S3

The S3 template provides a simple means for an application to store and access files on AWS S3. This template is set up for deploying an S3 bucket using Terraform and provides a simple TypeScript API to work with this bucket.

• S3 bucket defined in Terraform
• Supports definition for multiple environments (staging, production)
• Infrastructure easily stood up using an npm script yarn infra up
• Embed in server applications by linking to the package

import { getBucketName, connect } from 'my-s3-module';

const s3 = connect();
await s3.putObject({
  BucketName: getBucketName(),
  Key: 'my-doc',
  Body: 'content',
});

In order to provide a basic configuration for an S3 bucket, we only need to know the name of the bucket you want to create.

Please note that a bucket name needs to be globally unique. However, buckets are always created in a specific AWS region. The bucket will be deployed to the AWS region you have specified.

yarn infra up [deploymentName]

3. Development

This is how an the S3 package can be used from another package:

import { getBucketName, connect } from 'my-s3-module';

const s3 = connect();
await s3.putObject({
  BucketName: getBucketName(),
  Key: 'my-doc',
  Body: 'content',
});

The object returned from connect() is an instance of the AWS S3 client.

Note it is also possible to add additional TypeScript files in the templates src/ folder. This is a good place to put an abstraction layer on top of the S3 interface, for instance a data repository specific to the needs of your application.

All infrastructure for this module is defined in Terraform. You can find the Terraform files for this template in the directory [moduleDir]/infra/aws. You can define multiple deployments for this template, for instance for development, staging and production environments.

If you configured AWS deployment before downloading your project, the deployments and their respective configurations are defined in [moduleDir]/goldstack.json.

The configuration tool will define one deployment. This will be either dev or prod depending on your choice during project configuration. In the example goldstack.json below, a deployment with the name dev is defined.

{
  "$schema": "./schemas/package.schema.json",
  "name": "...",
  "template": "...",
  "templateVersion": "...",
  "configuration": {},
  "deployments": [
    {
      "name": "dev",
      "awsRegion": "us-west-2",
      "awsUser": "awsUser",
      "configuration": {
        ...
      }
    }
  ]
}

Infrastructure Commands

Infrastructure commands for this template can be run using yarn. There are four commands in total:

• yarn infra up: For standing up infrastructure.
• yarn infra init: For initialising Terraform.
• yarn infra plan: For running Terraform plan.
• yarn infra apply: For running Terraform apply.
• yarn infra destroy: For destroying all infrastructure using Terraform destroy.
• yarn infra upgrade: For upgrading the Terraform versions (supported by the template). To upgrade to an arbitrary version, use yarn infra terraform.
• yarn infra terraform: For running arbitrary Terraform commands.

For each command, the deployment they should be applied to must be specified.

yarn infra [command] [deploymentName]

For instance, to stand up the infrastructure for the dev deployment, the following command would need to be issued:

yarn infra up dev

Generally you will only need to run yarn infra up. However, if you are familiar with Terraform and want more fine-grained control over the deployment of your infrastructure, you can also use the other commands as required.

Note that for running yarn infra terraform, you will need to specify which command line arguments you want to provide to Terraform. By default, no extra arguments are provided:

yarn infra terraform [deployment] plan

If extra arguments are needed, such as variables, you can use the --inject-variables option, such as for running terraform plan:

yarn infra terraform [deployment] --inject-variables plan

If you want to interact with the remote backend, you can also provide the --inject-backend-config option, such as for running terraform init:

yarn infra terraform [deployment] --inject-backend-config init

Customizing Terraform

Goldstack templates make it very easy to customize infrastructure to your specific needs. The easiest way to do this is to simply edit the *.tf files in the infra/aws folder. You can make the changes you need and then run yarn infra up [deploymentName] to apply the changes.

The infra/aws folder contains a file variables.tf that contains the variables required for your deployment; for instance the domain name for a website. The values for these variables are defined in the module's goldstack.json file in the "configuration" property. There is one global configuration property that applies for all deployments and each deployment also has its own configuration property. In order to add a new variable, add the variable to variables.tf and then add it to the configuration for your template or to the configurations for the deployments.

Note that due to JavaScript and Terraform using different conventions for naming variables, Goldstack applies a basic transformation to variable names. Camel-case variables names are converted to valid variables names for Terraform by replacing every instance of a capital letter C with _c in the variable name. For instance:

myVariableName in the Goldstack configuration will translate to the Terraform variable my_variable_name as defined in variables.tf.

Terraform State

In order to manage your infrastructure, Terraform maintains a state for each deployment; to calculate required changes when the infrastructure is updated and also for destroying the infrastructure if it is no longer required. Goldstack by default will store the terraform state in the infra/aws folder as simple files.

This works well for deploying infrastructure from your local development environment but is not a good choice when building a CI/CD pipeline for the infrastructure definition. In that case, it is better to define Remote State. A popular choice many projects adopt here is to store the state in an S3 bucket. Please see the Terraform documentation for further details.