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Amazon Web Services (AWS)

Beginner’s Guide to Writing AWS Lambda Functions in Python

Published by Pearson

Intermediate content levelIntermediate

AWS Lambda functions are the building blocks for creating sophisticated applications and services on AWS. In this online training you will use Python to develop Lambda functions that communicate with key AWS services, including: API Gateway, SQS, and Cloudwatch functions. You will also learn how a new cloud-based development environment, Cloud9, can streamline writing, debugging and deploying AWS Lambda functions.

One of the emerging cloud-native trends is serverless. This training covers real-world examples of how to run code without thinking about servers. Some of the benefits of programming with AWS Lambda in Python include: no servers to manage, continuous scaling, and subsecond metering. Several use cases include: data processing, stream processing, IoT backends, mobile, and web applications.

What you’ll learn and how you can apply it

  • Developing with Cloud9
  • Writing AWS lambda functions in Python
  • Implementing Cloud-native Data Engineering patterns, i.e. serverless
  • Architecting event driven architectures on the AWS platform using: SQS and Python Lambda

This live event is for you because...

  • You work with data and want to learn cloud-native data engineering patterns
  • You are new to the AWS Cloud and want to learn to write functions in Python that do not require servers
  • You are a Data Scientist who needs a simpler way to get Data Engineering results
  • You want to learn about serverless technology and how to accomplish it in Python

Prerequisites

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Part 1: Using Cloud9 to Develop Python Lambda Functions(Length: 90 min)

  • Developing with Cloud9
  • Launching Cloud9 and Workspace Configuration
  • Creating and Deploying Lambda functions
  • Importing Lambda functions
  • Invoking Lambda functions
  • Invoking Lambda function inside API Gateway

Q&A (15 min) Break (15 min)

Part 2: Creating Timed Lambdas (Length: 45 min)

  • Using AWS Lambda with Cloudwatch Events
  • Using AWS Lambda to populate AWS SQS (Simple Queuing Service)
  • Using AWS Cloudwatch logging with AWS Lambda

Q&A (10 min) Break (5 min)

Part 3: Creating Event Driven Lambdas (Length: 45 min)

  • Triggering AWS Lambda with AWS SQS Events
  • Reading AWS SQS Events from AWS Lambda
  • Writing results to AWS DynamoDB

Q&A (15 min)

Your Instructor

  • Noah Gift

    Noah Gift is lecturer and consultant in both the UC Davis Graduate School of Management’s MSBA program and Northwestern’s graduate data science program, MSDS, where he teaches and designs graduate machine learning, AI, and data science courses and consults on machine learning and cloud architecture for students and faculty. These responsibilities include leading a multicloud certification initiative for students. He’s the author of close to 100 technical publications, including two books on subjects ranging from cloud machine learning to DevOps. Noah has approximately 20 years’ experience programming in Python. He’s a Python Software Foundation Fellow, an AWS Subject Matter Expert (SME) on machine learning, an AWS Certified Solutions Architect and AWS Academy Accredited Instructor, a Google Certified Professional Cloud Architect, and a Microsoft MTA on Python. Over his career, he’s served in roles ranging from CTO, general manager, and consulting CTO to cloud architect at companies including ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios, and Linden Lab. In the last 10 years, he’s been responsible for shipping many new products that generated millions of dollars of revenue and had global scale. Currently, he’s consulting startups and other companies. Noah holds an MBA from UC Davis, an MS in computer information systems from Cal State Los Angeles, and a BS in nutritional science from Cal Poly San Luis Obispo.