This way, in case there was a breaking change for your code in one of the releases, you can still benefit from the previous upgrades. ✨

### Breaking Changes - Upgrade

* ⬆️ Upgrade Starlette to 0.16.0. PR [#4016](https://github.com/tiangolo/fastapi/pull/4016) by [@tiangolo](https://github.com/tiangolo).

Also upgrades the ranges of optional dependencies:

* `"jinja2 >=2.11.2,<4.0.0"`
* `"itsdangerous >=1.1.0,<3.0.0"`

- Kubeadm: during 'upgrade apply', if the kube-proxy ConfigMap is missing, assume that kube-proxy should not be upgraded. Same applies to a missing kube-dns/coredns ConfigMap for the DNS server addon. Note that this is a temporary workaround until 'upgrade apply' supports phases. Once phases are supported the kube-proxy/dns upgrade should be skipped manually. ([#89593](https://github.com/kubernetes/kubernetes/pull/89593), ...

    * Discussion for these changes can be found on SIG Build's [TensorFlow Community Forum thread](https://discuss.tensorflow.org/t/tensorflow-linux-wheels-are-being-upgraded-to-manylinux2014/8339)
*   The `tf.keras.mixed_precision.experimental` API has been removed. The non-experimental symbols under `tf.keras.mixed_precision` have been available since TensorFlow 2.4 and should be used instead.

     */
    String getOnlineHelpNameBackup();

    /**
     * Get the value for the key 'online.help.name.upgrade'. <br>
     * The value is, e.g. upgrade <br>
     * comment: Online help key for upgrade.
     * @return The value of found property. (NotNull: if not found, exception but basically no way)
     */
    String getOnlineHelpNameUpgrade();

    /**