Working with API Gateway HTTP API type, Lambda Function, and SQS Queue

In this article, I will show you on how the API Gateway HTTP API type, triggers a Lambda function to send a message with the current time to the SQS queue created with Python and boto3.

This function then returns that message back to API Gateway so we can see it.

AWS Lambda is a serverless, event-driven compute service that lets you run code for virtually any type of application or back-end service without provisioning or managing servers. You can trigger Lambda from over 200 AWS services and only pay for what you use.

Let’s get started!

Objectives:

Create a Standard SQS Queue using Python.
Create a Lambda function in the console with a Python 3.7 or higher runtime.
Modify the Lambda to send a message to the SQS queue and to test the function.

The message should contain the current time. Use the built-in test function for testing.

Create an API Gateway HTTP API type trigger for the lambda.
Test the trigger to verify the message was sent.
Finally, we will check out the SQS queue to see that it is receiving messages from Lambda.
Check out your Logs in CloudWatch.

Pre-requisites:

AWS user account with admin access, not a root account.
IDE of your liking with AWS CLI, Python, and boto3 installed.

I am using Cloud9, had to install boto3 on Cloud9 because it did not have it.

pip3 install boto3

For this article, I used boto3 documentation.

You can find the complete code on my GitHub Repository.

Create a standard queue in AWS SQS using Python

Here is the python and boto3 script with a (.py extension) to create AWS Standard SQS Queue on Cloud9.

python create_sqs_queue.py

The output will give you a URL.

Here is the link to my code for create_sqs_queue.py

# --- boto3_python_projects/trigger_api_lambda_sqs/create_sqs_queue.py ---

# Create a Standard SQS Queue using Python


# AWS Python SDK
import boto3


# A low-level client representing Amazon Elastic Compute Cloud (SQS)
sqs_client=boto3.client("sqs")


# use Amazon service sqs
sqs_resource = boto3.resource('sqs')


# Queue will be created 
sqs_queue = sqs_resource.create_queue(QueueName='time_queue')



# prints the output - Standard Queue url
print('Standard Queue created. Queue URL: ' + sqs_queue.url)

Check Amazon SQS on AWS Console to see that the Queue was created.

Click on the queue — time_queue
Note down SQS ARN and SQS URL

Create a Lambda Function with Python

Now I will create a Lambda function that will send a message to the SQS queue I just created.

In the AWS console, navigate to Lambda.

Click Create function.

Select Author from scratch
Name your function — lambda_sqs
Select Python 3.9 from Runtime from drop-down
Click change default execution role to see - create a new role with basic lambda permissions
Click Create function.

Configuring the Role with proper policies/permissions is the key issue here adhering to the principle of least privilege, just so that it can access proper AWS resources for sending out the message.

Once the Lambda function has been successfully created, navigate to the Lambda function

Click on the function — lambda_sqs

On the Function overview

Click Configuration/Permissions
Click the newly created IAM role -> lambda_sqs-role

You will now come to IAM Console.

Click Add Permissions
Click Attach policies to add additional permissions

You will now come to the screen as shown below:

Click in the Current permission policies
Click on the + sign of the AWSLambdaBasicExecutionRole - to see the current permissions

Click Edit to add the following permissions
Click on the JSON tab to view

Add “sqs:SendMessage” to send message to SQS in the Action element.
Add the ARN of the SQS queue in the Resource element.

This is what it looks like in the end after adding permissions.

- Review policy
- Save changes

Here is the link to my code for AWSLambdaBasicExecutionRole.json

# --- boto3_python_projects/trigger_api_lambda_sqs/AWSLambdaBasicExecutionRole.json ---

{
    "Version": "2012-10-17",
    "Statement": [
        {
            "Effect": "Allow",
            "Action": [
                "logs:CreateLogGroup",
                "sqs:SendMessage"
                ],
            "Resource": [
                "arn:aws:logs:us-east-1:xxxxxxxxxxxx:*",
                "arn:aws:sqs:us-east-1:xxxxxxxxxxxx:time_queue"
                ]
        },
        {
            "Effect": "Allow",
            "Action": [
                "logs:CreateLogStream",
                "logs:PutLogEvents"
            ],
            "Resource": [
                "arn:aws:logs:us-east-1:xxxxxxxxxxxx:log-group:/aws/lambda/lambda_sqs:*"
            ]
        }
    ]
}

Modify lambda to send a message to SQS queue and to test the function

Navigate back to Lambda

Click Code
Add the following code to Code source of your Lambda function.
Change the QueueURL to the URL for your SQS queue that you created in the first step.

This will send a message to SQS that contains the current time — time_date

Here is the link to my code for lambda_sendmsg_sqs.py

# --- boto3_python_projects/trigger_api_lambda_sqs/lambda_sendmsg_sqs.py ---
import json
import boto3
from datetime import datetime


def lambda_handler(event, context):
    now = datetime.now()
    time_date = now.strftime("%H:%M:%S %m/%d/%Y")
    sqs = boto3.client('sqs')
    sqs.send_message(QueueUrl="https://sqs.us-east-1.amazonaws.com/xxxxxxxxxxxx/time_queue",MessageBody=time_date)

    return {
        'statusCode': 200,
        'body': json.dumps('Message sent Successfully!')

    }