- Added a "reason" field to the "image_garbage_collected_total" metric, allowing administrators to differentiate between images that were collected for reasons "age" vs "space".
   ([#123345](https://github.com/kubernetes/kubernetes/pull/123345), [@haircommander](https://github.com/haircommander))

For more information and other documents, see <a href="/">go.dev</a>.
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<p>
Go is a general-purpose language designed with systems programming
in mind. It is strongly typed and garbage-collected and has explicit
support for concurrent programming.  Programs are constructed from
<i>packages</i>, whose properties allow efficient management of
dependencies.
</p>

<p>

- Fixed a regression in default 1.26 configurations, which enabled PodDisruptionConditions by default, 

covered work so as to satisfy simultaneously your obligations under this
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- Garbage collector now can correctly orphan ControllerRevisions when StatefulSets are deleted with orphan propagation policy. ([#84984](https://github.com/kubernetes/kubernetes/pull/84984), [@cofyc](https://github.com/cofyc)) [SIG Apps]

### Other notable changes

* Corrected family type (inet6) for ipsets in ipv6-only clusters ([#68436](https://github.com/kubernetes/kubernetes/pull/68436), [@uablrek](https://github.com/uablrek))
* Corrects check for non-Azure managed nodes with the Azure cloud provider ([#70135](https://github.com/kubernetes/kubernetes/pull/70135), [@marc-sensenich](https://github.com/marc-sensenich))

- This PR corrects that documentation, making it clear to users that podSelector is optional and describes its default behavior. ([#131354](https://github.com/kubernetes/kubernetes/pull/131354), [@tomoish](https://github.com/tomoish)) [SIG Network]

- Fixes a bug where images pinned by the container runtime can be garbage collected by kubelet. ([#120056](https://github.com/kubernetes/kubernetes/pull/120056), [@ruiwen-zhao](https://github.com/ruiwen-zhao)) [SIG Node]

        should switch to
        `tf.estimator.Estimator.experimental_export_all_saved_models`.
*   tf.data:
    *   Add `tf.data.experimental.StatsOptions()`, to configure options to
        collect statistics from `tf.data.Dataset` pipeline using
        `StatsAggregator`. Add nested option, `experimental_stats` (which takes
        a `tf.data.experimen tal.StatsOptions` object), to `tf.data.Options`.