A detailed dive into resolvers, and a kickoff article to a series about Paypal's best practices and observations for building GraphQL APIs. Offering some tips and guidance for understanding how common practices could end up being inefficient, the article covers fetching and passing data in resolvers and subsequently illuminates the points with some examples. A great read for a well-written summary of effective resolver practices.
Describing how GraphQL supports the buzzing engine of the Netflix Marketing Tech team (covered in a fascinating series in its own right: part 1 and part 2), this blog post explains the benefits offered by GraphQL for the internal application that creates and manages Netlfix ads, called Monet. It also covers the challenges that GraphQL brought with it: such as duplicate network requests, difficulty debugging code due to abstraction, and the impact of partial objects fetched with GraphQL.
An interesting overview of schema stitching in production! Reading this article, which covers both schema stitching and schema merging rooted in examples and experiences from artsy, one comes away with an understanding of the ways to apply and use schema stitching as well as how to validate that the process was done successfully.
TentaQL is an open source automated tool for GraphQL data-abstraction-layer creation. Supporting PostgreSQL, MongoDB, and MySQL, it is accessible via a web app where a user can submit their database URI and get a zip package for running GraphQL. Currently still in Beta, TentaQL also offers a Postgres and Mongo demo for users eager to explore the feature set without sharing their own details.