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AWS Lambda Complete Guide

AWS Lambda Complete Guide: What It Is And How To Use It?

How often do you wish you could run some code without worrying about maintaining your server? If so, good fortune finds you! With AWS Lambda, you can run your code in response to events and only pay for the computing time you use. In that case, kick back, relax, and prepare to enter the exciting world of serverless computing! Learn more about AWS Lambda and how you can use it to create scalable, low-cost apps in this in-depth guide.

What Is AWS Lambda?

Amazon Web Services (AWS) offers a serverless computing service called AWS Lambda. It frees you from the burden of provisioning and managing servers, enabling you to focus on writing and running code in response to events.

To ensure your code runs smoothly, you can tailor the resources available to your Lambda function during its creation. You pay for the time that your code executes in AWS Lambda, and it will automatically scale up or down to match the needs of your app.

Because AWS Lambda handles the application’s infrastructure and operations, you can concentrate on developing your app’s functionality. The applications you may create with AWS Lambda range from straightforward event-driven routines to intricate microservices structures. Node.js, Python, Java, Go, Ruby, and C# are just some of its compatible languages.


AWS Lambda Workflow


How To Use AWS Lambda?

There are only a few critical tasks to remember while developing and releasing a Lambda function. This section will walk you through creating a Lambda function, setting up event triggers, and running a test. Here are the steps to use AWS Lambda:

Creating A Lambda Function:

Click the “Create function” button in the Lambda service’s section of the AWS Management Console to set up a new Lambda function. Optional wizards will guide you through building the function from scratch using an existing blueprint or container image. Select “New blank document” and label your function. The language in which you’ll write the code for your function, known as its “runtime,” can be chosen.

Coding It Up:

After creating a Lambda function, one can write code for that function in the function editor. You can either type your code into the editor or upload a ZIP file with your code inside. A starter code snippet is provided. The sample code will be formatted using the programming language’s syntax you specified. When you’re done with your code, click the Test button to run it in the editor. You can also perform function testing by providing input and expected output data.

Configuring Your Function:

Your function’s access to other AWS services is defined by the execution role that Lambda generates for you automatically. The memory and processing power requirements of your function must be set. Other advanced options for your function include establishing environment variables, adding layers, and configuring other settings. You can do so if you need to make changes or add a new position.

Setting Up Event Triggers:

Many types of events can trigger your Lambda function’s execution. One can set up triggers for various events, including those from AWS services like S3, API Gateway, and CloudWatch, as well as events generated by your programs. Look for the “Add trigger” button on the page where functions are configured to begin setting up event triggers.

Testing Your Function:

After creating your code and establishing your event triggers, it’s time to ensure everything is working as it should. Before putting your function into production, you should ensure it works as expected by testing it extensively. The Lambda console has a Test button you may use to try out your function. One can also automate function testing using the AWS Command Line Interface and Software Development Kits.

Deploying Your Function:

After your function has passed testing, you may send it into production by making an alternate name. Once the new version or alias has been established, you can use it in production. You can deploy your function through the AWS Management Console, the AWS Command Line Interface (CLI), or SDKs.

AWS Lambda Integrations With Other AWS Services

Because of its compatibility with other AWS services, AWS Lambda is a flexible option for developing serverless software. Some of the most popular AWS tools that you may utilize in conjunction with Lambda are as follows:

Amazon S3:

Amazon Simple Storage Service (S3) is a web-based, highly scalable object storage service. If you have an AWS Lambda function, you may set up S3 to call it whenever a new object is added to an S3 bucket. You can use this function to process the object in a way that is specific to your needs, such as creating thumbnails, processing data, or triggering other AWS services. In response to an event notification from S3, Lambda will execute your function whenever a new object is added to the bucket.

Amazon API Gateway:

Create, implement, and manage RESTful APIs at any scale with the help of Amazon API Gateway, a fully managed service. You can connect API Gateway to your Lambda function to provide unique processing for your API. With this capability, you may create serverless web apps that can process several requests per second. Caching, security, and rate restriction are just some of the capabilities that API Gateway offers to keep your API safe and scalable.

Amazon DynamoDB:

The latency of Amazon DynamoDB never exceeds tens of milliseconds, regardless of the size of the database. When a table in DynamoDB changes, your Lambda function can be activated using a stream. This function can implement your data processing and analysis in real-time. Lambda receives an event notice from DynamoDB whenever a table change occurs and executes your function in response.

Amazon CloudWatch Events:

With Amazon CloudWatch, you can keep tabs on your AWS resources and apps in real-time. CloudWatch notifies Lambda of the occurrence of a predetermined event, at which point your function is executed. Rules can be set up in CloudWatch Events to automatically call your Lambda function at regular intervals (every minute, every hour, etc.). Using this function, you can schedule repeating data processing or automate other mundane processes.

Amazon Kinesis:

Amazon Kinesis is a service for ingesting, processing, and analyzing massive amounts of streaming data in real time. You can use Lambda to process Kinesis data streams. Kinesis notifies Lambda of incoming data streams, and Lambda, in turn, executes your function. This function will let you construct instantaneous analytics and data processing.

Amazon SQS:

To scale and decouple microservices, distributed systems, and serverless applications, you can use Amazon Simple Queue Service (SQS). An AWS Lambda function can process messages from an SQS queue. Your function is executed by Lambda in response to an event notification from SQS when a message arrives. This allows for the creation of scalable and robust message-processing systems.


When developing serverless apps that can grow to meet the needs of any workload, AWS Lambda is an invaluable tool. Lambda allows for the creation of serverless web applications that can process millions of requests per second and automate mundane activities by integrating with Amazon API Gateway and CloudWatch Events. When combined with other AWS services like S3, DynamoDB, Kinesis, and SQS, Lambda allows developers to create scalable, low-cost applications that AWS entirely manages.

Clients across various sectors hire Triotech Systems because of our expertise in custom software development, cloud solutions, and digital transformation. Triotech Systems has a team of specialist engineers who are well-versed in AWS Lambda and other AWS services, allowing them to assist clients in harnessing the potential of serverless computing for the sake of innovation and business expansion. Triotech Systems can assist you in making the most of cutting-edge cloud technology to construct a brand-new application or enhance an existing one.


The cost of using AWS Lambda depends on the number of requests and the time it takes to complete the tasks. After the first million requests per month are processed at no cost, subsequent requests will incur a nominal fee. No minimum or sign-up fees are required, and you’ll only be charged for the computing time you actually consume.

The list of supported languages for AWS Lambda is long, and it includes popular ones like Node.js, Python, Java, Go, C#, and Ruby. Code written in other languages can also be executed with the help of a custom runtime.

A single Lambda function can only run for up to 15 minutes at a time. If your function takes longer than that to complete, consider dividing it into multiple functions or utilizing more AWS services.

Lambda on AWS is completely managed and works seamlessly with other AWS services like S3, DynamoDB, and Kinesis. AWS Lambda, however, can be used with other cloud providers through the use of bespoke integrations or API calls.

You can use the various monitoring and debugging tools available in AWS Lambda to locate and fix problems within your functions. Requests can be tracked using X-Ray, while log data can be seen with CloudWatch Logs, and performance metrics may be monitored with CloudWatch Metrics. In addition, you may keep tabs on and study the performance of your Lambda functions with the help of external programs like New Relic and Datadog.

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