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### Azure

SIG Azure worked on improvements in the cloud provider, including significant work on the Azure Load Balancer implementation.

### Cluster Lifecycle

* HTTPS
* Running on startup
* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

## HTTPS { #https }

If we focus just on the **container image** for a FastAPI application (and later the running **container**), HTTPS normally would be handled **externally** by another tool.

### SIG CLI

SIG CLI's main focus this release was on refactoring `kubectl` internals to improve composability, readability and testability of `kubectl` commands. Those refactors will allow the team to extract a mechanism for extensibility of kubectl -- that is, plugins -- in the next releases.

### SIG Cluster Lifecycle

 *  New: Make OkHttp OSGi ready.
 *  New: Add already-implemented interfaces Closeable and Flushable to the cache.


## Version 3.0.0-RC1

_2016-01-02_

OkHttp 3 is a major release focused on API simplicity and consistency. The API
changes are numerous but most are cosmetic. Applications should be able to
upgrade from the 2.x API to the 3.x API mechanically and without risk.

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StaticPodPath, ManifestURL is renamed to StaticPodURL, and ManifestURLHeader is renamed to StaticPodURLHeader. Users should focus on switching to the v1beta1 API. ([#60314](https://github.com/kubernetes/kubernetes/pull/60314), [@mtaufen](https://github.com/mtaufen))

* The DevicePlugins feature has graduated to beta, and is now enabled by default; users should focus on moving to the v1beta API if possible. ([#60170](https://github.com/kubernetes/kubernetes/pull/60170), [@jiayingz](http...

* Remove Azure kube-up as the Azure community has focused efforts elsewhere. ([#41672](https://github.com/kubernetes/kubernetes/pull/41672), [@mikedanese](https://github.com/mikedanese))

    are available in Linux x86, Windows x86, and Linux aarch64 packages.

    *   **Linux x86 packages:**
        *   oneDNN optimizations are *enabled by default* on CPUs with
            neural-network-focused hardware features such as AVX512_VNNI,
            AVX512_BF16, AMX, etc.
            ([Intel Cascade Lake](https://www.intel.com/content/www/us/en/products/platforms/details/cascade-lake.html)
            and newer CPUs.)

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