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In this lesson we cover AWS Lambda — a core building block for serverless, event-driven applications on AWS.

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What is AWS Lambda?

AWS Lambda is a serverless compute service that runs your code in response to events without requiring you to provision or manage servers. You upload your application code, set triggers and configuration (for example, memory and timeout), and AWS handles the underlying infrastructure: capacity provisioning, operating system maintenance, scaling, monitoring, and logging. Because Lambda is serverless, you don’t manage EC2 instances. Instead you tune function-level settings such as memory (which also affects available CPU) and timeout. Lambda automatically scales compute capacity to match incoming request volume, making it a strong fit for workloads that vary widely in demand (for example, e-commerce traffic spikes).

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How Lambda integrates with other services (Triggers)

Lambda’s power comes from tight integrations across the AWS ecosystem. You register an event source (a trigger) and Lambda executes your function when that event occurs. Common triggers include Amazon S3, Amazon API Gateway, DynamoDB Streams, CloudWatch Events (EventBridge), and many others.
  • Example (S3): process uploads, transcode media, or generate thumbnails
    • When a user uploads a file to an Amazon S3 bucket, the S3 PutObject event can trigger a Lambda function to process the file (transcode into 480p/720p/1080p/2K/4K, create thumbnails, extract metadata, etc.). This lets you build media-processing pipelines without managing servers.
A simple AWS Lambda workflow diagram: a file icon goes into an Input S3 Bucket, triggers a Lambda function, and the processed result is stored in an Output S3 Bucket.
  • Example (API): build serverless APIs with Amazon API Gateway
    • Amazon API Gateway receives HTTP requests and routes them to Lambda functions based on path and HTTP method. That combination lets you build RESTful or HTTP APIs without servers; Lambda implements business logic and reads/writes data to databases such as Amazon DynamoDB.
A simple AWS architecture diagram showing users sending requests to Amazon API Gateway, which invokes a Lambda function. The Lambda function then reads/writes data to Amazon DynamoDB.

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Key benefits and features

Below is a concise reference of core Lambda capabilities, benefits, and typical use cases.
A presentation slide titled "Features" with four numbered cards: 01 Serverless, 02 Event-Driven, 03 Language Support, and 04 Fault Tolerance. Each card has a colorful circular icon above its label.
  • Scaling and concurrency
    • Lambda scales automatically as events arrive — new execution environments are created as needed. Each AWS account has default concurrency limits per region; you can request increases or use reserved concurrency for predictable capacity.
  • Billing overview
    • You are billed for the number of requests and the compute duration (measured in GB-seconds). There is no charge when your function is not running. Provisioned Concurrency reduces cold starts but incurs additional cost.
Lambda is ideal for short-lived, event-driven tasks. Be aware of cold starts when scaling from zero and account-level concurrency limits — consider Provisioned Concurrency or reserved concurrency for latency-sensitive workloads.
Lambda provides a scalable, event-driven way to run backend logic without server management, making it a foundational service for modern cloud-native and serverless architectures.

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