Testing and debugging resolvers in AWS AppSync (JavaScript)

AWS AppSync executes resolvers on a GraphQL field against a data source. When working with pipeline resolvers, functions interact with your data sources. As described in the JavaScript resolvers overview, functions communicate with data sources by using request and response handlers written in JavaScript and running on the APPSYNC_JS runtime. This enables you to provide custom logic and conditions before and after communicating with the data source.

To help developers write, test, and debug these resolvers, the AWS AppSync console also provides tools to create a GraphQL request and response with mock data down to the individual field resolver. Additionally, you can perform queries, mutations, and subscriptions in the AWS AppSync console and see a detailed log stream of the entire request from Amazon CloudWatch. This includes results from the data source.

Testing with mock data

When a GraphQL resolver is invoked, it contains a context object that has relevant information about the request. This includes arguments from a client, identity information, and data from the parent GraphQL field. It also stores the results from the data source, which can be used in the response handler. For more information about this structure and the available helper utilities to use when programming, see the Resolver context object reference.

When writing or editing a resolver function, you can pass a mock or test context object into the console editor. This enables you to see how both the request and the response handlers evaluate without actually running against a data source. For example, you can pass a test firstname: Shaggy argument and see how it evaluates when using ctx.args.firstname in your template code. You could also test the evaluation of any utility helpers such as util.autoId() or util.time.nowISO8601().

Testing resolvers

This example will use the AWS AppSync console to test resolvers.

For a more practical example, suppose you have an app storing a GraphQL type of Dog that uses automatic ID generation for objects and stores them in Amazon DynamoDB. You also want to write some values from the arguments of a GraphQL mutation and allow only specific users to see a response. The following snippet shows what the schema might look like:

type Dog {
  breed: String
  color: String
}

type Mutation {
  addDog(firstname: String, age: Int): Dog
}

You can write an AWS AppSync function and add it to your addDog resolver to handle the mutation. To test your AWS AppSync function, you can populate a context object like the following example. The following has arguments from the client of name and age, and a username populated in the identity object:

{
    "arguments" : {
        "firstname": "Shaggy",
        "age": 4
    },
    "source" : {},
    "result" : {
        "breed" : "Miniature Schnauzer",
        "color" : "black_grey"
    },
    "identity": {
        "sub" : "uuid",
        "issuer" : " https://cognito-idp.{region}.amazonaws.com/{userPoolId}",
        "username" : "Nadia",
        "claims" : { },
        "sourceIp" :[  "x.x.x.x" ],
        "defaultAuthStrategy" : "ALLOW"
    }
}

You can test your AWS AppSync function using the following code:

import { util } from '@aws-appsync/utils';

export function request(ctx) {
  return {
    operation: 'PutItem',
    key: util.dynamodb.toMapValues({ id: util.autoId() }),
    attributeValues: util.dynamodb.toMapValues(ctx.args),
  };
}

export function response(ctx) {
  if (ctx.identity.username === 'Nadia') {
    console.log("This request is allowed")
    return ctx.result;
  }
  util.unauthorized();
}

The evaluated request and response handler has the data from your test context object and the generated value from util.autoId(). Additionally, if you were to change the username to a value other than Nadia, the results won’t be returned because the authorization check would fail. For more information about fine-grained access control, see Authorization use cases.

Testing request and response handlers with AWS AppSync's APIs

You can use the EvaluateCode API command to remotely test your code with mocked data. To get started with the command, make sure you have added the appsync:evaluateMappingCode permission to your policy. For example:

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": "appsync:evaluateCode",
            "Resource": "arn:aws:appsync:<region>:<account>:*"
        }
    ]
}

You can leverage the command by using the AWS CLI or AWS SDKs. For example, take the Dog schema and its AWS AppSync function request and response handlers from the previous section. Using the CLI on your local station, save the code to a file named code.js, then save the context object to a file named context.json. From your shell, run the following command:

$ aws appsync evaluate-code \
  --code file://code.js \
  --function response \
  --context file://context.json \
  --runtime name=APPSYNC_JS,runtimeVersion=1.0.0

The response contains an evaluationResult containing the payload returned by your handler. It also contains a logs object, that holds the list of logs that were generated by your handler during the evaluation. This makes it easy to debug your code execution and see information about your evaluation to help troubleshoot. For example:

{
    "evaluationResult": "{\"breed\":\"Miniature Schnauzer\",\"color\":\"black_grey\"}",
    "logs": [
        "INFO - code.js:13:5: \"This request is allowed\""
    ]
}

The evaluationResult can be parsed as JSON, which gives:

{
  "breed": "Miniature Schnauzer",
  "color": "black_grey"
}

Using the SDK, you can easily incorporate tests from your favorite test suite to validate your handlers' behavior. We recommend creating tests using the Jest Testing Framework, but any testing suite works. The following snippet shows a hypothetical validation run. Note that we expect the evaluation response to be valid JSON, so we use JSON.parse to retrieve JSON from the string response:

const AWS = require('aws-sdk')
const fs = require('fs')
const client = new AWS.AppSync({ region: 'us-east-2' })
const runtime = {name:'APPSYNC_JS',runtimeVersion:'1.0.0')

test('request correctly calls DynamoDB', async () => {
  const code = fs.readFileSync('./code.js', 'utf8')
  const context = fs.readFileSync('./context.json', 'utf8')
  const contextJSON = JSON.parse(context)
  
  const response = await client.evaluateCode({ code, context, runtime, function: 'request' }).promise()
  const result = JSON.parse(response.evaluationResult)
  
  expect(result.key.id.S).toBeDefined()
  expect(result.attributeValues.firstname.S).toEqual(contextJSON.arguments.firstname)
})

This yields the following result:

Ran all test suites.
> jest

PASS ./index.test.js
✓ request correctly calls DynamoDB (543 ms)
Test Suites: 1 passed, 1 total
Tests: 1 passed, 1 total
Snapshots: 0 totalTime: 1.511 s, estimated 2 s

Debugging a live query

There’s no substitute for an end-to-end test and logging to debug a production application. AWS AppSync lets you log errors and full request details using Amazon CloudWatch. Additionally, you can use the AWS AppSync console to test GraphQL queries, mutations, and subscriptions and live stream log data for each request back into the query editor to debug in real time. For subscriptions, the logs display connection-time information.

To perform this, you need to have Amazon CloudWatch logs enabled in advance, as described in Monitoring and logging. Next, in the AWS AppSync console, choose the Queries tab and then enter a valid GraphQL query. In the lower-right section, click and drag the Logs window to open the logs view. At the top of the page, choose the play arrow icon to run your GraphQL query. In a few moments, your full request and response logs for the operation are streamed to this section and you can view them in the console.