AWS Lambda

Serverless Computing Made Easy

AWS Lambda is one of the most popular services available for serverless computing. Offered by Amazon Web Services, AWS Lambda makes it easy for users to create self-contained, scalable, fault-tolerant code (written in a number of supported languages and runtimes) that can then run in the AWS cloud without having to provision or manage servers.

There are plenty of similar services out there, but none of them remove as many barriers to entry as does AWS Lambda. With this service, you don’t have to know how many servers, CPUs, or how much memory your code will need to run. With AWS Lambda, code is executed in response to events, and the resources for that code are automatically managed and adjusted.

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What AWS Lambda Is

The initial release of AWS Lambda came in November 2016. The platform was designed as a serverless compute service for running code without provisioning or managing servers, creating the necessary logic for workload-aware clusters, maintaining event integrations, or managing runtimes.

AWS Lambda makes it possible to run code nearly any type of application or backend service and is ideal for use cases such as:

Image/object uploads to Amazon S3
Updates to DynamoDB tables
Responding to website clicks
Reacting to sensor readings from IoT devices
Provision backend services triggered by custom HTTP requests

The AWS Lambda process is very simple. You write your code, set it up to be triggered from other AWS services, endpoints, or in-app activity, upload the code as a zip file or container image, and the service takes care of the rest. AWS Lambda will automatically allocate the necessary compute resources and execute your code based on the incoming code or event. You can also configure your code to be automatically triggered by any one of the 200 AWS services and SaaS applications, or you can call it directly from a web or mobile application.

And, like so many other services, you only pay for the computing time you use.

What is Serverless Computing?

At this point, you might be wondering what exactly is serverless computing? It’s not exactly what it sounds like. Yes, there is a server involved, but it’s not one you (the user or admin) have to manage. Instead, serverless computing allows you to build and run applications and/or services without having to worry about the supporting hardware. All server management is taken care of by the third-party host (in this case, AWS Lambda).

For many businesses, serverless computing isn’t only a way to save considerable money, it can be the only option. If you’re a startup or a company without a data center, you need the means to deploy and serve up your applications and services at scale. That’s where serverless computing comes in.

Difference Between AWS Lambda and Amazon EC2

You might already be familiar with Amazon EC2 (Amazon’s Elastic Compute Cloud service), so you understand the idea behind “renting” virtual computers to house your applications. But there’s a very important difference between AWS Lambda and Amazon EC2.

The difference between Lambda and EC2 is that with EC2 you are responsible for provisioning for capacity, monitoring health and performance, and designing for both fault tolerance and scalability.

With Lambda, this is all done for you. Lambda performs all operational and administrative activities for you.

Benefits of Using AWS Lambda

The biggest benefit of using Lambda is not having to worry about provisioning for your application or service. Your company will also enjoy:

Continuous and automatic scaling.
Cost optimization and millisecond metering.
Consistent performance, regardless of scale.
An increase in innovation.
Application modernization.
Vast serverless application repository.
Ability to build your own backend services.
Completely automated administration.
Built-in fault tolerance.
Functions can be packaged and deployed as container images.
Fine-grained performance control.
Shared file systems.
Pay for what you use.

What Languages Does AWS Lambda Support?

Although Lambda doesn’t support all programming languages, it does include a number of the most popular languages being used for cloud-native, web, and mobile app development, such as

Java
Go
PowerShell
Node.js
C#
Python
Ruby

Lambda also provides a Runtime API which makes it possible for you to use any additional languages.

Use Cases for AWS Lambda

AWS Lambda can work for several use cases. Here are a few ideas for you to consider:

Preprocess data before feeding it into a machine learning model.
Real-time data streaming processing.
Real-time file processing.
Operating serverless websites
Rapid document conversion
Predictive page rendering
Working with external services
Log analysis on the fly
Automated backups and everyday tasks
Processing uploaded S3 objects
Backend cleaning
Bulk real-time data processing

Companies That Use AWS Lambda

The list of companies that use AWS Lambda is just as impressive as the company that serves it up. The companies include Thomson Reuters, iRobot, Autodesk, Financial Engines, MLBAM, Square Enix, The Guardian, Benchling, T Mobile, Bustle, Alt/S, The Seattle Times, AOL, and Netflix.

Conclusion

AWS Lambda is a powerful and flexible service that makes it possible for businesses of all sizes to run code without having to also provide and manage costly servers. With this platform at your disposal, you can write Lambda functions in your favorite language and deploy them with familiar tools, such as AWS SAM, or Docker.

AWS Lambda should be the first consideration for any company looking to scale out services without having to scale up its hardware budget.