• [ ] An Introduction to GraphQL
• [ ] One-Size-Fits-All
• [ ] Let’s Go Back in Time
• [ ] Enter GraphQL
• [ ] Type System
• [ ] Introspection

• [ ] What Makes an API Great?
• [ ] Design First
• [ ] Client First
• [ ] Naming
• [ ] Descriptions
• [ ] Use the Schema, Luke!
• [ ] Expressive Schemas
• [ ] Specific or Generic
• [ ] The Relay Specification
• [ ] Lists & Pagination
• [ ] Sharing Types
• [ ] Global Identification
• [ ] Nullability
• [ ] Abstract Types
• [ ] Designing for Static Queries
• [ ] Mutations
• [ ] Fine-Grained or Coarse-Grained
• [ ] Errors
• [ ] Schema Organization
• [ ] Asynchronous Behavior
• [ ] Data-Driven Schema vs Use-Case-Driven Schema

Take-away:

1. design, code, schema first approaches
2. SDL generation audits
3. secretField: SecretType @featureFlagged(name: "secret")
4. mutating the context object
5. how to audit the query root
6. metadata on types
7. security and calculate complexity with dry run
8. REDACTED tooling

• [X] GraphQL Server Basics
• [ ] Code First vs SchemaFirst
• [ ] Generating SDL Artifacts
• [ ] Resolver Design
• [ ] Schema Metadata
• [ ] Multiple Schemas
• [ ] Modular Schemas
• [ ] Testing

Servers are created given a type definition and a runtime.

Resolvers:

  function resolveName(parent, arguments, context) {
      return parent.name;
  }

  resolveName({name: 'Jason'});

  query {
    user(id: "1234") {
      name
    }
  }

Resolvers cascade from the root.

  digraph G {
          resolver -> {
                  root
                  gco
          }
  }

Schema-first approaches allow for the definition of types but without any business logic.

This requires creating a root with a resolver as well as the schema with the root resolver (as compared with a secondary resolver?).

  const root = {
      hello: () => {
          return 'Hello'
      }
  }

  graphql(schema, '{ hello }', root). then((resp) => {
      console.log(resp);
  });

• [ ] Rate Limiting
• [ ] Blocking Abusive Queries
• [ ] Timeouts
• [ ] Authentication
• [ ] Authorization
• [ ] Blocking Introspection
• [ ] Persisted Queries

• [ ] Monitoring
• [ ] The N+1 Problem and the Dataloader Pattern
• [ ] Caching
• [ ] Compiled Queries

• [ ] Linting
• [ ] Analytics

• [ ] Design
• [ ] Review
• [ ] Development
• [ ] Publish
• [ ] Analyze Ship

• [ ] Is GraphQL a Good Choice for Public APIs
• [ ] Lack of Conventions
• [ ] With Great Power comes Great Responsibility

• [ ] GraphQL API Gateway
• [ ] GraphQL as a BFF
• [ ] Service Communication

• [ ] API Versioning is Never Fun
• [ ] Versioning GraphQL is Possible
• [ ] Continuous Evolution
• [ ] Change Management

• [ ] Documentation Generators
• [ ] The What, Not Just the How
• [ ] Workflows and Use Cases
• [ ] Example / Pre-Made Queries
• [ ] Changelogs
• [ ] Upcoming Changes

• [ ] Generators
• [ ] REST & GraphQL Alongside