* access. Access time is reset by all cache read and write operations (including {@code
   * Cache.asMap().get(Object)} and {@code Cache.asMap().put(K, V)}), but not by {@code
   * containsKey(Object)}, nor by operations on the collection-views of {@link Cache#asMap}}. So,
   * for example, iterating through {@code Cache.asMap().entrySet()} does not reset access time for
   * the entries you retrieve.
   *

   * access. Access time is reset by all cache read and write operations (including {@code
   * Cache.asMap().get(Object)} and {@code Cache.asMap().put(K, V)}), but not by {@code
   * containsKey(Object)}, nor by operations on the collection-views of {@link Cache#asMap}}. So,
   * for example, iterating through {@code Cache.asMap().entrySet()} does not reset access time for
   * the entries you retrieve.
   *

      for (int i = delegateIndex; i < delegates.size(); i++) {
        if (delegates.get(i).setFuture(inputFuture)) {
          recordCompletion();
          // this is technically unnecessary, but should speed up later accesses
          delegateIndex = i + 1;
          return;
        }
      }
      // If all the delegates were complete, no reason for the next listener to have to

   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,
   * and accesses that were performed on the map. The queue is drained on writes and when it exceeds
   * its capacity threshold.
   *
   * The Least Recently Used page replacement algorithm was chosen due to its simplicity, high hit

      for (int i = delegateIndex; i < delegates.size(); i++) {
        if (delegates.get(i).setFuture(inputFuture)) {
          recordCompletion();
          // this is technically unnecessary, but should speed up later accesses
          delegateIndex = i + 1;
          return;
        }
      }
      // If all the delegates were complete, no reason for the next listener to have to

   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,
   * and accesses that were performed on the map. The queue is drained on writes and when it exceeds
   * its capacity threshold.
   *
   * The Least Recently Used page replacement algorithm was chosen due to its simplicity, high hit

	// remove the root user. Also you cannot delete yourself.
	if accessKey == globalActiveCred.AccessKey || accessKey == cred.AccessKey {
		writeErrorResponseJSON(ctx, w, toAdminAPIErr(ctx, errIAMActionNotAllowed), r.URL)
		return
	}

	if err := globalIAMSys.DeleteUser(ctx, accessKey, true); err != nil {
		writeErrorResponseJSON(ctx, w, toAdminAPIErr(ctx, err), r.URL)
		return
	}

	}

	// confirm that the user is able to access the bucket
	uClient := s.getUserClient(c, accessKey, secretKey, "")
	versions := c.mustUploadReturnVersions(ctx, uClient, bucket)
	c.mustNotDelete(ctx, uClient, bucket, versions[0])

	assumeRole := cr.STSAssumeRole{
		Client:      s.TestSuiteCommon.client,
		STSEndpoint: s.endPoint,
		Options: cr.STSAssumeRoleOptions{
			AccessKey: accessKey,
			SecretKey: secretKey,

					_ = store.deleteUserIdentity(ctx, u.AccessKey, svcUser)
					delete(cache.iamUsersMap, u.AccessKey)
				case u.IsTemp():
					_ = store.deleteUserIdentity(ctx, u.AccessKey, stsUser)
					delete(cache.iamSTSAccountsMap, u.AccessKey)
					delete(cache.iamUsersMap, u.AccessKey)
				}
				if store.group != nil {
					store.group.Forget(u.AccessKey)
				}
			}
		}
	}

	switch {
	case usersPrefix:
		accessKey := path.Dir(strings.TrimPrefix(event.keyPath, iamConfigUsersPrefix))
		err = sys.store.UserNotificationHandler(ctx, accessKey, regUser)
	case stsPrefix:
		accessKey := path.Dir(strings.TrimPrefix(event.keyPath, iamConfigSTSPrefix))
		err = sys.store.UserNotificationHandler(ctx, accessKey, stsUser)
	case svcPrefix: