bernetes.io/docs/reference/scheduling/config) feature allows you to tune the algorithms and other settings of the kube-scheduler. You can easily enable or disable specific functionality (contained in plugins) in selected scheduling phases without having to rewrite the rest of the configuration. Furthermore, a single kube-scheduler instance can serve different configurations, called profiles. Pods can select the profile they want to be scheduled under via the `.spec.schedulerName` field.

###...

                    type: object
                  failureThreshold:
                    description: Minimum consecutive failures for the probe to be
                      considered failed after having succeeded.
                    format: int32
                    minimum: 0
                    type: integer
                  httpGet:

*   `tf.data`:

    *   Added support for alternative checkpointing protocol which makes it possible to checkpoint the state of the input pipeline without having to store the contents of internal buffers. The new functionality can be enabled through the `experimental_symbolic_checkpoint` option of `tf.data.Options()`.