manylinux_2_28 support
This was discussed at a SIG Build meeting recently (http://bit.ly/tf-sig-build-notes). Will likely be discussed again on the next one in December Thanks @mihaimaruseac for sharing the SIG build meeting pointers. We will wait when this is decided. For short term, I have one specific questions. If we install GCC11 in manylinux2014, will it break/violate manylinux2014 rules? Do you foresee any issue in such upgrade of gcc version? My understanding is that unless you compile everything with the same compiler you might hit some hard to debug issues (data corruption, etc.). Maybe not if you're using newer compilers now, but it was a certain thing in the past if you had some piece of code that used one ABI for `std::string` and another piece that used another ABI.

If you build everything yourself, you won't have this issue, but it will no longer be manylinux2014. Thanks @mihaimaruseac for the reply.
I have created manylinux2014 env and installed gcc 11 using the command:
yum install -y centos-release-scl
yum install -y devtoolset-11
Now if i am building TensorFlow for CPU using the default bazel build command, do you think it will be no longer manylinux2014?
Is there any workaround for it?

 I'm not sure. You can try building the wheel and then run `auditwheel` on it to see manylinux compliance
### Issue type

Build/Install

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

TF 2.15

### Custom code

Yes

### OS platform and distribution

Ubuntu 22.04

### Mobile device

Linux Ubuntu 22.04

### Python version

3.9

### Bazel version

Latest

### GCC/compiler version

10.2

### CUDA/cuDNN version

NA

### GPU model and memory

NA

### Current behavior?

This is not a bug, but didnt find a better place to ask the question.
Can we use manylinux_2_28 to build latest tensorflow v2.15? Latest binaries are released with manylinux2014 which use gcc 10.2.x. However to use the some of the flags available in GCC11/GCC12, can we use manylinux_2_28 to build Tensorflow binaries for CPU?

### Standalone code to reproduce the issue

```shell
N/A
```


### Relevant log output

```shell
NA
```
