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examples/lb3-express

This example shows how to use the serverless framework to run loopback3 (with express) in AWS Lambda.

Overview

A RDS (MySQL) database is created, along with all necessary virtual AWS infrastructure (VPC, subnets, DBSubnetGroup) to connect a lambda function running loopback to the MySQL database. The MySQL connection parameters are retrieved from lambda environment variables.

Check out this article for a more in-depth explanation of this sample.

About Sample Provided

The sample loopback application provided was created by following the process below:

  1. Using the command npm run lb and selecting:
  • What kind of application do you have in mind? api-server (A LoopBack API server with local User auth)

  1. Adding a new MySQL database to lib/server/datasources.json.

  2. Adding the CoffeeShop model and initializing it with data:

  • lib/common/coffee-shop.json: CoffeeShop model definition
  • lib/server/model-config.json: add CoffeeShop model so it can be loaded
  • lib/server/boot/create-sample-models.js: initialize CoffeeShop model with data

Customizing & Deploying This Sample

The following steps can be used to customize this sample to your needs and then deploy:

  1. Create your own loopback models with the command npm run lb-model

  2. The RDS mySqlDb in serverless.yml is configured to be as low cost as possible (not suitable for production!) so feel free to customize it to your needs.

  3. Deploy your project to AWS using the command npm run sls-deploy

  4. From the serverless Stack Outputs, retrieve LoopbackApiExplorer to access the loopback4 API explorer (it should look something like https://API_GATEWAY_ID.execute-api.AWS_REGION.amazonaws.com/SERVERLESS_STAGE/api/explorer/). You should end up with an URL similar to https://XXXXXXXXXX.execute-api.us-east-1.amazonaws.com/dev/api/explorer/.

Note: An error might be observed the first time lambda runs after (re-)creating the RDS database as the CoffeeTable model table might not be initialized before your API is invoked. This error would look something like:

{
    "error": {
        "statusCode": 500,
        "name": "Error",
        "message": "ER_NO_SUCH_TABLE: Table 'MY_TEST_DB.CoffeeShop' doesn't exist",
        "code": "ER_NO_SUCH_TABLE",
        "errno": 1146,
        "sqlMessage": "Table 'MY_TEST_DB.CoffeeShop' doesn't exist",
        "sqlState": "42S02",
        "index": 0,
        "sql": "SELECT count(*) as \"cnt\" FROM `CoffeeShop` ",
        "stack": "Error: ER_NO_SUCH_TABLE: Table 'MY_TEST_DB.CoffeeShop' doesn't exist\n    at ..."
    }
}

Retry after a few seconds and it all should work.

Cleaning Up The Sample

Once you are done with the sample environment, avoid unnecessary AWS charges by removing your serverless deployment with the command npm run sls-cleanup.

If you run into a cleanup error similar to the one below, you will need to manually remove the CloudFormation stack by going to: https://console.aws.amazon.com/cloudformation or using the aws-cli.

Serverless Error ---------------------------------------

  An error occurred: mySubnet2 - The subnet 'subnet-077e0f72824fe5dd3' has dependencies and cannot be deleted. (Service: AmazonEC2; Status Code: 400; Error Code: DependencyViolation; Request ID: XXX).

License

MIT © BotBitsSM