madmin.HealOpts{
						ScanMode: scanMode,
						Remove:   healDeleteDangling,
					})
				if err != nil {
					if isErrObjectNotFound(err) || isErrVersionNotFound(err) {
						// queueing happens across namespace, ignore
						// objects that are not found.
						return
					}
					result = healEntryFailure(0)
					bgSeq.countFailed(madmin.HealItemObject)

// user in the cluster, because they can be mounted by pods using the
// `clusterTrustBundle` projection.  All service accounts have read access to
// ClusterTrustBundles by default.  Users who only have namespace-level access
// to a cluster can read ClusterTrustBundles by impersonating a serviceaccount
// that they have access to.
//
// It can be optionally associated with a particular assigner, in which case it

	registerPeerRESTHandlers(router, commonGrid)

	// Register bootstrap REST router for distributed setups.
	registerBootstrapRESTHandlers(commonGrid)

	// Register distributed namespace lock routers.
	registerLockRESTHandlers(lockGrid)

	// Add lock grid to router
	router.Handle(grid.RouteLockPath, adminMiddleware(lockGrid.Handler(storageServerRequestValidate), noGZFlag, noObjLayerFlag))

└─────┴─────────────────────────────────┴──────────────────────────────────┴──────────┘
```

> NOTE: Canceled decommission will not make the pool active again, since we might have  potentially partial namespace on the other pools, to avoid this scenario be absolutely sure to make decommissioning a planned well thought activity. This is not to be run on a daily basis.

```

#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/platform/test.h"

using tensorflow::Status;
using tensorflow::string;
using tensorflow::TF_StatusPtr;

namespace tensorflow {
namespace {

// The tests are parameterized on:
// - a string representing the tracing implementation: "mlir" or "graphdef".
// - a boolean that when true enables TFRT as the execution engine.
class UnifiedCAPI

// TFE_TensorHandle's.
//
// TODO(ashankar): Figure out an alternative scheme that precludes the need for
// these API-boundary breaking methods.
namespace tensorflow {
class Tensor;
}  // namespace tensorflow

TFE_TensorHandle* TFE_NewTensorHandle(const tensorflow::Tensor& t,
                                      TF_Status* status);
#endif

                logger.debug("Lifecycle {}", lifecycle);
            }
            lifecyclesPrinted = true;
        }

        // If people are going to make their own lifecycles then we need to tell people how to namespace them correctly
        // so that they don't interfere with internally defined lifecycles.

        Map<String, Lifecycle> phaseToLifecycleMap = new HashMap<>();

        for (Lifecycle lifecycle : getLifeCycles()) {

#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/public/session.h"
#include "tensorflow/core/public/version.h"

// The implementation below is at the top level instead of the
// brain namespace because we are defining 'extern "C"' functions.
using tensorflow::AttrValueMap;
using tensorflow::DataType;
using tensorflow::ExtendSessionGraphHelper;
using tensorflow::FullTypeDef;
using tensorflow::Graph;

  xsi:schemaLocation="http://codehaus-plexus.github.io/MODELLO/2.0.0 https://codehaus-plexus.github.io/modello/xsd/modello-2.0.0.xsd"
  xml.namespace="http://maven.apache.org/LIFECYCLE/${version}"
  xml.schemaLocation="http://maven.apache.org/xsd/lifecycle-${version}.xsd">
  <id>lifecycle</id>
  <name>Lifecycle</name>
  <description>

  optional k8s.io.apimachinery.pkg.apis.meta.v1.GroupVersionKind responseKind = 2;

  // scope indicates the scope of a resource, either Cluster or Namespaced
  optional string scope = 3;

  // singularResource is the singular name of the resource.  This allows clients to handle plural and singular opaquely.