aws-fetch-file-and-store-in-s3

Fetch image from URL then upload to s3 Example

This example display how to fetch an image from remote source (URL) and then upload this image to a S3 bucket.

Use-cases

• Store a user's profile picture from another service.

How it works

We first fetch the data from given url and then call the S3 API putObject to upload it to the bucket.

fetch('image URL')
  .then(res => {
    return s3.putObject({Bucket, Key, Body: res.body}).promise();
  }).then(res => {
    callback(null, res);
  }).catch(err => {
    callback(err, null);
  });

Setup

Since this plugin uses the Serverless plugin serverless-secrets-plugin you need to setup the node_modules by running:

npm install

In addition you need to create an S3 bucket you want to store the files in. After you created the bucket add change the bucket name in serverless.yml custom settings to your buckets.

custom:
  bucket: <your-bucket-name>

Deploy

In order to deploy the you endpoint simply run

serverless deploy

The expected result should be similar to:

Serverless: Creating Stack...
Serverless: Checking Stack create progress...
.....
Serverless: Stack create finished...
Serverless: Packaging service...
Serverless: Uploading CloudFormation file to S3...
Serverless: Uploading service .zip file to S3 (1.8 KB)...
Serverless: Updating Stack...
Serverless: Checking Stack update progress...
................
Serverless: Stack update finished...

Service Information
service: aws-node-fetch-file-and-store-in-s3
stage: dev
region: us-west-1
api keys:
  None
endpoints:
  None
functions:
  aws-node-fetch-file-and-store-in-s3-dev-save: arn:aws:lambda:us-west-1:377024778620:function:aws-node-fetch-file-and-store-in-s3-dev-save

Usage

You can now send an HTTP request directly to the endpoint using a tool like curl

serverless invoke --function save --log --data='{ "image_url": "https://assets-cdn.github.com/images/modules/open_graph/github-mark.png", "key": "github.png"}'

The expected result should be similar to:

"Saved"
--------------------------------------------------------------------
START RequestId: c658859d-bd42-11e6-ac1f-c7a7ee5bd7f3 Version: $LATEST
END RequestId: c658859d-bd42-11e6-ac1f-c7a7ee5bd7f3
REPORT RequestId: c658859d-bd42-11e6-ac1f-c7a7ee5bd7f3	Duration: 436.94 ms	Billed Duration: 500 ms 	Memory Size: 1024 MB	Max Memory Used: 29 MB

Scaling

By default, AWS Lambda limits the total concurrent executions across all functions within a given region to 100. The default limit is a safety limit that protects you from costs due to potential runaway or recursive functions during initial development and testing. To increase this limit above the default, follow the steps in To request a limit increase for concurrent executions.