AWS Lambda and Serverless Function Patterns

AWS Lambda and Serverless Function Patterns#

Lambda runs your code without you provisioning or managing servers. You upload a function, configure a trigger, and AWS handles scaling, patching, and availability. The execution model is simple: an event arrives, Lambda invokes your handler, your handler returns a response. Everything in between – concurrency, retries, scaling from zero to thousands of instances – is managed for you.

That simplicity hides real complexity. Cold starts, timeout limits, memory-to-CPU coupling, VPC attachment latency, and event source mapping behavior all require deliberate design. This article covers the patterns that matter in practice.

Building an API with Cloudflare Workers and D1: From Zero to Production

Building an API with Cloudflare Workers and D1#

This tutorial walks through building a production API on Cloudflare Workers with a D1 database, KV caching, rate limiting, full-text search, and request logging. The patterns come from a real production deployment – not a toy example.

By the end you will have: a TypeScript Worker handling multiple API routes, a D1 database with FTS5 full-text search, KV-based caching and rate limiting, CORS support, request logging with IP hashing for privacy, and a deployment to Cloudflare’s global network.

CDN and Edge Computing Patterns

CDN and Edge Computing Patterns#

A CDN (Content Delivery Network) caches content at edge locations close to users, reducing latency and offloading traffic from origin servers. Edge computing extends this by running custom code at those edge locations, enabling request transformation, authentication, A/B testing, and dynamic content generation without round-tripping to an origin server.

CDN Cache Fundamentals#

Cache-Control Headers#

The origin server controls CDN caching behavior through HTTP headers. Getting these right is the single most impactful CDN optimization.

Cloudflare Workers as a Full-Stack Platform: Workers, D1, KV, R2, and Pages

Cloudflare Workers as a Full-Stack Platform#

Cloudflare started as a CDN and DDoS protection service. It is now a complete development platform. Workers provide serverless compute at 330+ edge locations. D1 provides a serverless SQLite database. KV provides a globally distributed key-value store. R2 provides S3-compatible object storage with zero egress fees. Pages provides static site hosting with git-integrated deploys. Durable Objects provide stateful, single-threaded coordination primitives. Queues provide async message processing between Workers.

Comparing Serverless Platforms: Cloud Run, Azure Functions, Lambda, and Cloudflare Workers

Comparing Serverless Platforms#

Choosing a serverless platform is not about which one is “best.” Each platform makes different tradeoffs around cold start latency, execution limits, pricing granularity, and ecosystem integration. The right choice depends on what you are building, what cloud you already use, and which constraints matter most.

This framework compares the four major serverless compute platforms as of early 2026: AWS Lambda, Google Cloud Run, Azure Functions, and Cloudflare Workers.

Knative: Serverless on Kubernetes

Knative: Serverless on Kubernetes#

Knative brings serverless capabilities to any Kubernetes cluster. Unlike managed serverless platforms, you own the cluster – Knative adds autoscaling to zero, revision-based deployments, and event-driven invocation on top of standard Kubernetes primitives. This gives you the serverless developer experience without vendor lock-in.

Knative has two independent components: Serving (request-driven compute that scales to zero) and Eventing (event routing and delivery). You can install either or both.

Lightweight Kubernetes at the Edge with K3s

Lightweight Kubernetes at the Edge with K3s#

K3s is a production-grade Kubernetes distribution packaged as a single binary under 100 MB. It was built for environments where resources are constrained and operational simplicity matters: edge locations, IoT gateways, retail stores, factory floors, branch offices, and CI/CD pipelines where you need a real cluster but cannot justify the overhead of a full Kubernetes deployment.

K3s achieves its small footprint by replacing etcd with SQLite (by default), embedding containerd directly, removing in-tree cloud provider and storage plugins, and packaging everything into a single binary. Despite these changes, K3s is a fully conformant Kubernetes distribution – it passes the CNCF conformance tests and runs standard Kubernetes workloads without modification.