README.md

Steps

Set up your Python virtual environment

python3 -m venv venv

Create an AWS S3 bucket to hold artifacts you're deploying to Lambda

This step requires that you have an authenticated aws client in place that can run the aws command.

./0-create-bucket.sh

The output of this is a file called bucket-name.txt which will contain a temporary bucket where deploy artifacts are staged.

Install Python Modules

./1-build.layer.sh

Deploy your Lambda

Create a file called .env in the root directory with this content, substituting your Neo4j Aura values:

export NEO4J_PASSWORD=mySecretPassword
export NEO4J_URI=neo4j+s://dbid.databases.neo4j.io
export NEO4J_USERNAME=neo4j

That file must be created for the deploy to work, as these environment variables will be provided to the lambda.

Next, deploy the lambda like so:

./2-deploy.sh

Sample output:

$ ./2-deploy.sh 
Uploading to 3d20b9c7d47cbd54fea7edc2309757d1  11228394 / 11228394.0  (100.00%)
Successfully packaged artifacts and wrote output template to file out.yml.
Execute the following command to deploy the packaged template
aws cloudformation deploy --template-file /Users/username/aura-lambda/out.yml --stack-name <YOUR STACK NAME>

Waiting for changeset to be created..
Waiting for stack create/update to complete
Successfully created/updated stack - aura-lambda

Invoke the Function

./3-invoke.sh

This will in a loop, every 2 seconds, submit the sample event (event.json) to the lambda function.

This is what successful output looks like:

$ ./3-invoke.sh 
{
    "StatusCode": 200,
    "ExecutedVersion": "$LATEST"
}
{"TotalCodeSize": 9970732198, "FunctionCount": 90}
{
    "StatusCode": 200,
    "ExecutedVersion": "$LATEST"
}

If all goes well, you will start to see records appear in your Neo4j Aura instance!

Cleanup

When you're finished, to delete all resources associated with this sample function:

./4-cleanup.sh