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What is AWS Lambda?

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AWS Lambda is a serverless computing service provided by Amazon Web Services (AWS). It allows you to run code without having to provision or manage servers explicitly. Here's a technical breakdown of AWS Lambda:

Architecture:

  1. Event Sources:
    • AWS Lambda is event-driven, meaning it executes code in response to events triggered by various AWS services or custom sources.
    • Events can be anything from changes in data stored in an S3 bucket, updates to a DynamoDB table, or HTTP requests through API Gateway.
  2. Execution Environment:
    • When an event occurs, AWS Lambda automatically provisions an execution environment to run your code.
    • The execution environment includes the runtime, dependencies, and resources required to execute the function.
    • Lambda supports multiple programming languages, including Node.js, Python, Java, Ruby, Go, and .NET Core.
  3. Execution Context:
    • Each function execution occurs within an execution context, which includes the runtime environment and resources allocated to the function.
    • The context provides information about the execution environment, such as memory size, execution time remaining, and AWS Identity and Access Management (IAM) role.
  4. Stateless Execution:
    • AWS Lambda functions are designed to be stateless, meaning they don't retain information between executions.
    • Any state or data that needs to persist should be stored externally, such as in an S3 bucket or a database.

Key Features:

  1. Automatic Scaling:
    • Lambda automatically scales based on the rate of incoming events. It can handle a single request or scale up to thousands of concurrent executions.
  2. Pay-per-Use Pricing:
    • You are billed based on the actual compute time consumed by your function, measured in milliseconds. There are no charges when your code is not running.
  3. Integration with Other AWS Services:
    • Lambda seamlessly integrates with various AWS services, allowing you to build serverless applications that respond to events from different sources.
  4. Resource Allocation:
    • You can configure the amount of memory allocated to your function, and AWS Lambda automatically provisions proportional CPU power, network bandwidth, and disk I/O.
  5. Environment Variables:
    • You can set environment variables for your Lambda function, allowing you to pass configuration values and secrets without hardcoding them in your code.

Workflow:

  1. Create Lambda Function:
    • Define your function code, specifying the runtime, handler function, and any dependencies.
  2. Configure Triggers:
    • Define event sources or triggers that will invoke your Lambda function. This could be an S3 bucket, an API Gateway endpoint, a DynamoDB table, etc.
  3. Deploy and Monitor:
    • Deploy your Lambda function to AWS, and AWS Lambda automatically takes care of provisioning the required resources.
    • Monitor the function's performance and logs through AWS CloudWatch.
  4. Automatic Scaling:
    • As events occur, Lambda automatically scales up to handle the load. If there is no activity, there are no ongoing costs.