Every team building on language models arrives at the same realisation at roughly the same point. You have shipped something, it is being used, and you cannot answer basic questions about it. What did users actually send. What did the model actually return when that complaint came in.
Why did the bill triple last month and which feature did it. Which of your prompts is slow. How often are you sending the same request twice. Logging model calls yourself is not hard, and it is also never the most urgent thing, so it does not get done, and the questions stay unanswered.
This category exists to close that gap and this is one of the easier entry points into it. The integration story is the genuine strength and the documentation demonstrates rather than asserts it. You change a base URL, or you add a header, and requests start being logged. That is it.
For a team that has been meaning to build logging for four months, the friction of getting something working in an afternoon is worth a lot, and the docs are honest and clear about how little you have to do. Cost attribution is the material I would actually recommend reading. The default state of most projects is a single monthly bill with no breakdown, and every conversation about whether a feature is worth its inference cost is therefore conducted on vibes. The documentation shows you how to tag requests with user identifiers, session identifiers and arbitrary properties, and then slice spend by them.
Doing this early changes the quality of your product decisions, because you can finally say that the summarisation feature costs a certain amount per active user per month, and have that be a fact rather than a guess. The caching pages are practical and the savings are not theoretical. A surprising proportion of production traffic in many applications is repeated or near repeated, and returning a stored response is both free and instant. The documentation covers the configuration and, to its credit, the cases where caching is wrong, which is more than some competitors manage.
Now the part that bothers me. The headline integration works by routing your requests through the vendor's infrastructure. That is why it is one line. It also means a third party is now in the path of every model call your application makes, seeing every prompt and every completion, and capable of taking your application down if they have a bad day.
There is an asynchronous logging option that avoids this, and it is documented, and it is not the default and not what the getting started page leads with. For a category whose entire purpose is visibility into your production system, the docs are notably quiet about the availability implications of the recommended architecture. Anyone evaluating this should make that decision deliberately. The teaching is product-shaped rather than discipline-shaped.
You will finish knowing how to use this tool. You will not finish knowing what to instrument and why, how to think about sampling when volume gets expensive, what a useful trace looks like when a single user action produces fifteen model calls, or how observability for model applications differs from the observability practice your organisation already has for its services. Those are the questions that make someone good at this, and the documentation is not trying to answer them. Evaluation is thin.
There is functionality for scoring outputs and it exists next to tools whose whole purpose is evaluation and which are considerably deeper. If evaluation is your main concern, this is not the material to learn from. And as ever with vendor documentation, there is nothing about when a competitor is a better fit or when your existing tracing stack would do the job with an exporter. That is expected and it is still a limitation on this as a learning resource.
My three point five is for a genuinely frictionless introduction to a category teams need and neglect, with cost attribution and caching guidance that will pay for themselves quickly. Marked down for leading with an architecture that inserts a vendor into your critical path without saying so plainly, for teaching the product instead of the practice, and for shallow evaluation coverage. Useful, and read it with the proxy question in mind.