[ECR] [request]: Apply lifecycle rules to tags (not images)

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**Tell us about your request**
I would like for ECR lifecycle policies to apply to image tags, instead of images.

**Which service(s) is this request for?**
ECR

**Tell us about the problem you're trying to solve. What are you trying to do, and why is it hard?**
Right now, when we push an image it includes multiple tags, like:

- `github-sha-` for every build
- `-latest` for every build from a PR
- `v1.2.3` if built from a tag/release

We want to expire `github-sha-*` tags frequently, but keep the other tags forever. Currently, we have to create a high priority rule for each tag pattern we want to keep, e.g. `v*` and `*-latest`.

However, this frequently results in images being accidentally expired. If someone manually adds a tag (like `dev-`) but the build also includes a `github-sha-` tag, then the image will be expired because the `github-sha-*` tag rule is matched, even though the image has additional tags that wouldn't be expired by any rule.

I would like to be able to create a lifecycle rule that only removes the _tag_ matching the rule, not the entire image. Then, an additional rule can delete untagged images to free up storage. This way, the behaviour is as expected - tags matching the rule pattern are deleted, and other tags are not affected if they are on the same image.

My proposal is to add a new `action` value to the rules: `expireTag` that has this effect, but I'm not set on this.

**Are you currently working around this issue?**

Currently, we insert a high priority rule for all of the tag patterns we want to keep. But as mentioned above, this frequently results in images being accidentally expired.

Start by reviewing the ECR lifecycle policy behavior described in the issue, including image tags, tag patterns, and the proposed expireTag action. Confirm whether the requested tag-only expiration is supported by the relevant ECR API and documentation; done means matching tags can be removed without expiring an image that has other tags.

Written by the indexing model from the issue text.