AWS Lambda Getting Started

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• Path 1: Interactive Web- and API-based Microservices or Applications
  Use AWS Lambda on its own or combined with other AWS services to build powerful web applications, microservices and APIs that help you to gain agility, reduce operational complexity, reduce cost and scale automatically.
  

  STEP 01

  Basic

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  Get Started with Lambda HTTP

  Learn how to build a dynamic web page from a single Lambda function. You will start off by assigning HTTPS endpoints to your Lambda function, which uses a Lambda Function URL to call your function directly without having to learn, configure and operate additional services. This is ideal for single-function microservices.
  

  STEP 02

  Basic

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  Use Lambda with Amazon API Gateway

  Next, you will use Amazon API Gateway to create a REST API and a resource (Amazon DynamoDB). When you call the API through an HTTPS endpoint, API Gateway invokes the Lambda function. This is ideal for microservices with multiple functions, leveraging Amazon API Gateway to map each function to API endpoints, methods and resources.
  

  STEP 03

  Basic

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  Build a Basic Web Application

  Now you are ready to create a simple web application using AWS Lambda, Amazon API Gateway, Amazon DynamoDB, and AWS Amplify Console. You will first build a static web app that renders "Hello World." Then you will learn how to add functionality to the web app so the text that displays is based on a custom input you provide.
  

  STEP 04

  Advanced

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  Build a Multi-Microservice Web Application

  Finally, you'll create a serverless web app with multiple microservices. You will host a static website, manage user authentication and build a serverless backend using AWS Amplify Console, Amazon Cognito, AWS Lambda, Amazon API Gateway, and Amazon DynamoDB.
  

  Reference

  Advanced

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  Reference Architecture

  This web reference architecture demonstrates how to use AWS Lambda in conjunction with other AWS services to build a serverless web app. This repository contains sample code for all the Lambda functions that make up the back end of the application.
  
• Path 2: Data Processing Applications
  Serverless allows you to ingest, process and analyze high volumes of data quickly and efficiently. Learn how to build a scalable serverless data processing solution. Use Amazon Simple Storage Service ( Amazon S3) to trigger for data processing or load machine learning (ML) models from Amazon Elastic File System (EFS) to AWS Lambda to perform ML inference in real time.
  

  STEP 01

  Basic

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  Use an Amazon S3 trigger to create thumbnail images

  Start off by creating a Lambda function and configure a trigger for Amazon S3. For each image file uploaded to an S3 bucket, Amazon S3 invokes a function which reads the image object from the source S3 bucket and creates a thumbnail image to save in a target S3 bucket.
  

  STEP 02

  Intermediate

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  Large-Scale Parallel Data Processing

  Also, learn how to orchestrate large-scale parallel workloads which convert .mp4 and .mov files from S3 into multiple Gif animations for timeline scrubbing. With distributed map from AWS Step Functions, jobs scale up quickly invoking thousands of parallel Lambda functions to complete jobs faster.
  

  STEP 03

  Advanced

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  Serverless Image Processing Hands-on Workshop

  Next, you will learn how to build an image processing workflow in response to an image uploaded to Amazon S3 using a simple, powerful, fully managed service AWS Step Functions together with AWS Lambda, Amazon DynamoDB, and Amazon Simple Notification Service (SNS).
  

  STEP 04

  Advanced

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  Building Scalable Data Processing Applications

  In this blog series, learn more on how to design and deploy serverless applications designed around the Amazon S3-to-AWS Lambda architecture patterns. The solutions presented use AWS services to create scalable serverless architectures, using minimal custom code.
  

  STEP 05

  Advanced

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  Pay as You Go Machine Learning Inference with AWS Lambda

  Learn how to deploy machine learning models for real-time inference using AWS Lambda functions which can now mount an Amazon Elastic File System (EFS). With this, you can create a Lambda function that loads the Python packages and model from EFS, and performs the prediction based on a test event.
  

  Reference

  Advanced

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  Reference Architecture

  This Real-time File Processing reference architecture is a general-purpose, event-driven, parallel data processing architecture that uses AWS Lambda. This architecture is ideal for workloads that need more than one data derivative of an object.
  

• Path 3: Real-Time Streaming Applications

  Streaming data allows you to gather analytical insights and act upon them, but also presents a unique set of design and architectural challenges. Learn how to achieve several general goals of streaming data workloads by using AWS Lambda and Amazon Kinesis to capture the messages, to process and aggregate the records and finally to load the results into other downstream systems for analysis or further processing.
  

  STEP 01

  Basic

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  Use AWS Lambda with Amazon Kinesis

  Amazon Kinesis is a service that makes it easy to collect, process and analyze video and data streams in real-time. You will start off by creating a Lambda function to consume events from a Kinesis stream.
  

  STEP 02

  Advanced

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  Stream Data Processing Hands-on Workshop

  Next, you will build a comprehensive serverless data processing application to process real-time data streams using Amazon Kinesis to create data streams and AWS Lambda to process streams in real-time.
  

  STEP 03

  Advanced

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  Building Serverless Applications with Streaming Data

  Finally, read this blog series to learn how to build a streaming data backend for a home fitness system by using a serverless approach. You will learn key streaming concepts and how to handle these in a serverless workload.
  

  Reference

  Advanced

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  Reference Architecture

  This reference architecture will use AWS Lambda and Amazon Kinesis to process real-time streaming data for application activity tracking, transaction order processing, click stream analysis, data cleansing, metrics generation, log filtering, indexing, social media analysis, and IoT device data telemetry and metering.
  
• Path 4: No use case in mind? Start with AWS Lambda 101

  New to AWS Lambda? Follow along the steps in this path, and build your first functional Lambda function with an event trigger.
  

  STEP 01

  Basic

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  Log into Your AWS Account

  First, log into the AWS Management Console and set up your root account. With the AWS Free Tier, you get 1 million free requests per month.
  

   

  STEP 02

  Basic

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  Your First Lambda Function

  Next, you will be ready to create and deploy a simple serverless Hello World function using the Lambda console, and review your output metrics.
  

  STEP 03

  Basic

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  Set Up Triggers for Lambda

  Finally, set up an event trigger for Amazon S3 that will invoke your Lambda function when an event occurs.