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Getting Started with AWS Lambda: A Step-by-Step Implementation Guide with Examples


Hello, here I’ll be taking an introductory look at AWS Lambda. AWS Lambda is a serverless computing service that’s designed to allow you to run your application code without having to provision or manage your own EC2 instances.


So to really understand serverless computers, you must first understand servers. For example, consider all the work that goes into running an EC2 instance: you have to install software, patch the instance, manage scaling and high availability, configure storage, and only after all that is done can you then write your application code and deploy it to the instance.


Now imagine if that infrastructure maintenance and administration went away, enabling you to focus entirely on your code and business logic. That’s the idea behind serverless. Now of course, this maintenance and server administration still exists behind the scenes; however, it’s no longer your job to do it - instead, it becomes the service’s responsibility and is managed by AWS.



Introduction to AWS Lambda

AWS Lambda is a serverless computing service offered by Amazon Web Services (AWS). It allows developers to run code without provisioning or managing servers. With Lambda, you can execute code in response to events and triggers, such as changes to data in Amazon S3, updates to a DynamoDB table, or HTTP requests via API Gateway. This blog will walk you through the process of setting up and using AWS Lambda, along with practical examples to demonstrate its capabilities.

Step 1: Setting Up AWS Lambda

1.1 AWS Account and IAM Role

Before you can use AWS Lambda, you'll need an AWS account. Once you have an account, it's best practice to set up an IAM (Identity and Access Management) role with the necessary permissions for Lambda. This role will determine what actions Lambda can perform on your behalf.

1.2 AWS Lambda Console

To create and manage Lambda functions, you can use the AWS Management Console. Sign in to your AWS account and navigate to the Lambda service.

Step 2: Creating a Lambda Function

2.1 Function Configuration

Click on the "Create function" button to start creating a new Lambda function. You'll be prompted to choose a blueprint or create a function from scratch. For this example, we'll choose the "Author from scratch" option.

Give your function a name, choose the runtime environment (e.g., Node.js, Python, Java, etc.), and select the IAM role you created in Step 1.2.

2.2 Function Code

Now it's time to write the code for your Lambda function. The code should be written in the runtime language you selected in the previous step. Here's an example of a simple Lambda function written in Node.js:

```javascript

exports.handler = async (event, context) => {

// Your code logic here

const response = {

statusCode: 200,

body: JSON.stringify('Hello from AWS Lambda!'),

};

return response;

};

```

2.3 Function Triggers

After writing the code, you can configure triggers for your Lambda function. As mentioned earlier, triggers can be events like changes to an S3 bucket or API Gateway requests. For demonstration purposes, let's set up an HTTP trigger using API Gateway.

Step 3: Configuring API Gateway Trigger

3.1 Create an API

Go to the AWS API Gateway service and create a new API. Choose the REST API option and give it a name.

3.2 Create a Resource and Method

Once the API is created, create a resource and a method under that resource. For example, create a resource with the path "/hello" and add a GET method to it.

3.3 Configure Integration with Lambda

In the method configuration, set up the integration type as Lambda Function and choose the Lambda function you created in Step 2.

3.4 Deploy the API

After configuring the integration, deploy the API to obtain an endpoint URL. This URL will trigger the Lambda function whenever an HTTP GET request is made to it.

Step 4: Testing the Lambda Function

Now that everything is set up, it's time to test your Lambda function. You can use the Lambda console to test the function or make an HTTP GET request to the API Gateway endpoint. If the function runs successfully, you should receive a response with a "Hello from AWS Lambda!" message.


Risks of not monitoring Lambda costs properly

Properly monitoring AWS Lambda costs is crucial to avoid potential risks and financial challenges. Failing to do so can lead to various negative outcomes.


Firstly, without effective monitoring, managing your AWS bill can become overwhelming and difficult. It is common for manual calculators to lose control, resulting in unexpected costs and budget overruns. This lack of control can be compared to a runaway truck, as the costs can quickly spiral out of hand.


Secondly, while Lambda is often chosen for its potential cost savings and operational ease, using it indiscriminately may not always result in desirable cost reductions. Without proper optimization of AWS costs, organizations may not fully benefit from the potential savings or achieve a higher return on investment (ROI). It is essential to know how to optimize costs efficiently to achieve the desired outcomes.


Thirdly, many available cost optimization tools often rely heavily on tagging, making them clunky, complex, and insufficient in providing actionable insights. These tools may lack the ability to map costs to specific unit costs, such as cost per customer, which is crucial for informed decision-making. Failing to understand the impact of work on Lambda costs can have repercussions on an organization’s ability to price products or services profitably and work within budget constraints.


Furthermore, the lack of visibility into Lambda costs can lead to costly mistakes. Several companies, including Adobe, Pinterest, Intuit, CloudOne, and Infor, have experienced unexpected and exorbitant cloud computing bills due to inadequate monitoring. These unforeseen expenses can rapidly deplete financial resources, posing a significant risk to overall company profitability.


Without proper monitoring, organizations may not be aware of cost anomalies until it’s too late. Detecting and addressing these anomalies in a timely manner is crucial to avoid unnecessary financial losses. Delayed realization, akin to Adobe’s unfortunate experience, can result in substantial financial damage.

To mitigate these risks, it is essential to have a comprehensive cloud cost intelligence platform like CloudZero. Such a platform provides insightful and precise reports that map AWS costs to specific customers, teams, features, and products. It offers real-time visibility into Lambda costs, enabling organizations to measure, monitor, and optimize their spend effectively. By leveraging CloudZero, companies can proactively identify cost anomalies and take appropriate actions, ensuring financial stability and operational efficiency.


Conclusion

AWS Lambda is a powerful server less computing service that allows developers to focus on writing code without worrying about infrastructure management. In this blog, we walked through the step-by-step process of setting up a Lambda function, configuring API Gateway as a trigger, and testing the function.

The benefits of AWS Lambda include automatic scaling, cost-efficiency, and easy integration with other AWS services. By leveraging Lambda, developers can build scalable and event-driven applications, making it a valuable tool in the serverless architecture paradigm.






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