Running using the AWS serverless stack

Tapir server endpoints can be packaged and deployed as an AWS Lambda function. This approach, known as the Fat Lambda function, utilizes a single lambda function for deploying multiple endpoints. To invoke the function, HTTP requests can be proxied through AWS API Gateway.

To configure API Gateway routes, and the Lambda function, tools like AWS SAM , AWS CDK or Terraform can be used, to automate cloud deployments.

For an overview of how this works in more detail, see this blog post .

Runtime & Server interpreters

Tapir supports three of the AWS Lambda runtimes: custom runtime, Java, and NodeJS. Below you have a list of classes that can be used as an entry point to your Lambda application depending on runtime of your choice. Each one of them uses server interpreter, which responsibility is to transform Tapir endpoints with associated server logic to function like AwsRequest => F[AwsResponse] in case of custom and Java runtime, or AwsJsRequest => Future[AwsJsResponse] in case of NodeJS runtime. Currently, two server interpreters are available, the first one is using cats-effect (AwsCatsEffectServerInterpreter), and the other one is using Scala Future (AwsFutureServerInterpreter). Custom runtime, and Java runtime are using only cats-effect interpreter, where NodeJS runtime can be used with both interpreters. These are corresponding classes for each of the supported runtime:

  • The AwsLambdaIORuntime for custom runtime. Implement the Lambda loop of reading the next request, computing and sending the response through Lambda runtime API.

  • The LambdaHandler for Java runtime, which utilizes RequestStreamHandler interface for handling requests, response flow inside Java runtime.

  • The AwsJsRouteHandler for NodeJS runtime. The main benefit is the reduced deployment time. Initialization of JVM-based application ( with sam local) took ~11 seconds on average, while Node.js based one only ~2 seconds.

To start using any of the above add the following dependency:

"com.softwaremill.sttp.tapir" %% "tapir-aws-lambda" % "1.9.4"


To make it possible, to call your endpoints, you will need to deploy your application to Lambda, and configure Amazon API Gateway. Tapir leverages ways of doing it provided by AWS, you can choose from: AWS SAM template file, terraform configuration, and AWS CDK.

You can start by adding one of the following dependencies to your project, and then follow examples:

"com.softwaremill.sttp.tapir" %% "tapir-aws-sam" % "1.9.4"
"com.softwaremill.sttp.tapir" %% "tapir-aws-terraform" % "1.9.4"
"com.softwaremill.sttp.tapir" %% "tapir-aws-cdk" % "1.9.4"


Go ahead and clone tapir project. To deploy you application to AWS you will need to have an AWS account and AWS command line tools installed.


SAM can be deployed using Java runtime or NodeJS runtime. For each of these cases first you will have to install AWS SAM command line tool, and create a S3 bucket, that will be used during deployment. Before going further, open sbt shell, as it will be needed for both runtimes.

For Java runtime, use sbt to run assembly task, and then runMain, this will generate template.yaml sam file in main directory

For NodeJS runtime, first generate AWS Lambda yaml file by execution inside sbt shell command awsExamples/runMain, and then build Node.js module with awsExamplesJS/fastLinkJS, it will create all-in-one JS file under tapir/serverless/aws/examples/target/js-2.13/tapir-aws-examples-fastopt/main.js

From now the steps for both runtimes are the same:

  1. Before deploying, if you want to test your application locally, you will need Docker. Execute sam local start-api --warm-containers EAGER, there will be a link displayed at the console output

  2. To deploy it to AWS, run sam deploy --template-file template.yaml --stack-name sam-app --capabilities CAPABILITY_IAM --s3-bucket [name of your bucket]. The console output should print url of the application, just add /api/hello to the end of it, and you should see Hello! message. Be aware in case of Java runtime, the first call can take a little longer as the application takes some time to start, but consecutive calls will be much faster.

  3. When you want to rollback changes made on AWS, run sam delete --stack-name sam-app


Terraform deployment requires you to have a S3 bucket.

  1. Install Terraform

  2. Run assembly task inside sbt shell

  3. Open a terminal in tapir/serverless/aws/examples/target/jvm-2.13 directory. That’s where the fat jar is saved. You need to upload it into your s3 bucket. Using command line tools: aws s3 cp tapir-aws-examples.jar s3://{your-bucket}/{your-key}.

  4. Run runMain {your-aws-region} {your-bucket} {your-key} inside sbt shell

  5. Open terminal in tapir root directory, run terraform init and terraform apply

That will create configuration and deploy Api Gateway and lambda function to AWS. Terraform will output the url of the created API Gateway which you can call followed by /api/hello path.

To destroy all the created resources run terraform destroy.


  1. First you need to install:

  2. Open sbt shell, then run assembly task, and execute runMain to generate CDK application template under cdk directory

  3. Go to cdk and run npm install, it will create all files needed for the deployment

  4. Before deploying, if you want to test your application locally, you will need Docker and AWS SAM command line tool , then execute cdk synth, and sam local start-api -t cdk.out/TapirCdkStack.template.json --warm-containers EAGER

  5. To deploy it to AWS simply run cdk deploy

  6. When you want to rollback changes made on AWS, run cdk destroy