As with everything, it depends on your requirements.
Say your goal is to externalize just your authorization policies from your code. A simple implementation might look like an OPA sidecar to your services, with the policy itself being sourced from a separate control plane - this might be something as simple as a centrally-managed S3 bucket.
The service implementation provides the attributes to OPA to allow it to evaluate the authorization policy as part of the query. e.g. which groups is this user in, what document are they accessing, is this a read, write or delete operation.
If you want to externalize sourcing of the attributes as well, that becomes more complicated. Now you need your authorization framework to know that Bob is in "Accounting" or that quarter_end_results.xls is a document of type "Financial Results".
You can either go push or pull for attribute sourcing.
The push model is to have the relevant attribute universe delivered to each of the policy decision points, along with the policy itself. This improves static stability, as you reduce the number of real-time dependencies required for authorization queries but can be a serious data distribution and management problem - particularly if you need to be sure that data isn't going stale in some sidecar process somewhere for some reason.
The pull model is to have an attribute provider that can you can query as necessary; probably backed with an attribute cache for sanity's sake. The problems are basically the opposite set - liveness is guaranteed but static stability is more complicated.
The methods are not equivalent: in particular, the pull model is sufficient to answer simple authorization questions like 'can X do Y to Z?' - we pull the attributes of X, Y and Z and evaluate the authorization policy.
However, if you need to answer questions like 'to which Z can X do Y?', how does that work? For simple cases you may be able to iterate over the universe of Z's asking the prior question; but it generalizes poorly.