AWS Lambda is among the most popular services for serverless computing. Provided by Amazon Web Services, it allows users to create scalable, self-contained, fault-tolerant code that runs in the AWS cloud without the need to manage or provision servers. AWS Lambda supports various languages and runtimes, making it a versatile option for developers.
While other similar services exist, AWS Lambda stands out by removing many of the barriers to entry. There’s no need to determine the number of servers, CPUs, or memory requirements for your code. Instead, AWS Lambda automatically manages and adjusts the resources, executing code in response to events seamlessly.
What AWS Lambda Is
The initial release of AWS Lambda came in November 2016. The platform was designed as a serverless computing 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 for 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
- Provisioning 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 cloud infrastructure 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? Despite the name, it doesn’t mean there are no servers involved. There is indeed a server, but it’s not one that you (the user or admin) need to manage. Instead, serverless computing allows you to build and run applications and services without worrying about the underlying hardware infrastructure. All server management is handled by the third-party host—AWS Lambda in this case.
For many businesses, serverless computing isn’t just a way to save substantial costs; it can be the only viable option. If you’re a startup or a company without a data center, you need a way to deploy and scale your applications and services. That’s where serverless computing steps in, offering a solution that is both scalable and cost-effective.
Difference Between AWS Lambda and Amazon EC2
You might already be familiar with Amazon EC2 (Amazon’s Elastic Compute Cloud service), where you essentially “rent” virtual servers to host your applications. However, there’s a key difference between AWS Lambda and Amazon EC2.
With EC2, you are responsible for provisioning capacity, monitoring health and performance, and designing for fault tolerance and scalability. Essentially, you manage the infrastructure.
In contrast, with Lambda, all of these operational and administrative tasks are handled for you. AWS Lambda automatically manages capacity, monitors performance, and ensures your application is fault-tolerant and scalable without requiring you to handle the underlying infrastructure.
Benefits of Using AWS Lambda
The biggest benefit of using AWS Lambda is that you don’t have to worry about provisioning for your application or service. Your company can also take advantage of several additional benefits:
- Continuous and automatic scaling
- Cost optimization with millisecond metering
- Consistent performance regardless of scale
- Increased innovation opportunities
- Application modernization
- Access to a vast serverless application repository
- The ability to build your own backend services
- Completely automated administration
- Built-in fault tolerance
- The option to package and deploy functions as container images
- Fine-grained performance control
- Support for shared file systems
- A pay-for-what-you-use pricing model
What Languages Does AWS Lambda Support?
Although AWS Lambda doesn’t support every programming language, it does include several popular ones commonly used for cloud-native, web, and mobile app development, including:
Additionally, Lambda offers a Runtime API, allowing you to use other programming languages not natively supported.
Use Cases for AWS Lambda
AWS Lambda can be utilized for a variety of use cases. Here are a few ideas 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 routine tasks
- Processing uploaded S3 objects
- Backend cleaning
- Bulk real-time data processing
The list of companies leveraging AWS Lambda is as impressive as the service itself. Notable users include:
Companies That Use AWS Lambda
- Thomson Reuters
- iRobot
- Autodesk
- Financial Engines
- MLBAM
- Square Enix
- The Guardian
- Benchling
- T-Mobile
- Bustle
- Alt/S
- The Seattle Times
- AOL
- Netflix
Conclusion
AWS Lambda is a powerful and flexible service that enables businesses of all sizes to run code without the need to provision and manage costly servers. With AWS Lambda, you can write functions in your preferred language and deploy them using familiar tools like AWS SAM or Docker.
For any company aiming to scale services while keeping hardware costs manageable, AWS Lambda should be a top consideration.
