GraphQL Deep Dive - Bruno Scheufler

GraphQL makes it easy to design APIs for multiple platforms at once, allowing you to iterate quickly and build products faster. Scaling GraphQL APIs can be challenging, and I've written about some of the best practices and solutions I've encountered along the way.

Jul 25, 2021

Improving DataLoader Stack Traces

DataLoader is an elegant solution for batching access to your application data layer, and optionally caching it for subsequent access. With the rise of GraphQL, DataLoader has grown in popularity too, as it can be used for accessing data in multiple layers, caching it the first time, and returning the cached resource immediately on lower layers....GraphQL

Mar 10, 2021

Efficient Caching with Reduced Roundtrips

Imagine you're building a service that heavily depends on content served by an external provider. Sending a request each time a resource is accessed would quickly lead to rate-limiting, so to provide an improved experience, we want to introduce caching....Caching, DataLoader, Systems Architecture

Feb 04, 2021

GraphQL-powered API Integration Tests

When you build a service focused around a GraphQL endpoint, you might think of testing strategies that can make use of it. After all, your resolvers will contain large parts of the actual business logic, otherwise, exposing an API wouldn't be useful, would it?...GraphQL, Testing, Integration Tests, Apollo

Jan 17, 2021

Centralized Validation with GraphQL Scalar Types

When building user-facing API products and services, validating inputs and enforcing limits is hugely important. Often, this involves repeating similar steps to check given parameters and arguments. Since you can't really trust user-supplied data until it is validated, you're usually required to validate arguments and then perform your business logic. Repeating this in multiple places is cumbersome and opens up possibilities for code duplication, missing validation steps, or other unintended side effects....GraphQL