- Fix a bug where loadbalancer deletion gets stuck because of missing resource group. ([#93962](https://github.com/kubernetes/kubernetes/pull/93962), [@phiphi282](https://github.com/phiphi282))

- Fix azure file migration panic ([#94853](https://github.com/kubernetes/kubernetes/pull/94853), [@andyzhangx](https://github.com/andyzhangx)) [SIG Cloud Provider]
- Fix bug where loadbalancer deletion gets stuck because of missing resource group [#75198](https://github.com/kubernetes/kubernetes/issues/75198) ([#93962](https://github.com/kubernetes/kubernetes/pull/93962), [@phiphi282](https://github.com/phiphi282)) [SIG Cloud Provider]

from-ut.com
from-va.com
from-vt.com
from-wa.com
from-wi.com
from-wv.com
from-wy.com
ftpaccess.cc
fuettertdasnetz.de
game-host.org
game-server.cc
getmyip.com
gets-it.net
go.dyndns.org
gotdns.com
gotdns.org
groks-the.info
groks-this.info
ham-radio-op.net
here-for-more.info
hobby-site.com
hobby-site.org
home.dyndns.org
homedns.org

* scheduler: Fix issue were a new pod with affinity gets stuck at `creating` because the node had been deleted but the pod still exists. ([#56835](https://github.com/kubernetes/kubernetes/pull/56835), [@wenlxie](https://github.com/wenlxie))

* kubectl will list all allowed print formats when an invalid format is passed. ([#64371](https://github.com/kubernetes/kubernetes/pull/64371), [@CaoShuFeng](https://github.com/CaoShuFeng))

  
  Fixed multiple iptables proxy regressions introduced in 1.22:
  
    - When using Services with SessionAffinity, client affinity for an
      endpoint now gets broken when that endpoint becomes non-ready
      (rather than continuing until the endpoint is fully deleted).
  
    - Traffic to a service IP now starts getting rejected (as opposed to

            instead of relying on `Model.inputs` and `Model.input_names`, which
            are no longer set for subclass Models. This attr is set in eager,
            `tf.function`, and graph modes. This gets rid of the need for users
            to manually call `Model._set_inputs` when using Custom Training
            Loops(CTLs).
        *   Dynamic shapes are supported for generators by calling the Model on