* fix: retry detach azure disk issue ([#78700](https://github.com/kubernetes/kubernetes/pull/78700), [@andyzhangx](https://github.com/andyzhangx))
    * try to only update vm if detach a non-existing disk when got <200, error> after detach disk operation

attempt either succeeded or failed respectively. On the destination side, a `X-Amz-Replication-Status` status of `REPLICA` indicates that the object was replicated successfully. Any replication failures are automatically re-attempted during a periodic disk scanner cycle.

To perform bi-directional replication, repeat the above process on the target site - this time setting the source bucket as the replication target. It is recommended that replication be run in a system with at least two CPU's...

	updatedRules := make(map[string]lifecycle.Rule, len(bucketLifecycle.Rules))
	for _, rule := range bucketLifecycle.Rules {
		updatedRules[rule.ID] = rule
	}

	// Get list of rules for the bucket from disk
	meta, err := globalBucketMetadataSys.GetConfigFromDisk(ctx, bucket)
	if err != nil {
		writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
		return
	}
	expiryRuleRemoved := false

			return
		}

		writeCustomErrorResponseJSON(ctx, w, errorCodes.ToAPIErr(ErrAdminConfigBadJSON), err.Error(), r.URL)
		return
	}

	// Update the actual server config on disk.
	if err = saveServerConfig(ctx, objectAPI, cfg); err != nil {
		writeErrorResponseJSON(ctx, w, toAdminAPIErr(ctx, err), r.URL)
		return
	}

	// Write to the config input KV to history.

should be used with caution when working with untrusted models.

### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the
TensorFlow process effectively executes arbitrary code.

	for k, v := range b.cachesRoot {
		tmp := make([]string, len(v))
		copy(tmp, v)
		dst2[k] = tmp
	}

	return dst, dst2
}

// deleteAll will delete all on disk data for ALL caches.
// Deletes are performed concurrently.
func (b *bucketMetacache) deleteAll() {
	ctx := context.Background()

	objAPI := newObjectLayerFn()
	if objAPI == nil {
		return
	}

)

// MRFReplicateEntry mrf entry to save to disk
type MRFReplicateEntry struct {
	Bucket     string `json:"bucket" msg:"b"`
	Object     string `json:"object" msg:"o"`
	versionID  string `json:"-"`
	RetryCount int    `json:"retryCount" msg:"rc"`
	sz         int64  `json:"-"`
}

// MRFReplicateEntries has the map of MRF entries to save to disk
type MRFReplicateEntries struct {

  exit 1
fi

# "TFCI_MACOS_BAZEL_TEST_DIR_PATH" specifies the directory that Bazel should use
# when running tests. Each test will be executed in a separate subdirectory
# inside this directory. TF Mac builds need ~150 GB of disk space to be able to
# run all the tests. Since TFCI Mac VMs execute Bazel test commands in a
# partition with insufficient storage, we specify the
# 'TFCI_MACOS_BAZEL_TEST_DIR_PATH' environment variable to point to a partition

    /** No mapping between account names and security IDs was done */
    int NT_STATUS_NONE_MAPPED = 0xC0000073;
    /** The security ID structure is invalid */
    int NT_STATUS_INVALID_SID = 0xC0000078;
    /** The disk is full */
    int NT_STATUS_DISK_FULL = 0xC000007f;
    /** Insufficient resources are available to complete the request */
    int NT_STATUS_INSUFFICIENT_RESOURCES = 0xC000009a;

// PersistToDisk persists in-memory resync metadata stats to disk at periodic intervals
func (s *replicationResyncer) PersistToDisk(ctx context.Context, objectAPI ObjectLayer) {
	resyncTimer := time.NewTimer(resyncTimeInterval)
	defer resyncTimer.Stop()

	// For each bucket name, store the last timestamp of the
	// successful save of replication status in the backend disks.
	lastResyncStatusSave := make(map[string]time.Time)