Triggering Lambda function and processing SQS messages to S3 – Lab 82

Lab 82

Services Covered

•  Lambda
•  S3
•  SQS

Lab description

The purpose of this lab is to create a chain of events. Messages send to a SQS Queue will trigger a Lambda function that will process them and store the output as JSON object to a S3 bucket.

• Create Lambda function
• Create a SQS Queue
• Trigger Lambda function on new messages in the Queue

Lab date

10-10-2021

Prerequisites

• AWS account

Lab steps

1. Create a destination S3 bucket.
2. Create a IAM Role for Lambda, it should allow it execution, access to S3 and SQS

   

3. Create a Lambda function that will process and store messages

   import json
   
   import boto3
   
   def lambda_handler(event, context):
   
      sqs_msg = json.loads(event['Records'][0]['body'])
   
      print("SQS Message : ", sqs_msg)
   
      bucket_name = "<<BUCKET_NAME>>"
   
      try:
   
          s3Client = boto3.client("s3", region_name= "us-east-1")
   
          Response = s3Client.put_object(Bucket= bucket_name, Key= "Message.json", Body= json.dumps(sqs_msg))
   
          print("S3 upload success !")
   
          return {
   
              "status" : 200,
   
              "body" : "S3 upload success"
   
          }
   
      except Exception as e:
   
          print("Client connection to S3 failed because ", e)
   
          return{
   
              "status" : 500,
   
              "body" : "S3 upload failed"
   
          }

4. Create a standard Queue in SQS.
5. In the Lambda Configuration tab go to Triggers and choose the created queue.
6. In SQS send a message to the queue.
   
   It should trigger execution of Lambda function and store that message to S3.

   

Lab files

• lambda.py

Acknowledgements

• Whizlabs