Infrastructure update for Channel Cloning/CDN sync

### Your question:

Hey everyone,

we (Anaconda) have been working on upgrades for the channel cloning/CDN sync infrastructure of anaconda.org, which is is used for conda-forge.

## Time planning

We are planning to switch to the new infrastructure tomorrow, 2024-08-27 at 12:30 UTC.
**No downtime is expected for users**.

Due to the amount of changes on the conda-forge channel, the initial sync after the switch to the new infrastructure will be a bit slower than the usual syncs - it is currently running in a "dry run" mode on the new infrastructure already to keep its caches up to date, and I expect the initial sync on the new infrastructure to take ~30 minutes.

We have already implemented this change for the r and anaconda channels to ensure that our maintenance process and the new infrastructure are working as desired.

## What's changing?

* The codebase has been updated to make the cloning more fault-tolerant and reliable
* The new infrastructure is more tightly integrated into our observability stack, enabling us to detect problems earlier and more granularly (e.g. a specific package that fails to clone instead of just a general cloning error)
* We're adding a `last-updated.json` file at the channel root, which contains the last update time both as UNIX and ISO8601 timestamps. We are using this directly to monitor the updates end-to-end. Check it out for the [anaconda](https://conda.anaconda.org/anaconda/last-updated.json) channel if you're interested!

## Other notes

This topic was discussed in the conda-forge meeting on 2024-08-21 and it was decided to bring it up here to raise awareness.

If there's any questions, please ask!

The issue is an infrastructure announcement rather than a contribution task and names no files, tests, or entry points. Start by confirming whether the planned switch has already happened and locating the channel cloning/CDN sync and observability configuration. No newcomer-sized definition of done is provided.

Written by the indexing model from the issue text.