Trigger Lambda function that will resize jpg on an object creation evenets in S3

Lab Details

  1. Services covered
  2. Lab description
  3. Lab date
  4. Prerequisites
  5. Lab steps
  6. Lab files
  7. Acknowledgements

Services Covered

  •  SNS
  • S3 S3
  • lambda Lambda

Lab description

You have been tasked with creating a prototype replacement infrastructure using Amazon Web Services (AWS). Amazon SNS has been chosen because of its flexibility. Your company would like the option of extending the system in the future and have the ability to notify customers when an image has been processed.

Learning Objectives

  • Create a event notification on object creation in S3 bucket
  • Trigger Lambda function with SNS

Lab date



  • AWS account

Lab steps

  1. Create an Amazon SNS Topic. Using the Amazon SNS console, create a topic that satisfies the following:

    Type is Standard
    Access Policy is Basic
    Everyone can publish and subscribe

  2. Create two Amazon S3 buckets.
  3. Notify Amazon SNS when images are uploaded. Using the Amazon S3 console, create an event notification on your uploads-calabs bucket that satisfies the following:

    Notification is triggered by all object creation events and not triggered by any other type of event
    Notification is triggered only by uploaded objects whose name ends with .jpg
    Uses your Amazon SNS topic as the Destination

  4. Create a Lambda function. Use Python as runtime and following code:
    import boto3
    from PIL import Image
    from io import BytesIO
    import json
    import urllib
    upload_bucket_name = "uploads-calabs-xxxxxx"
    resize_bucket_name = "resized-calabs-xxxxxx"
    size = 500, 500
    s3 = boto3.resource('s3')
    def handler(event, context):
       for record in event['Records']:
           print(f'--- processing event record: {record} ---')
           message = json.loads(record['Sns']['Message'])
           for s3_record in message['Records']:
               print(f'--- processing s3 record: {s3_record} ---')
               key = urllib.parse.unquote_plus(s3_record['s3']['object']['key'])
               print(f'--- {key} image was uploaded to {upload_bucket_name} ---')
               upload_file = BytesIO()
               s3.Bucket(upload_bucket_name).download_fileobj(key, upload_file)
               print(f'--- downloaded {key} image from {upload_bucket_name} bucket to in memory file ---')
               image =
               image = image.resize(size)
               resize_file = BytesIO()
     , format='JPEG')
               print(f'--- resized {key} image to {size} ---')
               s3.Object(resize_bucket_name, key).put(Body=resize_file.getvalue())
               print(f'--- uploaded {key} file to {resize_bucket_name} bucket ---')

    Change the bucket names and set the timeout to 3 minutes and 256 MB memory limit.

  5. Subscribe the image resizing AWS Lambda function to your Amazon SNS topic. Using the Amazon SNS console, create a subscription for your topic that satisfies the following:

    Uses the AWS Lambda Protocol
    Subscription Endpoint set to the AWS Lambda function that you created in previous step (manually copy it from the Lambda console if it doesn’t show up)

  6. Upload an image file to the uploads bucket. I uploaded three files that were > 1MB and in result the resized files in resized bucket are much smaller:

Lab files