Introduction As a developer, you can build, deploy and manage serverless applications by using AWS services such as Lambda Functions and DynamoDB. In this blog post, I will show you how to create a simple Serverless Application Model (SAM) template for your application.

What is AWS Serverless? AWS Serverless is a way to build and run applications without thinking about servers. Serverless applications are composed of functions, which are run in response to events such as user touch points on an app, or when data changes on an application backend. Functions are stateless and ephemeral: they don't need to be maintained after they've been used; instead, you can use them again (and again) for new requests within your application codebase without having to worry about the cost associated with maintaining them.

What do we need to create a Serverless Application? To create a Serverless Application, you need to have an AWS account and credentials. You can create your AWS credentials through the AWS Console or via the console of your choice (AWS CLI, Amazon CodePipeline, etc.). The most important thing about creating a Serverless Application is that it requires you to use Lambda functions in order for it to be serverless. However, there are several other components needed for this including:

● SAM template - A template that defines how code should be executed when triggered by events from an API Gateway endpoint.

● AWSLambda-Function - The code responsible for execution when triggered by events from an API Gateway endpoint or Lambda function configured with Auto Scaling Groups/Role Scales/Role Tiers

SAM, the Serverless Application Model SAM, the Serverless Application Model, is a specification for describing and deploying serverless applications. It was created by Amazon to simplify the process of building these applications. SAM is a JSON-based file format that describes your function (more on functions later), including its name, whether it's stateless or stateful, what language it uses (JavaScript or Python), and how many invocations you can handle at one time. In addition to being declarative in nature—that means you don't have to write any code yourself—the other cool thing about SAM is that it's standardized across different cloud providers like AWS Lambda and Azure Functions so developers can easily move between platforms without having to learn new languages or APIs each time they need something new from one provider versus another."

API Gateway AWS Lambda is an Amazon Web Services (AWS) service that allows you to run code in response to events on your serverless applications. You can use it to run custom functions or organize your code in a way that makes it easy for other developers to add new features, without having them change the existing codebase.

Lambda Function AWS Lambda functions are stateless and can be thought of as servers that run code in response to an event. For example, if your application is processing a user's order for a pizza, you could write a Lambda function to handle the order and then send back a confirmation email when it's complete. The name "lambda" comes from the idea of being small (hence the letter L) and lightweight (hence lamb). It also refers to an adult male sheep who has an udder (which produces milk). Similar to how this works with AWS Lambda: You don't have too much overhead because there's no infrastructure or other resources required; instead all you need is enough memory space on your machine so that your code runs quickly enough—and nothing more!

DynamoDB table DynamoDB is a managed NoSQL database service. It's designed to be highly scalable, low latency, and fast—with the ability to handle thousands of read/write requests per second (RPS). DynamoDB is fully managed: you don't need to worry about provisioning or scaling your data; it occurs automatically as you add capacity in real-time.

Deploying, Managing, and Testing Sam app Deploying, Managing, and Testing the App on AWS The first step is to deploy your app to AWS. You can use the AWS SAM CLI tool or API calls to deploy your code from a local environment into an S3 bucket in Amazon Web Services (AWS) Simple Storage Service (S3). The following example shows how you would deploy a Lambda function that uses DynamoDB as an underlying database: ● aws s3 mb s3://my-droplet/my-lambda-functions/sam_app.. --region us-east-1 --bucket myappname ● aws lambda create-function sam_app_deployed \ --function \ --name "Sam App Deployed" \ --runtime python2.7 \ --role arn:aws:iam::123456789012:role/lambdaRoleArn > sam_app_deployed.py After you have deployed your code, you can test it locally on a development machine before deploying it into production. Once you get started with AWS serverless, there is no going back. You will not be able to stop using AWS Lambda and DynamoDB. It’s like eating an omelet - once you start eating it, the habit becomes hard to break! We have seen many developers who have moved from traditional cloud hosting services to AWS Serverless because it provides a better set of features at cheaper rates but still allows them to build scalable applications without any technical limitations or constraints on their infrastructure.

Conclusion We have covered most of the basics of creating a Serverless application. In another post, in the future, we will explore more advanced topics such as deploying Sam applications and testing them.