Lately, Ive been exploring AWS AppSync Merged APIs to better understand the complexities and tradeoffs involved in creating a unified GraphQL API experience that can be supported by various subdomain teams.
Motivation
GraphQL is all about the graph formed by the Types in the schema. Forming relationships between Types allows clients to connect these different entities. This enables enhanced client experiences and can result in more efficient server interactions.
However, as the number of Types (vertices in the graph) increases, so does the maintenance of the API. Maybe the API holds all the functionality for a scaling business, and so the capabilities of the API and the number of engineers supporting the API grow. If the GraphQL API is implemented in AppSync, Merged APIs can help lower the cognitive load of maintenance by allowing subsections of the API to be powered by Source APIs (and possibly a single domain team).
Example
Our simplified example involves the API of a fictional car manufacturer called Wheely. Wheely has software teams supporting two areas of the business: Parts Manufacturing and Car Assembly. Due to various reasons, the two teams prefer not to maintain their shared AppSync API in a single codebase (possibly due to differences like spaces vs. tabs). They decide to split the codebase to better suit their domains' needs but still aim to collectively provide support for a unified GraphQL API to maximize its benefits for the business.
They opt to use AppSync Merged APIs to create a single Wheely API supported by a single AppSync API for each domain. The Car Assembly team wants to manage the core information about Wheely's car offerings, while the Parts Manufacturing team focuses on overseeing the inventory of parts used in the cars. Both teams also see the value in being able to retrieve all parts used in a specific car as a key feature of the API.
API Design
Both source APIs will provide their parts of the overall GraphQL API and each leverage the @canonical annotation to avoid conflicts on Types and Fields.
Car Assembly
The Car Assembly API owns the Car Type and the getCar Query. This schema also has the Car.parts Field, but makes note to other engineers that it does not own it, so other engineers can be aware of this dependency. The same is true for the Part Type.
# Owned by the Parts Manufacturing AppSync API
type Part {
id: ID!
}
type Car @canonical {
id: ID!
make: String!
model: String!
# Owned by the Parts Manufacturing AppSync API
parts: [Part!]!
}
type Query {
getCar(id: ID!): Car @canonical
}
Parts Manufacturing
The Parts Manufacturing API owns the Part Type and the getPart Field. It also owns the Car.parts Field even though it doesn't own the Car Type. This AppSync API has a resolver for the Car.parts Field and no other source API can add a resolver for that Field, making this API the source of truth for this piece of data.
# Owned by the Car Assembly AppSync API
type Car {
parts: [Part!]! @canonical
}
type Part @canonical {
id: ID!
name: String!
}
type Query {
getPart(id: ID!): Part @canonical
}
Car.parts Resolver
This resolver relies on the IDs of the parts to retrieve being passed to it either via the source or stash in the context. It then uses those IDs to filter its datastore to retrieve the parts needed to fulfill the parts Field for the request.
/**
* This resolver assumes the part IDs will be a field from the parent field OR be included in the stash.
*/
export function request(ctx) {
/**
* @type {string[] | undefined}
*/
const partIds = ctx.source.partIds ? ctx.source.partIds : ctx.stash.partIds;
if (partIds === undefined) {
util.error('No part IDs supplied.')
}
const parts = [
{
id: "1",
name: "Headlights"
},
{
id: "2",
name: "Sunroof"
},
{
id: "3",
name: "Leather Seats"
},
{
id: "4",
name: "Cloth Seats"
}
];
return {
payload: parts.filter(part => partIds.includes(part.id))
};
}
export function response(ctx) {
return ctx.result
}
Merged API
This is the final merged API that the client would depend on. The client doesn't see that the implementation of this is spread across multiple APIs. We've really leaned into the "Interface" part of the API here.
type Car {
id: ID!
make: String!
model: String!
parts: [Part!]!
}
type Part {
id: ID!
name: String!
}
type Query {
getCar(id: ID!): Car
getPart(id: ID!): Part
}
Tradeoffs and Considerations
Managing API Design
With the nested Type dependency from the merged APIs, communication between owners of the Source APIs is important. GraphQL design (and any API for that matter) should have time put into the "how" it should work. Doing that over disparate teams and evolving the API over time increases complexity.
Collaboration is always important in software engineering. However, using Merged APIs without a plan of how to drive changes, who owns which parts, or which parts live in which AppSync APIs could hinder success.
Contract Coordination
As you can see in the Car.parts resolver, it expects the partIds data to be passed in either from the parent Field resolver (in the source) or inserted earlier in the request's stash. The implementation in the repository will have the Query.getCar resolver always return the partIds Field to AppSync, even if the client doesn't request the Car.parts Field. It's returning the entire data model.
This works fine for this simple example. But, maybe in the future, the Car Assembly team makes a design decision to only return to AppSync Fields that the client requests, so they can increase performance. If the client doesn't request Car.parts, then the resolver will not return partIds, and then the implicit contract between that API and the Parts Manufacturing API will break.
Similar to the API design consideration above, the software teams need to be aware of the interactions between dependencies and dependents.
"Unowned" API Resources
In AppSync Merged APIs, the resulting API is the combination of all the source APIs. Not everything in the Merged API needs the @canonical annotation though. Source APIs can contribute any Type, Query, Mutation, etc. and not provide any conflict-resolution through the @canonical annotation. Conflicting definitions could result in unexpected behaviors for clients and bugs.
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