Prerequisites:
- AWS CLI (See: AWS CLI installation).
- Docker (See: Docker installation).
- No other experience (we'll guide you through step-by-step).
Full Working Example:
Programming Language & Frameworks:
- We'll use Node.js in this tutorial, but the examples can be adapted to any AWS Lambda-supported language, such as Python, Ruby, Java, C#, Go and even PHP.
- We'll avoid third-party ImageMagick wrappers to make the examples more portable.
Part 1: Creating the AWS Lambda Boilerplate
If you already have an AWS Lambda function, you can skip forward to "part 2".
Otherwise, let's create our skeletal Lambda function...
1) Creating the AWS S3 Buckets
First, we'll create a CloudFormation stack for the S3 buckets we need:
buckets-cloudformation.yml:
Resources:
# Contains our Lambda Function's code.
LambdaFunctionCodeBucket:
Type: 'AWS::S3::Bucket'
Properties:
BucketName: my-lambda-function-code
# Contains our images/photos.
ImageBucket:
Type: 'AWS::S3::Bucket'
Properties:
BucketName: my-images
Remember: replace my-lambda-function-code and my-images with unique bucket names.
Next, we'll create the stack:
aws cloudformation create-stack \
--stack-name my-buckets \
--template-body file://buckets-cloudformation.yml
2) Creating the AWS Lambda Function
To create a basic Lambda function, create the following files:
function.js:
module.exports.invoke = async () => {
return "This will be your resized image...";
}
function-cloudformation.yml:
Resources:
LambdaFunction:
Type: 'AWS::Lambda::Function'
Properties:
FunctionName: AwsLambdaImageResizeExample
Handler: function.invoke
Runtime: nodejs14.x
Role: !GetAtt LambdaFunctionRole.Arn
MemorySize: 1024
Code:
S3Bucket: my-lambda-function-code # <--- CHANGE ME
S3Key: AwsLambdaImageResizeExample.zip
LambdaFunctionRole:
Type: AWS::IAM::Role
Properties:
AssumeRolePolicyDocument:
Version: '2012-10-17'
Statement:
- Effect: Allow
Principal:
Service:
- lambda.amazonaws.com
Action:
- sts:AssumeRole
Path: "/"
Policies:
- PolicyName: AppendToLogsPolicy
PolicyDocument:
Version: '2012-10-17'
Statement:
- Effect: Allow
Action:
- logs:CreateLogGroup
- logs:CreateLogStream
- logs:PutLogEvents
Resource: "*"
- PolicyName: S3FullAccessPolicy
PolicyDocument:
Version: '2012-10-17'
Statement:
- Effect: Allow
Action: s3:*
Resource:
- arn:aws:s3:::my-images # <--- CHANGE ME
- arn:aws:s3:::my-images/* # <--- CHANGE ME
Remember: replace my-lambda-function-code and my-images with your unique bucket names.
ZIP the function code:
zip -ry function-dist.zip .
Upload the ZIP file to S3:
aws s3 cp function-dist.zip s3://my-lambda-function-code/AwsLambdaImageResizeExample.zip
Deploy the stack:
aws cloudformation create-stack \
--stack-name my-image-resize-lambda \
--template-body file://function-cloudformation.yml \
--capabilities CAPABILITY_NAMED_IAM
Check the status of the deployment:
aws cloudformation describe-stack-events \
--stack-name my-image-resize-lambda
Important: the latest event should say "ResourceStatus": "CREATE_COMPLETE".
4) Invoking the AWS Lambda Function
Test the Lambda function we just created:
aws lambda invoke \
--function-name AwsLambdaImageResizeExample \
function-result.json
Now print the function's output:
cat function-result.jsonIt should read:
"This will be your resized image..."Note: we've used the AWS CLI to invoke our Lambda function. To invoke via HTTP, you'll need to create a AWS::ApiGatewayV2::Integration – there are many tutorials for this online – just search around!
Part 2: Calling ImageMagick from AWS Lambda
If you've been following part 1, your working directory will now contain the following:
/
buckets-cloudformation.yml
function.js
function-cloudformation.yml
function-dist.zip
function-result.json
Now we'll install /imagemagick as a subdirectory...
1) Installing ImageMagick on AWS Lambda
Firstly, please complete our tutorial on building ImageMagick for Amazon Linux 2.
On completing this tutorial, you'll have an ImageMagick directory containing the following:
bash-4.2# ls -la
total 28
drwxr-xr-x 7 root root 4096 May 2 11:04 .
dr-xr-x--- 1 root root 4096 May 2 11:04 ..
drwxr-xr-x 2 root root 4096 May 2 11:04 bin
drwxr-xr-x 3 root root 4096 May 2 11:04 etc
drwxr-xr-x 3 root root 4096 May 2 11:04 include
drwxr-xr-x 4 root root 4096 May 2 11:04 lib
drwxr-xr-x 3 root root 4096 May 2 11:04 share
Move this entire directory to /imagemagick, giving you:
/
imagemagick/
bin/
etc/
include/
lib/
share/
buckets-cloudformation.yml
function.js
function-cloudformation.yml
function-dist.zip
function-result.json
2) Installing the S3 Client on AWS Lambda
Before we start resizing images, we'll need to install @aws-sdk/client-s3 on our Lambda function.
This is so we can download the original photos from AWS S3 to generate image thumbnails for them on request:
npm install @aws-sdk/client-s3@3
3) Writing the AWS Lambda Image Resize Code
To start resizing images on our AWS Lambda function, we'll need update our code to the following:
function.js:
const { execFile } = require("child_process");
const { S3 } = require("@aws-sdk/client-s3");
const fs = require("fs");
const path = require("path");
const localFile = path.resolve("/tmp/original-image.jpg");
const s3 = new S3();
const s3Key = "original-image.jpg";
//
// Remember to change this!
//
const imageBucketName = "my-images"
module.exports.invoke = async () => {
await downloadFile(s3Key, localFile);
await resizeImage(localFile);
return await sendFileAsResponse(localFile);
}
async function downloadFile(s3Key, localFile) {
const image = await s3.getObject({
Bucket: imageBucketName,
Key: s3Key
});
await new Promise((resolve, reject) => {
const writer = fs.createWriteStream(localFile);
writer.on("close", resolve);
writer.on("error", reject);
image.Body.pipe(writer);
});
}
async function resizeImage(localFile) {
await new Promise((resolve, reject) => {
execFile(
path.resolve("imagemagick/bin/magick"),
[
localFile,
"-resize",
"100x100",
localFile
],
(error, stdout, stderr) => {
if (error !== null) {
reject(error);
} else {
resolve();
}
}
);
});
}
async function sendFileAsResponse(localFile) {
return {
isBase64Encoded: true,
statusCode: 200,
headers: { "content-type": "image/jpg"},
body: (await fs.promises.readFile(localFile)).toString('base64')
}
}Now redeploy the function:
zip -ry function-dist.zip .
aws s3 cp \
function-dist.zip \
s3://my-lambda-function-code/AwsLambdaImageResizeExample.zip
aws lambda update-function-code \
--function-name AwsLambdaImageResizeExample \
--s3-bucket my-lambda-function-code \
--s3-key AwsLambdaImageResizeExample.zip
4) Try It Out!
Firstly, upload a test image:
aws s3 cp original-image.jpg s3://my-images/original-image.jpg
Finally, resize the image using the AWS Lambda function:
aws lambda invoke \
--function-name AwsLambdaImageResizeExample \
function-result.json
Now print the result:
cat function-result.jsonYou'll see your resized image, base64-encoded in the body field:
{
"isBase64Encoded": true,
"statusCode": 200,
"headers": {
"content-type": "image/jpg"
},
"body": "/9j/4AAQSkZJRg...9k="
}This is because AWS Lambda only supports JSON responses: to return the raw image, you need to put API Gateway in front of the Lambda function.
AWS Lambda Image Resize Example – Code Repository
See a full working example of running ImageMagick on AWS Lambda to resize images below:
https://github.com/upload-io/aws-lambda-image-magick-resize-example
Final Thoughts
To summarise, we've managed to build our own AWS image processing service by:
- Creating an AWS Lambda function.
- Installing ImageMagick on it.
- Uploading an image/photo to S3.
- Using ImageMagick to resize the image (within the Lambda function).
- Returning the resized image as a base64-encoded JSON response.
The crux of this tutorial has been building a standalone ImageMagick binary that's compatible with Amazon Linux, and uploading it as part of the Lambda function's ZIP file. Once you've done this, you can simply exec the ImageMagick binary from within your Lambda function.
We hope you've enjoyed this tutorial on AWS Lambda image processing, and look forward to having you back again soon!
