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Pablo Rodriguez

Aws Lambda

Introduction to AWS Lambda

Section titled “Introduction to AWS Lambda”

  • AWS Lambda basics:

    • Serverless compute service
    • Run code without provisioning/managing servers
    • Run on schedule or in response to events
    • Pay only for compute time used
    • Code runs only when triggered
    • Code you run is a Lambda function

  • Benefits of Lambda:

    • Supports multiple programming languages
      • Java, Go, PowerShell, Node.js, C#, Python, Ruby
      • Use any library (native or third-party)
    • Completely automated administration
      • AWS manages infrastructure
      • Focus on building differentiated services
      • AWS handles administration, maintenance, security patches
      • Built-in logging and monitoring through CloudWatch
    • Built-in fault tolerance
      • Maintains compute capacity across multiple Availability Zones
      • Protection against machine/data center failures
      • No maintenance windows or scheduled downtimes
    • Supports orchestration of multiple functions
      • Build workflows with AWS Step Functions
      • Define sequential, parallel, branching, error-handling steps
      • Create stateful, long-running processes
    • Pay-per-use pricing
      • Pay only for requests served and compute time required
      • Billing metered in 100-millisecond increments
      • Cost-effective and scalable

  • AWS Lambda event sources:

    • AWS services or applications that trigger Lambda functions
    • Services that invoke Lambda asynchronously:
      • Amazon S3
      • Amazon SNS
      • Amazon CloudWatch Events
    • Services Lambda can poll:
      • Amazon SQS
      • Amazon DynamoDB
    • Services that invoke Lambda directly:
      • Elastic Load Balancing (Application Load Balancer)
      • Amazon API Gateway
    • Direct invocation:
      • Lambda console
      • Lambda API
      • AWS SDK
      • AWS CLI
      • AWS toolkits

  • Lambda function configuration:

    • Name the function
    • Specify runtime environment (Python, Node.js, etc.)
    • Define execution role (IAM permissions)
    • Configure function:
      • Add trigger (event source)
      • Add function code
      • Specify memory allocation (128MB to 10,240MB)
      • Optional settings: environment variables, description, timeout, VPC, tags

  • Example use cases:

    • Schedule-based example: Start and stop EC2 instances

      • CloudWatch event scheduled to run Lambda function
      • Function triggered with IAM role permissions
      • EC2 instances started/stopped at defined times

    • Event-based example: Create thumbnail images

      • User uploads object to S3 bucket
      • S3 detects object-created event
      • S3 invokes Lambda function with event data
      • Function runs with execution role
      • Function reads object, creates thumbnail, saves to target bucket

  • AWS Lambda quotas:

    • Soft limits per Region:
      • Concurrent executions = 1,000
      • Function and layer storage = 75GB
    • Hard limits for individual functions:
      • Maximum memory allocation = 10,240MB
      • Function timeout = 15 minutes
      • Deployment package size = 250MB unzipped
      • Container image code package size = 10GB

AWS Lambda provides serverless compute capabilities that automatically scale without server management. It enables you to run code in response to events or on a schedule while only paying for the actual execution time, making it cost-effective for many application patterns.