*   `Estimator.export_savedmodel()` now includes all valid serving signatures
    that can be constructed from the Serving Input Receiver and all available
    ExportOutputs. For instance, a classifier may provide regression- and
    prediction-flavored outputs, in addition to the classification-flavored one.
    Building signatures from these allows TF Serving to honor requests using the

* Add external link [Machine learning model serving in Python using FastAPI and Streamlit](https://davidefiocco.github.io/2020/06/27/streamlit-fastapi-ml-serving.html) to docs. PR [#1669](https://github.com/tiangolo/fastapi/pull/1669) by [@davidefiocco](https://github.com/davidefiocco).

- Kubeadm: add the deprecated flag --port=0 to kube-controller-manager and kube-scheduler manifests to disable insecure serving. Without this flag the components by default serve (e.g. /metrics) insecurely on the default node interface (controlled by --address). Users that wish to override this behavior and enable insecure serving can pass a custom --port=X via kubeadm's "extraArgs" mechanic for these components. ([#92720](https://github.com/kubernetes/kubernetes/pull/92720),...

:focus-visible, suppress the focus outline\n// on elements that programmatically receive focus but wouldn't normally show a visible\n// focus outline. In general, this would mean that the outline is only applied if the\n// interaction that led to the element receiving programmatic focus was a keyboard interaction,\n// or the browser has somehow determined that the user is primarily a keyboard user and/or\n// wants focus outlines to always be presented.\n//\n// See https://developer.mozilla.org/en-US/docs/Web/...