Getting Started with AWS Lambda

Getting Started with AWS Lambda: A Step-by-Step Tutorial for Beginners

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Serverless computing is a strong approach that has arisen in the constantly changing cloud computing ecosystem that makes developers concentrate on writing code without managing servers. AWS Lambda is a standout offering in the Amazon Web Services (AWS) ecosystem for novices who want to start their serverless journey. This detailed blog helps anyone looking to earn their AWS Certification because it will walk you through the process of setting up AWS Lambda. But let’s analyse first: What is AWS Lambda.

What is AWS Lambda?

Amazon Web Services offers a serverless compute solution called AWS Lambda. Essentially, it frees you from provisioning and managing servers so that you may execute code. Cloud computing is now even more flexible and efficient thanks to this serverless architecture. With AWS Lambda, developers can concentrate entirely on creating code and specifying the circumstances that lead to its execution; AWS handles the infrastructure and scaling in the background.

Step-by-Step Tutorial for Beginners

Step 1: Set Up an AWS Account

You must have an AWS account before using AWS Lambda. Visit the AWS website to create a free account if you don’t already have one. You’ll be able to use Lambda and many other AWS services after your account is set up.

Step 2: Navigate to AWS Lambda Console

Once you’ve logged into your Amazon account, go to the Lambda console. The console is the main interface for setting up and controlling Lambda functions. Get acquainted with the layout, as this will be where you usually work with Lambda.

Step 3: Create a New Lambda Function

Click the “Create function” button in the Lambda console to start a new Lambda function. You will be given the option to build a function from scratch or select a blueprint. While you have complete control over your function when you create from scratch, blueprints are pre-configured templates for typical use cases.

Step 4: Configure Your Lambda Function

It’s time to configure your Lambda function after selecting a blueprint or writing a function from scratch. Choose a runtime (such as Python, Java, or Node.js), assign a name to your function, and configure the execution role. The rights that your Lambda function will have in your AWS environment are specified by the execution role.

Step 5: Add Triggers

Because lambda functions are event-driven, occurrences cause them to happen. You can add triggers to your function in this phase. Events from other AWS services, such as a change in an S3 bucket or an HTTP request made via API Gateway, can also serve as triggers. Select the right trigger based on your use case.

Step 6: Write Your Lambda Function

Now that you have the fundamental setup in place, you can write the Lambda function’s code. Select the programming language that you are most familiar with using AWS Lambda. Since Lambda functions are meant to be stateless and have a brief lifespan, keep this in mind while you write the code to handle the event that calls your function.

Step 7: Test Your Lambda Function Locally

It’s best practice to test your Lambda function locally before releasing it to the cloud. With the help of a collection of tools from AWS, like the SAM CLI and AWS CLI, you may replicate Lambda function calls on your local computer. Before you publish your code to the cloud, testing locally can help you find and fix any problems.

Step 8: Deploy Your Lambda Function

It’s time to deploy your Lambda function to the AWS cloud if you’re happy with it. When you select “Deploy” on the Lambda console, AWS will handle the deployment procedure. The function is now operational and prepared to manage events.

Step 9: Monitor and Troubleshoot

AWS Lambda offers a range of monitoring tools to help track your functions’ effectiveness. Get insights into your functions’ behaviour, see logs, and set alarms using the AWS CloudWatch console. Monitoring is essential for seeing potential problems and taking appropriate action.

Step 10: Scale as Needed

Automatic scaling is one of serverless computing’s main benefits. Your functions are automatically scaled via AWS Lambda according to the incoming workload. Lambda automatically manages the rising demand as your application expands, guaranteeing peak performance without the need for manual intervention.


Best wishes! You have completed the steps necessary to get started with AWS Lambda. This platform for serverless computing offers an adaptable and expandable way to run code without having to deal with the headaches of server management. Use the wealth of documentation and community assistance offered by AWS Lambda as you continue to explore it to make the most out of your serverless programming experience. Have fun with coding!

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