readTimeout(Duration.ofSeconds(1))
        .build()

    // Make a call expecting a timeout reading the response headers.
    val call1 = client.newCall(Request(server.url("/")))
    assertFailsWith<SocketTimeoutException> {
      call1.execute()
    }.also { expected ->

    // way for it to return a false negative would be for the target value to jump around in the map
    // such that none of the subsequent iterations observed it, despite the fact that at every point
    // in time it was present somewhere int the map. This becomes increasingly unlikely as
    // CONTAINS_VALUE_RETRIES increases, though without locking it is theoretically possible.

    // way for it to return a false negative would be for the target value to jump around in the map
    // such that none of the subsequent iterations observed it, despite the fact that at every point
    // in time it was present somewhere int the map. This becomes increasingly unlikely as
    // CONTAINS_VALUE_RETRIES increases, though without locking it is theoretically possible.

    setUp(parameters.first, parameters.second)
    cache.maxSize = 8
    taskFaker.runNextTask()
    set("a", "aa", "aa")
    set("b", "bb", "bbb")

    // Cause the cache trim to fail on the second value leaving a partial snapshot.
    filesystem.setFaultyDelete(cacheDir / "a.1", true)
    taskFaker.runNextTask()

    // Confirm the partial snapshot is not returned.
    assertThat(cache["a"]).isNull()

	if !opts.NoAuditLog {
		auditObjectErasureSet(ctx, "GetObjectInfo", object, &er)
	}

	if !opts.NoLock {
		// Lock the object before reading.
		lk := er.NewNSLock(bucket, object)
		lkctx, err := lk.GetRLock(ctx, globalOperationTimeout)
		if err != nil {
			return ObjectInfo{}, err
		}
		ctx = lkctx.Context()
		defer lk.RUnlock(lkctx)
	}

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#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/platform/casts.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/platform/protobuf.h"
#include "tensorflow/core/platform/strcat.h"
#include "tensorflow/core/platform/test.h"

using exec plugins, rather than storing credentials on the node's filesystem.

### Contextual Logging in Alpha

Kubernetes 1.24 has introduced [contextual logging](https://github.com/kubernetes/enhancements/issues/3077)
that enables the caller of a function to control all aspects of logging (output formatting, verbosity, additional values and names).

### Avoiding Collisions in IP allocation to Services

    * Remove metadata agent config maps in favor of command line flags.
    * Update the metadata agent's liveness probe to a new /healthz handler.
    * Logging Agent Improvements
    * Bump logging agent version to 0.2-1.5.33-1-k8s-1.
    * Appropriately set log severity for k8s_container.
    * Fix detect exceptions plugin to analyze message field instead of log field.

* Fixed a bug in the apiserver storage that could cause just-added finalizers to be ignored on an immediately following delete request, leading to premature deletion. ([#77619](https://github.com/kubernetes/kubernetes/pull/77619), [@caesarxuchao](https://github.com/caesarxuchao))