## Concepts

- All Buckets on MinIO are always in one of the following states: unversioned (the default) and all other existing deployments, versioning-enabled, or versioning-suspended.

			pools:  []poolDisksLayout{{layout: setArgs, cmdline: strings.Join(args, " ")}},
		}
		return
	}

	for _, arg := range args {
		if !ellipses.HasEllipses(arg) && len(args) > 1 {
			// TODO: support SNSD deployments to be decommissioned in future
			return fmt.Errorf("all args must have ellipses for pool expansion (%w) args: %s", errInvalidArgument, args)
		}
		setArgs, err = GetAllSets(setDriveCount, arg)
		if err != nil {

	Shutdown(context.Context) error
	NSScanner(ctx context.Context, updates chan<- DataUsageInfo, wantCycle uint32, scanMode madmin.HealScanMode) error
	BackendInfo() madmin.BackendInfo
	Legacy() bool // Only returns true for deployments which use CRCMOD as its object distribution algorithm.
	StorageInfo(ctx context.Context, metrics bool) StorageInfo
	LocalStorageInfo(ctx context.Context, metrics bool) StorageInfo

	// Bucket operations.

				start := time.Now()

				for result := range sys.hcClient.Alive(cctx, madmin.AliveOpts{}, eps...) {
					var lastOnline time.Time
					var offline time.Duration
					//	var deploymentID string
					sys.hMutex.RLock()
					prev, ok := sys.hc[result.Endpoint.Host]
					sys.hMutex.RUnlock()
					if ok {
						if prev.Online != result.Online || !result.Online {
							if !prev.lastHCAt.IsZero() {

				writeErrorResponseJSON(ctx, w, importErrorWithAPIErr(ctx, ErrAdminConfigBadJSON, err, allSvcAcctsFile, ""), r.URL)
				return
			}

			// Validations for LDAP enabled deployments.
			if globalIAMSys.LDAPConfig.Enabled() {
				skippedAccessKeys, err := globalIAMSys.NormalizeLDAPAccessKeypairs(ctx, serviceAcctReqs)
				skipped.ServiceAccounts = append(skipped.ServiceAccounts, skippedAccessKeys...)

## Major Features and Improvements

TensorFlow 2.0 focuses on **simplicity** and **ease of use**, featuring updates
like:

*   Easy model building with Keras and eager execution.
*   Robust model deployment in production on any platform.
*   Powerful experimentation for research.
*   API simplification by reducing duplication and removing deprecated
    endpoints.

For details on best practices with 2.0, see

	reqInfo := logger.GetReqInfo(ctx)
	var newReqInfo *logger.ReqInfo
	if reqInfo != nil {
		newReqInfo = logger.NewReqInfo(reqInfo.RemoteHost, reqInfo.UserAgent, reqInfo.DeploymentID, reqInfo.RequestID, reqInfo.API, bucket, object)
	} else {
		newReqInfo = logger.NewReqInfo("", "", globalDeploymentID(), "", "Heal", bucket, object)
	}
	healCtx := logger.SetReqInfo(GlobalContext, newReqInfo)

	reqID := w.Header().Get(xhttp.AmzRequestID)

	vars := mux.Vars(r)
	bucket := vars["bucket"]
	object := likelyUnescapeGeneric(vars["object"], url.PathUnescape)
	reqInfo := &logger.ReqInfo{
		DeploymentID: globalDeploymentID(),
		RequestID:    reqID,
		RemoteHost:   handlers.GetSourceIP(r),
		Host:         getHostName(r),
		UserAgent:    r.UserAgent(),
		API:          api,
		BucketName:   bucket,

			}
			if tt.expectedWriteQuorum != actualWriteQuorum {
				t.Errorf("Expected Write Quorum %d, got %d", tt.expectedWriteQuorum, actualWriteQuorum)
			}
		})
	}
}

// In some deployments, one object has data inlined in one disk and not inlined in other disks.
func TestGetObjectInlineNotInline(t *testing.T) {
	ctx, cancel := context.WithCancel(t.Context())
	defer cancel()

alpha, is no longer available. Kubernetes now only uses the _structured parameters_ model (also alpha) for allocating dynamic resources to Pods.

  if and only if classic DRA was enabled in a cluster, remove all workloads (pods, app deployments, etc. ) which depend on classic DRA and make sure that all PodSchedulingContext resources are gone before upgrading. PodSchedulingContext resources cannot be removed through the apiserver after an upgrade and workloads would not work properly. ...