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Sébastien Stormacq
dee635267b
Change Examples, README, and doc to refer to https://github.org/awslabs instead of https://github.org/swift-server --------- Co-authored-by: Sebastien Stormacq <stormacq@amazon.lu>
99 lines
5.1 KiB
Markdown
99 lines
5.1 KiB
Markdown
# List Amazon S3 Buckets with the AWS SDK for Swift
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This is a simple example of an AWS Lambda function that uses the [AWS SDK for Swift](https://github.com/awslabs/aws-sdk-swift) to read data from Amazon S3.
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## Code
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The Lambda function reads all bucket names from your AWS account and returns them as a String.
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The code creates a `LambdaRuntime` struct. In it's simplest form, the initializer takes a function as argument. The function is the handler that will be invoked when the API Gateway receives an HTTP request.
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The handler is `(event: APIGatewayV2Request, context: LambdaContext) -> APIGatewayV2Response`. The function takes two arguments:
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- the event argument is a `APIGatewayV2Request`. It is the parameter passed by the API Gateway. It contains all data passed in the HTTP request and some meta data.
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- the context argument is a `Lambda Context`. It is a description of the runtime context.
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The function must return a `APIGatewayV2Response`.
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`APIGatewayV2Request` and `APIGatewayV2Response` are defined in the [Swift AWS Lambda Events](https://github.com/awslabs/swift-aws-lambda-events) library.
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The handler creates an S3 client and `ListBucketsInput` object. It passes the input object to the client and receives an output response.
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It then extracts the list of bucket names from the output and creates a `\n`-separated list of names, as a `String`
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## Build & Package
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To build the package, type the following commands.
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```bash
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swift build
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swift package archive --allow-network-connections docker
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```
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If there is no error, there is a ZIP file ready to deploy.
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The ZIP file is located at `.build/plugins/AWSLambdaPackager/outputs/AWSLambdaPackager/AWSSDKExample/AWSSDKExample.zip`
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## Deploy
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The deployment must include the Lambda function and an API Gateway. We use the [Serverless Application Model (SAM)](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/what-is-sam.html) to deploy the infrastructure.
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**Prerequisites** : Install the [SAM CLI](https://docs.aws.amazon.com/serverless-application-model/latest/developerguide/install-sam-cli.html)
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The example directory contains a file named `template.yaml` that describes the deployment.
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To actually deploy your Lambda function and create the infrastructure, type the following `sam` command.
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```bash
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sam deploy \
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--resolve-s3 \
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--template-file template.yaml \
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--stack-name AWSSDKExample \
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--capabilities CAPABILITY_IAM
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```
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At the end of the deployment, the script lists the API Gateway endpoint.
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The output is similar to this one.
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```
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-----------------------------------------------------------------------------------------------------------------------------
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Outputs
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-----------------------------------------------------------------------------------------------------------------------------
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Key APIGatewayEndpoint
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Description API Gateway endpoint URL"
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Value https://a5q74es3k2.execute-api.us-east-1.amazonaws.com
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-----------------------------------------------------------------------------------------------------------------------------
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```
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## Invoke your Lambda function
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To invoke the Lambda function, use this `curl` command line.
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```bash
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curl https://a5q74es3k2.execute-api.us-east-1.amazonaws.com
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```
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Be sure to replace the URL with the API Gateway endpoint returned in the previous step.
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This should print text similar to
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```bash
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my_bucket_1
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my_bucket_2
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...
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```
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## Delete the infrastructure
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When done testing, you can delete the infrastructure with this command.
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```bash
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sam delete
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```
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## ⚠️ Security and Reliability Notice
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These are example applications for demonstration purposes. When deploying such infrastructure in production environments, we strongly encourage you to follow these best practices for improved security and resiliency:
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- Enable access logging on API Gateway ([documentation](https://docs.aws.amazon.com/apigateway/latest/developerguide/set-up-logging.html))
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- Ensure that AWS Lambda function is configured for function-level concurrent execution limit ([concurrency documentation](https://docs.aws.amazon.com/lambda/latest/dg/lambda-concurrency.html), [configuration guide](https://docs.aws.amazon.com/lambda/latest/dg/configuration-concurrency.html))
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- Check encryption settings for Lambda environment variables ([documentation](https://docs.aws.amazon.com/lambda/latest/dg/configuration-envvars-encryption.html))
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- Ensure that AWS Lambda function is configured for a Dead Letter Queue (DLQ) ([documentation](https://docs.aws.amazon.com/lambda/latest/dg/invocation-async-retain-records.html#invocation-dlq))
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- Ensure that AWS Lambda function is configured inside a VPC when it needs to access private resources ([documentation](https://docs.aws.amazon.com/lambda/latest/dg/configuration-vpc.html), [code example](https://github.com/awslabs/swift-aws-lambda-runtime/tree/main/Examples/ServiceLifecycle%2BPostgres)) |