Deploy to AWS

The function deploys as a container image. The Amazon.Lambda.Tools CLI builds the image, pushes it to Amazon ECR and creates or updates the function in one go.

1. Install the CLI.

   dotnet tool install -g Amazon.Lambda.Tools

2. Fill in src/Presentation/aws-lambda-tools-defaults.json. The template leaves profile and region empty on purpose. We don’t know where you live.

   {
     "profile": "default",
     "region": "ap-southeast-2",
     "configuration": "Release",
     "package-type": "image",
     "function-memory-size": 256,
     "function-timeout": 30,
     "image-command": "Presentation::Acme.Reviews.Presentation.LambdaFunction.Handler::GetMovies"
   }

3. Deploy.

   dotnet lambda deploy-function --project-location ./src/Presentation

   The CLI asks for a function name and an IAM role the first time.

4. Invoke it for real.

   aws lambda invoke --function-name acme-reviews-get-movies \
     --cli-binary-format raw-in-base64-out --payload '{"limit":5}' response.json

One image, many functions

Each Lambda function runs one handler method. To deploy GetAuthors and GetReviews as well, deploy the same image again with a different image-command and function name. They share the code but scale and bill separately.

Tip

Remember the goldfish: each deployed function has its own /tmp database. Seed it, or better, point it at a real database before anyone relies on the data.

Settings worth a look

Setting	Template default	Why you might change it
function-memory-size	256 MB	Lambda gives you CPU in proportion to memory, so more memory often means a faster cold start
function-timeout	30 seconds	The handler stops its work when the invocation is about to run out of time, so set this to what your callers will wait for