- A new set of alpha metrics are reported by the Kubernetes scheduler under the `/metrics/resources` endpoint that allow administrators to easily see the resource consumption (requests and limits for all resources on the pods) and compare it to actual pod usage or node capacity. ([#94866](https://github.com/kubernetes/kubernetes/pull/94866), [@smarterclayton](https://github.com/smarterclayton)) [SIG API Machinery, Instrumentation,...

        `True`,`tf.data` will now automatically add a `prefetch` transformation
        to datasets that end in synchronous transformations. This enables data
        generation to be overlapped with data consumption. This may cause a
        small increase in memory usage due to buffering. To enable this
        behavior, set `inject_prefetch=True` in
        `tf.data.experimental.OptimizationOptions`.

## Known Issues

* Improved **correctness** in corner cases.
* **Safer** types.
* Better **performance** and **less energy** consumption.
* Better **extensibility**.
* etc.

...all this while keeping the **same Python API**. In most of the cases, for simple models, you can simply upgrade the Pydantic version and get all the benefits. 🚀