monolayer SDK

Appearance

Bucket ​

Workload for AWS S3 compatible storage.

Description ​

With this workload you define AWS S3 compatible storages.

A Bucket workload is initialized with a valid bucket name.

See examples.

Each workload has the ML_AWS_ENDPOINT_URL environment variable name associated with it to hold the endpoint url to connect to development and test environments.

Client ​

You can use any AWS S3 compatible client with the workload, although the AWS SDK for Javascript is recommended.

The client is defined by passing a constructor function when initializing the workload.

You access the client with the client accessor. This accessor will call this client constructor function with the workload's environment variable name and memoize its result.

See examples.

Development environment ​

A docker container for the dev environment is launched with npx monolayer start dev

You can stop it with npx monolayer stop dev.

After the container is started:

  • The ML_AWS_ENDPOINT_URL environment variable with the endpoint URL to the workload's Docker container will be written to .env.
  • The bucket will be created if it does not exist.

See examples on how to configure a client for development.

INFO

Check your framework documentation to see it the .env file is loaded automatically.

Test environment ​

A docker container for the test environment is launched with npx monolayer start test

You can stop it with npx monolayer stop test.

  • The ML_AWS_ENDPOINT_URL environment variable with the endpoint URL to the workload's Docker container will be written to .env.
  • The bucket will be created if it does not exist.

See examples on how to configure a client for test.

INFO

Check your framework documentation to see it the .env.test file is loaded automatically.

Examples ​

ts
import { Bucket } from "@monolayer/sdk";
import { S3Client } from "@aws-sdk/client-s3";

const imagesBucket = new Bucket(
  "workloads-images",
  () =>
    new S3Client({
     // Configure forcePathStyle and endpoint
     // when the dev or test container is running
     ...(process.env.ML_AWS_ENDPOINT_URL
       ? {
           forcePathStyle: true,
           endpoint: process.env.ML_AWS_ENDPOINT_URL,
         }
       : {}),
     // Other configuration options
   }),
);