Introducción
He estado construyendo API GraphQL en un entorno sin servidor durante más de 3 años. Ya ni siquiera puedo imaginar trabajar con API RESTful. Combine el poder de GraphQL con la escalabilidad de AWS Lambda y tendrá un servidor que puede manejar cantidades infinitas de tráfico.
En este tutorial, crearemos e implementaremos un servidor GraphQL en AWS Lambda y accederemos a él a través de un punto final de API Gateway. Usaremos CloudFormation y la AWS CLI para implementar todos nuestros recursos de AWS y el código de la aplicación.
Lo que cubriremos
- Construya un servidor GraphQL usando Apollo
- Implemente ese servidor GraphQL en Lambda
- Utilice API Gateway para enviar solicitudes a Lambda
- Utilice CloudFormation para implementar la pila de aplicaciones en AWS
- Configure Lambda para el desarrollo local.
TL; DR: puede obtener el código fuente completo de la aplicación en Github.
¿Qué es GraphQL?
GraphQL es un lenguaje de consulta para describir API utilizando un sistema de esquema fuertemente tipado. Un servidor GraphQL responde a esas consultas utilizando datos existentes. A continuación se muestran algunas de las principales ventajas de utilizar GraphQL.
Consulta solo lo que necesita tu aplicación
A diferencia de las API REST, GraphQL permite a los clientes consultar con precisión y solo lo que necesitan. El servidor cumple la solicitud del cliente devolviendo solo lo que el cliente solicita.
GraphQL usa un sistema fuertemente tipado
El sistema fuertemente tipado de GraphQL permite a los usuarios realizar una introspección del esquema completo. Y la API GraphQL sirve como documentación clara sobre las capacidades del servidor y le notifica sobre errores durante el desarrollo.
Puedes componer tus consultas en una sola solicitud
Con GraphQL, puede consultar varios recursos y obtener respuestas combinadas con una sola solicitud. Con menos solicitudes, las aplicaciones que usan GraphQL funcionan mucho más rápido.
¿Qué es AWS Lambda?
AWS Lambda es un servicio informático ofrecido por AWS que le permite ejecutar el código de su aplicación sin tener que administrar ningún servidor. AWS gestiona todos los gastos generales, como la infraestructura, la seguridad, los recursos, el sistema operativo y los parches, para que los desarrolladores puedan centrarse solo en crear la aplicación.
Empecemos…
Configurar el proyecto
Comencemos creando una carpeta de proyecto. Luego, cambie al directorio e inicialice un proyecto Node. Que estoy usando node 10.x
en los ejemplos. Puede instalar la versión de nodo de su elección usando asdf.
mkdir apollo-server-lambda-nodejs cd apollo-server-lambda-nodejs yarn init
A continuación, cree una carpeta que albergue todo nuestro código fuente.
mkdir src
Finalmente, cree un archivo de índice dentro del src
directorio que sirve como controlador lambda.
cd src touch index.js

Complete el archivo de índice con el siguiente código.
exports.handler = async () => { return { body: 'Hello from Lambda' }; };
El código anterior es un controlador Lambda muy simple que regresará Hello from Lambda
cuando se invoca. Primero implementemos nuestro código en AWS Lambda.
Empaqueta el código de la aplicación
Antes de que podamos implementar nuestro código en Lambda, debemos crear un zip de nuestra aplicación y cargarlo en un bucket de S3. Estamos utilizando AWS CLI para crear el depósito. Configure AWS CLI ahora siguiendo esta guía si aún no lo ha hecho.
Cree un bucket de S3 para usarlo para implementar nuestro código en Lambda. Elija un nombre único para su bucket de S3. Los nombres de los depósitos son únicos a nivel mundial en todas las regiones de AWS.
aws s3 mb s3://lambda-deploy-asln
Cree un archivo de la aplicación usando el comando zip y verifique los archivos dentro del zip.
zip -rq dist-latest.zip src package.json zipinfo dist-latest.zip
Copie el archivo zip en S3 mediante el comando AWS CLI.
aws s3 cp dist-latest.zip s3://lambda-deploy-asln/dist-latest.zip
Finalmente, use el siguiente comando para verificar que el archivo existe en S3.
aws s3 ls s3://lambda-deploy-asln

Ahora que hemos implementado la aplicación empaquetada en S3, a continuación, debemos configurar nuestro Lambda y API Gateway en AWS. En la siguiente sección, usaremos CloudFormation para configurar todos los recursos de AWS necesarios.
Configurar AWS lambda con integración de proxy de puerta de enlace API
CloudFormation es un servicio de AWS que nos ayuda a escribir infraestructura como código. CloudFormation hace que sea muy sencillo crear y administrar nuestros recursos de aplicaciones. Usemos CloudFormation para definir nuestra pila.
Cree un archivo llamado cloudformation.yml
en la raíz del proyecto.
touch cloudformation.yml
Agregue el siguiente código al cloudformation.yml
--- Description: GraphQL server on AWS lambda Parameters: Version: Description: Application version number Type: String BucketName: Description: S3 bucket name where the source code lives Type: String Resources: LambdaFunction: Type: AWS::Lambda::Function Properties: Code: S3Bucket: !Ref BucketName S3Key: !Sub dist-${Version}.zip Handler: src/index.handler Description: GraphQL Apollo Server Role: !GetAtt LambdaExecutionRole.Arn Runtime: nodejs10.x Timeout: 10 LambdaExecutionRole: Type: "AWS::IAM::Role" Properties: AssumeRolePolicyDocument: Version: "2012-10-17" Statement: - Effect: "Allow" Principal: Service: - "lambda.amazonaws.com" Action: - "sts:AssumeRole" Policies: - PolicyName: "LambdaFunctionPolicy" PolicyDocument: Version: '2012-10-17' Statement: - Effect: Allow Action: - logs:CreateLogGroup - logs:CreateLogStream - logs:PutLogEvents Resource: "*" GraphQLApi: Type: 'AWS::ApiGateway::RestApi' Properties: Name: apollo-graphql-api GraphQLApiResource: Type: 'AWS::ApiGateway::Resource' Properties: ParentId: !GetAtt GraphQLApi.RootResourceId RestApiId: !Ref GraphQLApi PathPart: 'graphql' GraphQLApiMethod: Type: 'AWS::ApiGateway::Method' Properties: RestApiId: !Ref GraphQLApi ResourceId: !Ref GraphQLApiResource AuthorizationType: None HttpMethod: POST Integration: Type: AWS_PROXY IntegrationHttpMethod: POST Uri: !Sub arn:aws:apigateway:${AWS::Region}:lambda:path/2015-03-31/functions/${LambdaFunction.Arn}/invocations GraphQLApiDeployment: Type: 'AWS::ApiGateway::Deployment' Properties: RestApiId: !Ref GraphQLApi StageName: v1 DependsOn: - GraphQLApiResource - GraphQLApiMethod GraphQLApiPermission: Type: 'AWS::Lambda::Permission' Properties: Action: lambda:invokeFunction FunctionName: !GetAtt LambdaFunction.Arn Principal: apigateway.amazonaws.com SourceArn: !Sub arn:aws:execute-api:${AWS::Region}:${AWS::AccountId}:${GraphQLApi}/* Outputs: ApiUrl: Description: Invoke url of API Gateway endpoint Value: !Sub //${GraphQLApi}.execute-api.${AWS::Region}.amazonaws.com/v1/graphql
Sé que están sucediendo muchas cosas en esta plantilla. Examinemos el código paso a paso.
Parámetros de plantilla
Firstly, we define some parameters that we use in the template. We can pass those variables as parameter overrides when deploying the CloudFormation Stack.
Description: GraphQL server on AWS lambda Parameters: Version: Description: Application version number Type: String BucketName: Description: S3 bucket name where the source code lives Type: String
Lambda Function
We define our lambda function specifying the path from where it should pull the application code. This bucket is the same one we created earlier.
LambdaFunction: Type: AWS::Lambda::Function Properties: Code: S3Bucket: !Ref BucketName S3Key: !Sub dist-${Version}.zip Handler: src/index.handler Description: GraphQL Apollo Server Role: !GetAtt LambdaExecutionRole.Arn Runtime: nodejs10.x Timeout: 10
We want our Lambda function to be able to send application logs to AWS CloudWatch. Lambda requires special permissions to be able to write logs to CloudWatch. So we create a role that enables writing to CloudWatch and assign it to the Lambda function.
LambdaExecutionRole: Type: "AWS::IAM::Role" Properties: AssumeRolePolicyDocument: Version: "2012-10-17" Statement: - Effect: "Allow" Principal: Service: - "lambda.amazonaws.com" Action: - "sts:AssumeRole" Policies: - PolicyName: "LambdaFunctionPolicy" PolicyDocument: Version: '2012-10-17' Statement: - Effect: Allow Action: - logs:CreateLogGroup - logs:CreateLogStream - logs:PutLogEvents Resource: "*"
API Gateway
We also want an HTTP endpoint to invoke the lambda function. API Gateway can be used to create an HTTP endpoint. We can then configure API Gateway to proxy all incoming requests from the client to the Lambda function and send the response from Lambda back to the client.
Firstly, we create an API Gateway RestApi.
GraphQLApi: Type: 'AWS::ApiGateway::RestApi' Properties: Name: apollo-graphql-api
Then, we create an API Gateway Resource, which accepts requests at /graphql
.
GraphQLApiResource: Type: 'AWS::ApiGateway::Resource' Properties: ParentId: !GetAtt GraphQLApi.RootResourceId RestApiId: !Ref GraphQLApi PathPart: 'graphql'
Next, we configure the Resource to accept POST requests by creating an API Gateway Method and then we integrate it with Lambda.
GraphQLApiMethod: Type: 'AWS::ApiGateway::Method' Properties: RestApiId: !Ref GraphQLApi ResourceId: !Ref GraphQLApiResource AuthorizationType: None HttpMethod: POST Integration: Type: AWS_PROXY IntegrationHttpMethod: POST Uri: !Sub arn:aws:apigateway:${AWS::Region}:lambda:path/2015-03-31/functions/${LambdaFunction.Arn}/invocations
Finally, we create an API Gateway Deployment which deploys the API to the specified stage.
GraphQLApiDeployment: Type: 'AWS::ApiGateway::Deployment' Properties: RestApiId: !Ref GraphQLApi StageName: v1 DependsOn: - GraphQLApiResource - GraphQLApiMethod
Lambda / API Gateway permission
At this point, we have both the Lambda function and API gateway configured correctly. However, API Gateway needs special permission to invoke a Lambda function. We permit API Gateway to invoke Lambda by creating a Lambda Permission resource.
GraphQLApiPermission: Type: 'AWS::Lambda::Permission' Properties: Action: lambda:invokeFunction FunctionName: !GetAtt LambdaFunction.Arn Principal: apigateway.amazonaws.com SourceArn: !Sub arn:aws:execute-api:${AWS::Region}:${AWS::AccountId}:${GraphQLApi}/*
Finally, we export the API URL at the end of the template. We can use this URL to invoke calls to the Lambda.
Outputs: ApiUrl: Description: Invoke url of API Gateway endpoint Value: !Sub //${GraphQLApi}.execute-api.${AWS::Region}.amazonaws.com/v1/graphql
Deploy CloudFormation stack to AWS
Now that we have the CloudFormation template ready let’s use the AWS CLI command to deploy it to AWS.
Run the following command in your console. Make sure to update the BucketName to whatever the name of the bucket you created earlier is.
aws cloudformation deploy \ --template-file ./cloudformation.yml \ --stack-name apollo-server-lambda-nodejs \ --parameter-overrides BucketName=lambda-deploy-asln Version=latest \ --capabilities CAPABILITY_IAM

It might take some time to deploy the stack. Lambda function should be ready to start taking requests when the deployment finishes.
Verify API Gateway and Lambda are working as expected
Now that we have deployed our CloudFormation Stack let us verify if everything is working as expected. We need the API Gateway URL to send a request to our Lambda Function. The API URL we exported in the CloudFormation template comes in handy here.
Run the following command to print the API URL in the command line.
aws cloudformation describe-stacks \ --stack-name=apollo-server-lambda-nodejs \ --query "Stacks[0].Outputs[?OutputKey=='ApiUrl'].OutputValue" \ --output text

Now, use the curl
command to invoke the API URL. You should get "Hello from Lambda" back from the server.
curl -d '{}' //o55ybz0sc5.execute-api.us-east-1.amazonaws.com/v1/graphql

Add deploy script for easier deployment
You might have noticed that we ran a whole bunch of commands to package and deploy our application. It would be very tedious to have to run those commands every time we deploy the application. Let’s add a bash script to simplify this workflow.
Create a directory called bin
at the root of the application and add a file named deploy
.
mkdir bin touch bin/deploy
Before we can execute the script, we need to set correct file permissions. Let’s do that by running the following command.
chmod +x bin/deploy

At this point, our directory structure should look like in the screenshot below.

Add the following code to the file.
#!/bin/bash set -euo pipefail OUTPUT_DIR=dist CURRENT_DIR=$(pwd) ROOT_DIR="$( dirname "${BASH_SOURCE[0]}" )"/.. APP_VERSION=$(date +%s) STACK_NAME=apollo-server-lambda-nodejs cd $ROOT_DIR echo "cleaning up old build.." [ -d $OUTPUT_DIR ] && rm -rf $OUTPUT_DIR mkdir dist echo "zipping source code.." zip -rq $OUTPUT_DIR/dist-$APP_VERSION.zip src node_modules package.json echo "uploading source code to s3.." aws s3 cp $OUTPUT_DIR/dist-$APP_VERSION.zip s3://$S3_BUCKET/dist-$APP_VERSION.zip echo "deploying application.." aws cloudformation deploy \ --template-file $ROOT_DIR/cloudformation.yml \ --stack-name $STACK_NAME \ --parameter-overrides Version=$APP_VERSION BucketName=$S3_BUCKET \ --capabilities CAPABILITY_IAM # Get the api url from output of cloudformation stack API_URL=$( aws cloudformation describe-stacks \ --stack-name=$STACK_NAME \ --query "Stacks[0].Outputs[?OutputKey=='ApiUrl'].OutputValue" \ --output text ) echo -e "\n$API_URL" cd $CURRENT_DIR
OK, let’s break down what’s going on in this script.
We start by defining some variables. We generate the archive file inside the dist
directory. We set the app version to the current timestamp at which the script runs. Using the timestamp, we can make sure that the version number is always unique and incremental.
#!/bin/bash set -euo pipefail OUTPUT_DIR=dist CURRENT_DIR=$(pwd) ROOT_DIR="$( dirname "${BASH_SOURCE[0]}" )"/.. APP_VERSION=$(date +%s) STACK_NAME=apollo-server-lambda-nodejs
We then clean up any old builds and create a new dist
directory.
echo "cleaning up old build.." [ -d $OUTPUT_DIR ] && rm -rf $OUTPUT_DIR mkdir dist
Then we run the zip command to archive the source code and its dependencies.
echo "zipping source code.." zip -rq $OUTPUT_DIR/dist-$APP_VERSION.zip src node_modules package.json
Next, we copy the zip file to the S3 bucket.
echo "uploading source code to s3.." aws s3 cp $OUTPUT_DIR/dist-$APP_VERSION.zip s3://$S3_BUCKET/dist-$APP_VERSION.zip
Then we deploy the CloudFormation stack.
echo "deploying application.." aws cloudformation deploy \ --template-file $ROOT_DIR/cloudformation.yml \ --stack-name $STACK_NAME \ --parameter-overrides Version=$APP_VERSION BucketName=$S3_BUCKET \ --capabilities CAPABILITY_IAM
Finally, we query the CloudFormation Stack to get the API URL from the CloudFormation Outputs and print it in the console.
# Get the api url from output of cloudformation stack API_URL=$( aws cloudformation describe-stacks \ --stack-name=$STACK_NAME \ --query "Stacks[0].Outputs[?OutputKey=='ApiUrl'].OutputValue" \ --output text ) echo -e "\n$API_URL"
Deploy to AWS using the deploy script
Let’s try out the deployment using the deploy script. The script expects the S3_Bucket variable to be present in the environment. Run the following command to run the deployment. When the deployment is successful, the script will output the API URL that we can use to invoke the lambda.
S3_BUCKET=lambda-deploy-asln ./bin/deploy

To simplify this even further, let’s invoke it using yarn. Add the following in your package.json
.
"scripts": { "deploy": "S3_BUCKET=lambda-deploy-asln ./bin/deploy" }
Hereafter we can simply run yarn deploy
to initiate deployments.
Improve workflow with local Lambda and API Gateway
We frequently modified the application code while working on our application. Right now, deploying to AWS us-east-1 region takes me around 10 seconds. I am on a 40Mb/s upload speed internet connection.
Time to deploy becomes more significant as the size of the application grows. Having to wait 10 seconds or more to realize I have made a syntax error is not productive at all.
Let’s fix this by setting up the lambda function locally and invoke it using a local API Endpoint. AWS SAM CLI enables us to do just that. Follow the instruction on this page to install it.
Once done, from the root of the project, run the following command.
sam local start-api --template-file cloudformation.yml

The local endpoint is now available at //localhost:3000. We can use this endpoint to send requests to our local Lambda.
Open another terminal and run the following command to send a request. You should see the response from our local Lambda function.
curl -d '{}' //localhost:3000/graphql

Finally, add the following lines in the scripts
section of the package.json
.
"dev": "sam local start-api --template-file cloudformation.yml"
Hereafter we can run the yarn dev
command to start the dev server.
Set up the GraphQL server in Lambda
Without further talking, let’s jump right into the code and build the GraphQL server.
Start by installing the dependencies. We are using Apollo Server to build our GraphQL server. Apollo Server is an open-source implementation of GraphQL Server.
yarn add apollo-server-lambda graphql
Replace the content of src/index.js
with the following code.
const { ApolloServer, gql } = require('apollo-server-lambda'); const typeDefs = gql` type Query { user: User } type User { id: ID name: String } `; const resolvers = { Query: { user: () => ({ id: 123, name: 'John Doe' }) } }; const server = new ApolloServer({ typeDefs, resolvers }); exports.handler = server.createHandler();
Here, we define a schema which consists of a type User and a user query. We then define a resolver for the user query. For the sake of simplicity, the resolver returns a hardcoded user. Finally, we create a GraphQL handler and export it.
To perform queries to our GraphQL server, we need a GraphQL client. Insomnia is my favourite client. However, any other GraphQL client should be just fine.
Now, let’s run a query to ensure our server is working as expected.
Create a new GraphQL request in Insomnia.


Add the following query in the body and submit the query to //localhost:3000
. Assuming your dev server is still running, you should see the following response from the GraphQL server.

Now that we've verified everything is working fine in the local server let’s run the following command to deploy the GraphQL server to AWS.
yarn deploy

The API URL is outputted in the console once the deployment is complete. Replace the URL in Insomnia with the one from API Gateway. Rerun the query to see it resolve.

Summary
Congratulations, you have successfully deployed a GraphQL Server in AWS Lambda purely using CloudFormation. The server can receive GraphQL requests from the client and return the response accordingly.
We also set up the development environment for local development without adding many dependencies.
If you liked this tutorial, please share it with your network.