AWS Lambda

 

What is AWS Lambda?

Let us start with an example: Let us assume you are developing an application and deploy it on a server. The cost of maintaining the server is high; it can be provisioning and scaling of the server or any other activities related to the maintenance of servers. If these activities are automated, then you would save a huge cost and time. That is the concept of serverless, and Lambda is one of the AWS serverless applications. Lambda requires you to just write the code and deploy it; it maintains the server for you.

Serverless does not mean that there is no server. It just mean that you don't have to maintain the server as AWS takes care of it for you.

 

What are the benefits of Lambda?

Apart from the advantages of serverless service, Lambda also provides a facility to code in any Lambda-supported languages. Also, from the pricing side, Lambda will use a pay-for-use model, which means users will be charged only if Lambda is used; otherwise, they are not charged.

What are the downsides of Lambda?

A few disadvantages are limited disk space: its 512 MB. Also, the memory of a Lambda function can be used is 128MB to 3008MB. Another downside is that Lambda functions time out in 15 minutes. That means that if your function has a logic that takes more than 15 minutes, then Lambda is not recommended.

What are the ways of invoking Lambda?

There are three different ways of invoking the Lambda

a. Event-based: We can configure Lambda to be invoked when an event happens. For instance, if users upload a photo, you would require to backup.

b. Schedule-based: We can configure the lambda to be run for every duration of time, such as every month, every fortnight. For example, if you need to do notify your employees every month, then you can use Lambda.

c. Next is to integrate programmatically using API Gateway to invoke your Lambda. To provide you an instance, we can configure a .Net Web API to be deployed to Lamda; when there is a request API Gateway invokes the Lambda.

Let us understand how to create a Lambda.

Demo1: Let us create a Lambda function that sends an email. This Lambda function should be triggered when any user uploads a file to an S3 bucket.

So the steps will be as below:

The first step will be to create an S3 bucket. For the steps to create an S3 bucket, please follow this. The second step should be creating Simple Email Service emails and verifying those emails; you just can't give an email address in the Lambda function so that an email can be sent. The email addresses should be registered with AWS Simple Email Service services and those should be verified. The final step is to create a Lambda function that sends an email and adding a trigger to this Lambda.

a. Create an S3 bucket as in the steps above.

b. For registering emails with AWS Simple Email Service, Navigate to AWS SES service in AWS console and click on 'Email addresses'.

c. Click on 'Verify Email Addresses'.

d. Enter the email address to verify. A notification to verify the email address will be sent to the owner of the email address. After successful verification from the email address's owner, the email address will be verified. Until then, it shows pending verification.

e. We have not created an S3 bucket and added emails in AWS SES services, Next we need to create a Lambda function that sends an email. For that, navigate to the Lambda console.

f. Click on 'Create Function'. Give a name to the Lambda function, and select Phyton 2.7 as the runtime. Click on 'Create Function'

g. Copy and paste below phyton code.

import boto3
	from botocore.exceptions import ClientError
	print('Loading function')
	SENDER = "sender@gmail.com"
	RECIPIENT = "receiver@gmail.com"
	SUBJECT = "Somebody added a photo!"
	BODY_TEXT = "You need to monitor it!"
	AWS_REGION = "us-east-1"
	CHARSET = "UTF-8"
	def lambda_handler(event, context):
	client = boto3.client('ses', region_name=AWS_REGION)
	try:
	response = client.send_email(
	Destination={
	'ToAddresses': [
	RECIPIENT,
	],
	},
	Message={
	'Body': {
	'Text': {
	'Charset': CHARSET,
	'Data': BODY_TEXT,
	},
	},
	'Subject': {
	'Charset': CHARSET,
	'Data': SUBJECT,
	},
	},
	Source=SENDER
	)
	# Error handling
	except ClientError as e:
	print(e.response['Error']['Message'])
	else:
	print("Email sent! Message ID:"),
	print(response['MessageId'])

h. Click on 'Add Trigger'.

i. Select S3 because we need to trigger the Lambda when the user uploads a photo. Select the bucket you would have created as in above steps. 

j. Accept the condition and click add. This adds the trigger. Next, click on 'Deploy'; this deploys the Lambda. 

All steps are complete. When you upload a file to the bucket you would get a notification in the receiver email.