Updated July 2026

AWS Lambda with Python

Class Duration

14 hours of live training delivered over 2 days.

Student Prerequisites

Some prior Python experience, such as writing basic scripts, functions, and classes
Professional programming experience, in Python or another language
Comfort with the command line and installing developer tools
No prior AWS Lambda or serverless experience required

Target Audience

Experienced programmers with some Python experience who are new to AWS Lambda
Teams adopting serverless Python on AWS who want a fast, practical ramp
For the Microsoft cloud instead, see Azure Functions with Python

Description

This fast-paced, two-day course is built for experienced programmers who have some Python experience and are new to AWS Lambda. The first part of the course consolidates the modern Python skills that serverless work relies on: its syntax and object model, environments and tooling, functions and type hints, working with data and JSON, and error handling, logging, and testing. Building on that foundation, the course moves to serverless development on AWS Lambda: writing handler functions in Python, wiring them to event sources such as API Gateway, S3, and SQS, packaging code and dependencies, deploying with infrastructure as code, and operating functions in production with logging, tracing, and performance tuning. Because participants already know how to program, the pace stays brisk and the focus stays on what is genuinely different about Python and about building on Lambda.

Learning Outcomes

Read and write idiomatic Python and apply its object model and core data types.
Set up Python environments and manage dependencies with modern tooling.
Use functions, modules, type hints, and dataclasses to structure Python code.
Work with JSON, files, and HTTP from Python.
Handle errors, add logging, and write unit tests with pytest.
Explain the AWS Lambda execution model, runtimes, limits, and pricing.
Build Python Lambda functions with handlers, events, context, and configuration.
Connect Lambda functions to event sources such as API Gateway, S3, SQS, and EventBridge.
Package and deploy Lambda functions using layers, container images, and infrastructure as code.
Operate Lambda functions with CloudWatch logging, tracing, and performance tuning.

Training Materials

All students receive comprehensive courseware covering all topics in the course. Courseware is distributed via GitHub in the form of documentation and extensive code samples. Students practice the topics covered through challenging hands-on lab exercises.

Software Requirements

Students will need a free, personal GitHub account to access the courseware, a recent Python release, the ability to install Python packages, Visual Studio Code with the ability to install extensions, the AWS CLI, and an AWS account with permission to create Lambda functions and related resources.

Training Topics

Python for Experienced Programmers

Python syntax and semantics compared to other languages
Dynamic typing, names, and the object model
Core data types: lists, tuples, dictionaries, sets, and strings
Control flow, comprehensions, and iteration
Writing idiomatic, readable Python

Python Environments and Tooling

Installing Python and managing versions
Virtual environments and dependency management with uv and pip
Project layout and packaging basics
Formatting and linting with ruff
Running and debugging in Visual Studio Code

Functions, Modules, and Type Hints

Defining functions, arguments, and return values
Modules, packages, and imports
Type hints and static checking with mypy
Dataclasses and structured data
Docstrings and code organization

Working with Data and JSON

Dictionaries and JSON serialization
Reading and writing files
Parsing and validating input data
Dates, times, and environment variables
Making HTTP requests from Python

Errors, Logging, and Testing

Exceptions and error-handling patterns
The logging module and structured logs
Writing unit tests with pytest
Mocking external services
Practical debugging techniques

Introduction to AWS Lambda and Serverless

What serverless computing is and when to use it
The AWS Lambda execution model
Supported Python runtimes
Pricing, limits, and quotas
Lambda within the AWS ecosystem

Building Lambda Functions in Python

The handler function, event, and context
Passing input and returning results
Environment variables and configuration
Managing dependencies for Lambda
Reusing connections and initialization code

Triggers and Event Sources

API Gateway and HTTP APIs
S3, DynamoDB, and EventBridge events
SQS and queue-based processing
Scheduled invocations
Understanding event payloads

Packaging and Deployment

Packaging code and dependencies as zip archives
Lambda layers for shared dependencies
Container image based functions
Infrastructure as code with AWS SAM
IAM roles and least-privilege permissions

Observability and Operations

Logging to CloudWatch
Metrics and alarms
Tracing with AWS X-Ray
Error handling, retries, and dead-letter queues
Cold starts and performance tuning