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Serverless computing allows DevOps teams the ability to create applications without having to manage servers in the cloud.
This allows teams to concentrate on developing new features and deploying them, rather than worrying about infrastructure. It can also reduce IT workloads in server maintenance and management.
Amazon Web Services (AWS), offers many serverless options for compute and storage, databases, message queueing and stream processing.
This post compares AWS Lambda and AWS Step Functions services in terms price, use cases and runtimes.
What is AWS Lambda and how does it work? AWS Lambda is a serverless computing platform offered by AWS. Developers can use Lambda for cloud-based execution of their code. AWS Lambda uses Lambda function to allow the use of most popular coding languages.
These functions can be run independently of any other code and can be output directly to users or for consumption by other services. Lambda allows you to focus on your function and how it is used. The backend infrastructure is managed by Lambda.
Lambda provides cloud infrastructure management and provisioning, just like any serverless system. This includes servers, databases, backend, security logic, and more. Front-end applications can be built without the need for complex hardware. Lambda’s pricing is determined by the number of executions and functions are provided as a service.
AWS Lambda uses include:
File processing–Imagine that you have an app that gives you files at random times and you want to convert them to a different format. These files can be converted by sending them to a Lambda function.
Website hosting–you have the option to host websites on S3 or outsource all computations through AWS Lambda. This allows you to manage your website without having to pay for server hosting.
Security updates–You can monitor your website’s log files using Lambda functions. When a log file is modified, you need to trigger your Lambda function.

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How AWS Lambda works
AWS Lambda components contain:
Function code–the function that you want to run when Lambda triggers.
Configuration specifications–details that define how functions are executed and which resources are required.
Event triggers–An optional source that triggers the function via other AWS services and/or external services. Functions can also be manually triggered.
Handler–A method that processes events in your function, and returns the results. It acts as a communication channel between the function’s functions and external services.
Environment variables–allows you to store runtime information using key-value pairs. These can be used to define external function configuration.

Here’s how AWS Lambda executes its model:
Containers–Lambda allocates an object and loads the necessary code resources to execute a function. It may reuse the same container to improve its performance.
Each instance can only process one request at a given time. Instances can be autoscaled to handle simultaneous invocations.
Events trigger Lambda functions. Events can be triggered by several AWS services or third-party services.
Stateless functions–containers are ephemeral with no persistent storage and functions are stateless. Temporary storage can be used in the container to keep loaded dependencies, but the function itself does not retain any history of previous runtimes.

These are some AWS Lambda specifications you should know:
Runtimes and supported languages–