AWS Lambda Tutorial – Getting Started With Triggers, Costs, and Getting Started With Web Editor


If you want to learn how to use AWS Lambda, this tutorial will help you to get started. It includes the following topics: Triggers, Costs, and Getting Started with Web Editor. After you have mastered the basic concepts, you can move on to more advanced topics. This tutorial will also provide helpful examples to help you start with AWS Lambda.

Getting started with AWS Lambda

To start with AWS Lambda, you first need to sign up for an account. Next, you will be prompted to create a new function. Once you’ve your account, you can click the orange “Create function” button on the main AWS Lambda page. A Lambda function typically accepts JSON-formatted input and responds using the same format.

Each Lambda function is packaged into a container and runs on a multi-tenant cluster of machines managed by AWS. It is allocated CPU and RAM capacity. This is multiplied by the amount of runtime that the function is required to complete. Then, customers pay for the use of the allocated memory and CPU. The cost is meager if the process doesn’t use many resources.

Once your Lambda function has been created, it will move into a container. This container will run the initialization code before receiving a request. This code segment can also set up database connections. When a call is made, a handler function will be called. It receives data from the event and context variables and can also include an error or result parameter.

Using the web editor

After installing the Lambda function, use the AWS console to create a new position. A new account will have an open console, but you can create a process by clicking on the Create Function button. Lambda functions typically respond to a query using JSON-formatted output.

Once you have created your Lambda function, you can upload it to AWS Lambda. To upload a Lambda function, follow the tutorial’s steps. In addition, you’ll need a Lambda function name, role (by default, it should be “system”), and web editor. Note that the web editor has a comment on line seven.

In this tutorial, you’ll create a Lambda function by uploading an image to S3. This will trigger a Lambda function that will resize the image in the backend. You’ll then receive an email confirming that the process was completed successfully.


Triggers are events that happen to an AWS Lambda function. The event can be anything that happens in the AWS account, such as uploading a file to S3. This tutorial will focus on triggers, but you can use any event you choose to trigger a Lambda function.

You can add triggers to distributions and cache behaviors to enable a particular Lambda function to run when certain events happen. For example, if you specify a trigger on CloudFront, the process will be executed every time an event occurs on CloudFront. In addition, the process will access the request body and replicate it to different regions if you want. Once the function is set up, you can add more triggers if needed.

AWS Lambda is a platform for massive computing. As a result, the caller can control the scale of the function and how it handles errors. AWS Lambda uses the RequestResponse invocation type, which maintains a connection until the function returns. After that, the response will include the ‘s body process and headers describing its response.


AWS Lambda is a cloud computing service used for various applications. It offers high availability and reduced financial risks. However, Lambda will incur costs as the number of requests and corresponding workloads increases. The free tier of AWS Lambda includes 400,000 GB seconds of computing time per month, which is approximately 110 hours. However, there are limits to the amount of memory a Lambda function can be configured with.

The costs of AWS Lambda vary depending on the amount of memory a Lambda function can use. For example, a 512 MB of memory function will cost $1,050 per month. For more significant operations, you can increase the memory size of the process. Alternatively, you can reduce the time that a process runs. A few simple steps can help you manage the costs of your Lambda function.

The most important thing to remember when using AWS Lambda is that paying for only what you use is always better. This way, you can avoid potential snowballing costs due to excessive usage. The expenses of Lambda will depend on the duration of the code and the number of requests it receives.