AWS Lambda Tutorial

AWS Lambda Tutorial

Amazon Web Services-AWS introduced the AWS Lambda feature, a serverless computing service. Users of AWS Lambda can create functions, develop self-contained applications written in the supportive language and runtimes, and upload their application to AWS Lambda, which executes the specified functions efficiently and flexibly. Lambda functions are given such importance because of their ability to perform any type of computing task. Let it be from serving web pages, processing vast data to calling APIs, and integrating with other services of AWS, Lambda functions have proven their authority and benefits. 

If you are an apprentice in AWS and want to understand it better, you can always visit Cloud Computing Courses and start your in-depth learning. It is also evident that every business in this tech world is familiar with AWS and is enjoying the privileges of AWS for its growth and development. Hence, it is important that every programmer must be aware of cloud computing-a widely emerging and growing industry. AWS is the most popular platform for every business that is more than happy to work on this cloud system as it has a more excellent value of authority in cloud platforms.

The "serverless" computing indicates there is no need to maintain your own servers to run these functions. AWS Lambda comes with a fully managed service that takes care of needed infrastructure for you. It also doesn't mean that the term serverless is void of servers. Instead, it means that the required servers, operating systems, network layers, and the rest of the required infrastructures are taken care of, which leaves you with the main task of focusing on writing your application code. If you want to learn and understand AWS and its functionalities at a beginner's stage, you can also take a peek at AWS - an introductory course on its functionalities.

Working of AWS Lambda

Cloud Computing and containers go hand in hand. Lambda functions run on their own containers. When you create a function, Lambda puts it into a new container, and this container is executed on a multi-tenant cluster of machines that are taken care of by AWS. Each function is allocated with appropriate RAM and CPU capacity before these functions start running. Once the function finishes its running, AWS takes care of the further requirements. The RAM allocated at its creation is multiplied by the time the function spent running. Thus, the customers are charged based on the memory allocated along with the total run time the function took to complete. It is evident that AWS manages the entire layer of the infrastructure of AWS Lambda. AWS purely supports the abstract concepts as customers will not be aware of the backend working of the system operations. They also need not worry about the updation of the underlying machines, avoiding network contention, and more. All these operations are taken care of by AWS.

AWS Lambda - an essential part of the Serverless Architecture

AWS Lambda is the leading candidate for running the applications code while you are aiming for serverless applications. To achieve a complete serverless stack, you will require a computing service, a database service, and an HTTP gateway service. Lambda features fill the primary role of the computer services on AWS. It integrates with various other AWS services and with API gateway, RDS, and DynamoDB forms serverless solutions for the AWS users. AWS Lambda also supports various popular languages and runtimes that make developers' jobs easier. Hence, it's a better fit for a wide range of serverless developers. 

Most Popular usecases of AWS Lambda

It is well-known that Lambda's architecture surpasses all the traditional Cloud Computing platforms. It provides scalable APIs. One Lambda function execution counts as a single HTTP request when you build APIs using AWS Lambda. Various parts of API can be linked to different Lambda functions through Amazon API Gateway. It is also essential to notice that AWS Lambda automatically scales your individual functions based on their requirements. This also leads to the conclusion that various parts of API can scale according to their needs - current usage levels. Hence, it makes way for a cost-effective approach with flexible API setups. Data Processing is also another advantage of AWS Lambda. These Lambda functions are optimized for even-based data processing. AWS Lambda is easier to integrate with data sources like Amazon DynamoDB. This helps you to trigger Lambda functions for specific data events.

You can get in-depth knowledge of AWS Lambda through this free online AWS Lambda Tutorial. You will briefly understand AWS Lambda, its roles, functions, and features. You can also hop onto the PG programs in Cloud Computing to dig deeper into its concepts and build your career in it. You can also enroll in this free AWS Lambda tutorial and earn a free AWS certificate on completing the course.