Serverless Computing

Learning Objectives Define Serverless Computing and distinguish it from traditional server-based architectures. Explain the core principles of Function as a Service (FaaS), including event-driven execution and statelessness. Analyze the primary benefits and drawbacks of serverless architectures, such as scalability, cost-efficiency, and cold starts. Identify at least three common use cases for serverless computing in real-world applications. Diagram a simple serverless workflow, connecting an event source, a function, and a downstream service. Describe the pay-per-execution cost model and its implications for application design. Imagine your app suddenly gets a million users overnight. 🤯 How could you handle that traffic instantly without ever touching a server? This lesso...

TermDefinitionExample Serverless ComputingA cloud computing execution model where the cloud provider dynamically manages the allocation and provisioning of servers. Developers write and deploy code in small, discrete units (functions) without worrying about the underlying infrastructure.You write a Python function to process a payment. Instead of deploying it on a server that runs 24/7, you upload it to a service like AWS Lambda. The function only runs when a customer clicks 'Buy Now' and you only pay for the milliseconds it's active. Function as a Service (FaaS)The core component of serverless computing. It's a category of cloud services that provides a platform for customers to develop, run, and manage application functionalities without the complexity of building an...

The Event-Trigger-Function Pattern Event Source -> Trigger -> Function Execution This is the fundamental execution model. An event (like an HTTP request or a file upload) from a source (like an API Gateway or a storage bucket) acts as a trigger, which invokes a specific function to run its logic. The Principle of Stateless Design Functions must not store persistent data locally. State must be externalized. Since any function instance can be destroyed after execution, you cannot rely on in-memory variables or local file systems to persist data between invocations. All state must be read from and written to an external, durable service like a database (e.g., DynamoDB) or object storage (e.g., S3). Pay-Per-Execution Cost Model Cost = (Number of Invocations * Price p...