What is AWS Lambda?

What is AWS Lambda?

AWS Lambda is a serverless computing service that executes your code in response to events and automatically manages the underlying computing resources for you. You can use AWS Lambda to extend other AWS services with custom logic, or create your own back-end services that operate on AWS scale, performance, and security. AWS Lambda can automatically execute code in response to various events, such as HTTP requests through the Amazon API Gateway, modifications to cubed objects in Amazon S3, table updates in Amazon DynamoDB, and state transitions in AWS Step Functions.

Lambda runs your code on a highly available computing infrastructure and performs all the management of computing resources, including server and operating system maintenance, capacity provisioning and automatic escalation, deployment of security and code patches, and code monitoring and registration. All you need to do is provide the code.

AWS Lambda Functions

The code that you run on AWS Lambda is called the "Lambda function". After creating your Lambda function, it will always be ready to run as soon as it is activated, similar to a formula in a spreadsheet. Each role includes its code, plus associated configuration information, including the role name and resource requirements. Lambda functions are "stateless", with no affinity for the underlying infrastructure, so Lambda can quickly start as many copies of the function as necessary to increase the rate of events received.

After uploading your code to AWS Lambda, you can associate your role with AWS-specific resources (for example, an Amazon S3-specific bucket, an Amazon DynamoDB table, an Amazon Kinesis flow, or an Amazon SNS notification). Then when the resource is changed Lambda will perform its role and manage computing resources as needed to track incoming requests.

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The most common use cases for AWS Lambda?

Due to the Lambda architecture, it can offer great benefits over traditional cloud computing configurations for applications where:

• Individual tasks performed for a short period of time;

• Each task is usually independent;

• There is a big difference between the lowest and highest levels of the application workload.

Some of the most common use cases for AWS Lambda that meet these criteria are:

Scalable APIs

When creating APIs using AWS Lambda, and execution of a Lambda function can serve a single HTTP request. Different parts of the API can be routed to different Lambda functions through the Amazon API Gateway. AWS Lambda automatically scales individual functions according to demand for them, so different parts of your API can be scaled differently based on current usage levels. This allows for flexible and cost-effective API configurations.

Data processing

Lambda functions are optimized for event-based data processing. It's easy to integrate AWS Lambda with data sources like Amazon DynamoDB and trigger a Lambda function for specific types of data events. For example, you can use Lambda to do a job every time an item is created or updated in DynamoDB, making it suitable for items like notifications, counters, and analytics.

Task Automation

With its event-based model and flexibility, AWS Lambda is ideal for automating multiple business tasks that don't require a full server all the time. This can include running scheduled tasks to clean up your infrastructure, processing form submitted data on your site or moving data between different data stores on demand.

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Benefits of AWS Lambda

There are no servers to manage

AWS Lambda automatically executes your code without the need to provision or manage servers. Just write the code and load it into Lambda.

Continuous Scale

AWS Lambda automatically scales your application by executing the code in response to each trigger. Its code runs in parallel and processes each trigger individually, scaling precisely with the size of the workload.

Measuring Seconds

With AWS Lambda, you are charged for every 100 ms your code is executed and the number of times it is activated. Pay only for the processing time you consume.

Consistent Performance

With AWS Lambda, you can optimize the execution time of your code by choosing the right memory size for your function. You can also enable provisioned concurrency to keep your functions initialized and hyper-ready to respond in two-digit milliseconds.

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