AWS Lambda is a serverless compute service that lets you run code without provisioning or managing servers. It automatically scales and manages the infrastructure required to run your code in response to events.
You can upload your code to Lambda and define event sources that trigger the execution of your code. Lambda automatically manages the execution environment, scales it as needed, and provides monitoring and logging.
The benefits of AWS Lambda include automatic scaling, reduced operational overhead, cost efficiency (as you pay only for the compute time used), and the ability to build event-driven architectures.
AWS Lambda functions can be triggered by various event sources, such as changes in Amazon S3 objects, updates to Amazon DynamoDB tables, HTTP requests through Amazon API Gateway, and more.
Lambda automatically handles concurrency by scaling out instances of your function in response to incoming requests. You can set a concurrency limit to control how many concurrent executions are allowed.
The maximum execution duration for a single Lambda invocation is 15 minutes.
You can pass data to Lambda functions through event objects, which contain information about the triggering event. You can also return data by using the return statement or creating a response object.
Yes, Lambda functions can communicate with external resources such as databases, APIs, and other AWS services by using appropriate SDKs and APIs provided by AWS.
AWS Lambda layers are a way to manage and share code that is common across multiple functions. Layers can include libraries, custom runtimes, and other function dependencies.
You can handle errors by using try-catch blocks in your code. Lambda also provides CloudWatch Logs for monitoring, and you can set up error handling and retries for asynchronous invocations.
Yes, Lambda functions can access the internet through the Virtual Private Cloud (VPC) or through public endpoints if your function is not configured within a VPC.
Lambda supports several runtimes, including Node.js, Python, Java, Go, Ruby, .NET Core, and custom runtimes using the Runtime API.
You can set environment variables for Lambda functions when creating or updating the function. These variables can be accessed within your code.
Synchronous invocations wait for the function to complete and return a response, while asynchronous invocations return immediately, and the response is sent to a specified destination.
Event Source Mapping allows you to connect event sources like Amazon DynamoDB streams or Amazon Kinesis streams to Lambda functions. This enables the function to process events as they occur.
You can use AWS Identity and Access Management (IAM) roles to grant permissions to your Lambda functions. Execution roles define what AWS resources the function can access.
AWS Step Functions is a serverless orchestration service that lets you coordinate multiple AWS services into serverless workflows using visual workflows called state machines.
You can use AWS Serverless Application Model (SAM) templates, AWS CloudFormation, or CI/CD tools like AWS CodePipeline to automate the deployment of Lambda functions.
Yes, Lambda functions can connect to on-premises resources by placing the function inside a VPC and using a VPN or Direct Connect connection to establish connectivity.
The Cold Start issue occurs when a Lambda function is invoked for the first time or after it has been idle for a while. The function needs to be initialized, causing a slight delay in response time.