Start today: create a new GitHub repository, initialize a CDK app, add your schema.graphql , write one resolver, and deploy it. Once you have that working, expand with data sources, pipelines, and real-time subscriptions. Your future self — and your team — will thank you.
type Item { id: ID! name: String! createdAt: AWSDateTime! } type Query { getItem(id: ID!): Item } appsync repo
my-appsync-repo/ ├── backend/ │ ├── schema/ │ │ └── schema.graphql │ ├── resolvers/ │ │ ├── Query/ │ │ │ ├── getItem.js │ │ │ └── listItems.js │ │ ├── Mutation/ │ │ │ ├── createItem.js │ │ │ └── updateItem.js │ │ └── pipelines/ │ ├── datasources/ │ │ └── datasources.json │ └── functions/ │ └── auth.js ├── infrastructure/ │ ├── appsync-stack.ts (CDK) │ └── config/ ├── tests/ │ ├── unit/ │ └── integration/ ├── scripts/ │ └── deploy.sh └── README.md This is the heart of your API. It defines types, queries, mutations, and subscriptions. Keep it in a single file or split it using #import directives. Example: Start today: create a new GitHub repository, initialize
An AppSync repo is not just about storing code; it is about treating your GraphQL API as a first-class, version-controlled, testable, and automatable component of your cloud architecture. Have you built an AppSync repo using a different pattern? Share your experience in the comments below, or check out the official AWS AppSync GitHub organization for more examples. type Item { id: ID
