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Beginner’s Guide to Writing AWS Lambda Functions in Python

Noah Gift

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 training course 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

About your instructor

  • Noah Gift is a lecturer in the University of California, Berkeley, graduate data science program, the Northwestern University graduate data science program, and the MSBA program at the University of California, Davis, Graduate School of Management. He consults with startups and other companies on machine learning and cloud architecture and does CTO-level consulting as the founder of Pragmatic AI Labs. Noah has approximately 20 years’ experience programming in Python and is a Python Software Foundation Fellow. Previously, he worked for a variety of companies in roles such as CTO, general manager, consulting CTO, and cloud architect. He’s published over 100 technical publications, including books on cloud machine learning and DevOps, for O’Reilly, Pearson, DataCamp, Udacity, and other publishers. He’s also a certified AWS Solutions Architect. Noah earned an MBA from the University of California, Davis, an MS in computer information systems from California State University, Los Angeles, and a BS in nutritional science from Cal Poly, in San Luis Obispo. You can find more about Noah by following him on GitHub, visiting his website, or connecting with him on LinkedIn.

Schedule

The timeframes 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)