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Comment by dnautics | Hacker News Reader

The whole point of graphQL is to allow FE teams to decide what information they need in an organizationally decoupled fashion, you haven't done that at all. Suppose FE wants another join on that object, now they must wait for you to push more code enabling those queries.

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Unfortunately for graphql, the claim that backend teams need to be constantly making endpoints for other decoupled teams is not as drastic and critical as you consider it to be.

Dare i even say switching to graphql and onboarding developers to graphql is a much more resource intensive process than adding another endpoint (or a couple).

> onboarding developers to graphql is a much more resource intensive process

As a BE/remote I basically taught myself most of elixir's graphQL framework in a day (wait, that was yesterday), while under feature pressure (due this afternoon), mostly by poking around and doing a bit of TDD. There are parts that I really hate about graphQL, but overall I consider it a win.

The problem with GraphQL is on the front end. Suddenly, the FE team becomes responsible for understanding the entire data model, which resources can be joined together, by what keys, and what is actually performant vs what isn't.

Instead of doing a simple GET /a/b/1/c and presenting that data structure, they now need to define a query, think about what resources to pull into that query etc. If the query ends up being slow, they have to understand why and work on more complex changes than simply asking the BE team for a smaller response with a few query params.

that's an interesting point! And the graphql basically obscures a mental model over a broad abstraction, so it's impossible to know exactly what's going on without going through and actually reading the BE code itself. Thanks for the perspective.

I hit this problem when contemplating exposing the API of the application I work on to customers, to be used in their automation scripts.

We quickly realized that expecting them to learn our data model and how to use it efficiently would be much more complicated than exposing every plausible use-case explicitly. We could do this on the "API front-end" by building a set of high-level utilities that would embed the GraphQL queries, but that would essentially double much of the work being done in the front-end (and more than double if some customers want to use Python scripting while others want JS and others want TCL or Perl).

So, we decided that the best place to expose those high-level abstractions is exactly the REST API, where it is maximally re-usable.

also, to add another point.

Most API teams will give you all the resources that you need.

It is most likely the case that the FE team will ask not for more, but rather, for less.

This was the exact problem why GraphQl was created in the first place - to account for Facebook's mobile platform, because they were receiving way too much data that needed to be trimmed because they didn't want to be sending like 500kb of json over mobile networks.

Competent API teams will give you all the resources that you need to be productive as a FE engineer, and if it is the case that your data needs some trimming, then go ahead and ask your decoupled backend team, while you can go ahead and keep working asynchronously while they get that done for you.

Not Fatal as you think it is.

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