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Coursera

Rust Serverless

Pragmatic AI Labs via Coursera

Overview

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Build production-grade AWS Lambda functions in Rust using Cargo Lambda. This hands-on course covers serverless fundamentals — stateless event handlers, millisecond billing, and managed runtimes that scale on demand — then implements the same S3-triggered handler in Python, Ruby, Node.js, and Rust so you can compare runtimes head-to-head. You will install Cargo Lambda, scaffold a new Lambda crate with cargo lambda new, iterate locally with cargo lambda watch, invoke against test payloads with cargo lambda invoke, produce a release binary with cargo lambda build --release, and ship to AWS with cargo lambda deploy. Along the way you will see why Rust's compile-time guarantees, ownership model, and small memory footprint make it a strong fit for AWS Lambda's pay-per-millisecond pricing. The closing module benchmarks all four runtimes on the same workload across memory configurations from 128 MB to 10,240 MB, so you can reason about price and performance trade-offs from real measurements rather than vendor claims. By the end, you will have shipped a working Rust Lambda from cargo lambda new to a deployed AWS endpoint and know when Rust is the right tool for serverless data engineering.

Syllabus

  • Week 1: Introduction to Serverless Computing and AWS Lambda
    • Covers instructor, career arc, course intent, the lightbulb analogy, and stateless event handlers.
  • Week 2: Hands-on with AWS Lambda - Multi-language Implementation
    • Covers managed runtime, millisecond billing, service integration, create function, and inline editor and Deploy.
  • Week 3: Rust and Cargo Lambda - Elevating Serverless Development
    • Covers cargo lambda, no Docker required, the four core commands, install paths, and cargo lambda new + watch.
  • Week 4: Advanced Cargo Lambda and Serverless Performance Optimization
    • Covers match-based dispatch, rand::Rng + serde, tunnel.sh wrapper, memory profile, and duration profile.

Taught by

Noah Gift

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