AWS SAM Framework and AWS Lambda - A Complete Hands-on Guide

Create your first AWS Lambda function in the AWS management console, test it with a sample event, monitor invocations and logs, deploy changes, and delete the function as needed.

Set up an ada profile in identity and access management, create a serverless admin user with programmatic access, attach administrator permissions, and configure credentials via serverless config credentials.

Set up your development environment by installing VS Code, the AWS toolkit, and Docker, download and configure credentials for an admin user, and prepare SAM to use these credentials.

Install Node.js across macOS, Windows, and Linux using the provided commands. Verify the installation by running node --version, then exit the shell.

Learn to run AWS Lambda locally for testing with Visual Studio Code and the AWS Toolkit, enabling local invocation, debugging, and Docker-based testing with event payloads and environment variables.

Follow the AWS CLI version 2 installation guide to install and verify the AWS CLI on macOS, Linux, or Windows, including credentials setup, path configuration, and testing with aws help.

Verify your AWS credentials by running aws sts get-caller-identity, locate and configure credentials in your profiles, and run aws configure to input the access key id and secret key.

Install and verify Docker using the docker desktop installer on Mac, Windows, or Linux, then run a terminal check to ensure docker is running for local lambda execution.

Install the AWS sam cli, set up docker, and create a sam application in vs code to define, test, and deploy serverless apps locally and remotely.

Learn how AWS SAM defines serverless apps with a YAML template, deploy via CloudFormation, and manage Lambda functions and apps locally and in the cloud using the SAM CLI.

Create your first serverless hello world API using AWS SAM and Lambda, set up an API gateway endpoint, and test locally with Docker before deploying to the cloud.

Deploy your AWS SAM app to the cloud with a guided deploy, provisioning resources and packaging artifacts to S3. Create and test a Lambda-backed API gateway endpoint via CloudFormation.

Learn to host and test your AWS serverless API locally with SAM local start-api, rebuild after changes, and verify endpoints on localhost:3000 before deploying to the cloud.

Invoke your lambda function directly with sam local invoke, using function name from template.yaml and an event JSON. View logs showing request IDs, memory size, status code, and response body.

Delete the AWS SAM app stack with CloudFormation delete-stack in us-east-1, then verify backend cleanup by refreshing and confirming the Lambda function is no longer present.

Built and deployed a serverless app with AWS SAM and Lambda, tested locally with Docker, and now explore building the same app in VS Code with the AWS Toolkit extension.

Discover creating a serverless AWS SAM app in VS Code with the AWS toolkit, run locally and in the cloud, and compare the hello world function and CLI workflow.

Deploy a SAM application to AWS Cloud using the serverless toolkit, selecting a region and an S3 bucket, then create a Hello World Lambda and REST API gateway endpoint.

Learn to run and debug AWS Lambda functions locally from your project using AWS SAM, Docker, and a cloud formation-based debug configuration, producing a 200 response with hello world.

Create and test a serverless project with the AWS toolkit extension, deploy to the cloud, and verify functionality locally and in the cloud.

Explore how to create Lambda functions with any runtime using AWS SAM, choosing templates and runtimes, and inspect the generated project structure, build outputs, and CloudFormation templates.

Learn the essentials of YAML syntax, including key-value pairs, nested objects, arrays, multi-line strings, and anchors, to model data and compare YAML with JSON.

Explain concepts of AWS Lambda, events and triggers, resources, and services in the AWS SAM framework, and illustrate how S3 events trigger Lambda to generate a thumbnail and update DynamoDB.

Explore the AWS SAM workflow to configure AWS Lambda timeouts and memory allocation, define multiple functions, override global settings per function, and deploy and test the results.

Configure IAM permissions for Lambda functions to access services like S3 and MDB, grant IAM policies, and deploy SAM templates to enable listing functions and prevent access denied errors.

Explore how environment variables provide external, runtime configuration for lambda functions, enabling behavior changes without code edits, including global and per-function overrides in sam templates.

deploy lambda functions in a VPC by selecting subnets and security groups, and verify the VPC execution role to ensure correct permissions.

Learn how to delete an aws sam stack using the sam delete command, which cleans up cloud formation resources and prevents unnecessary charges.

Explore how aws sam templates simplify infrastructure by transforming into CloudFormation resources like lambda functions, iam roles, api gateway, and dynamodb.

Understand AWS Lambda pricing, including free 1 million requests and $0.20 per million after, with 100 ms duration billing. Tune memory to optimize gigabyte seconds of compute and see costs.

Explore sam templates in greater depth by examining resource types, anatomy, components, and specifications. Understand template anatomy and the resource properties that define serverless applications.

Explore the anatomy of a SAM template, focusing on the required transform declaration, optional globals, and the resources, parameters, and outputs that define serverless apps.

Explore AWS SAM resource types and how SAM templates declare resources that CloudFormation converts into real services. Learn to define a simple table with keys, provisioned throughput, and tags.

Learn how AWS Step Functions orchestrate data workflows using state machines and tasks, build visual, low-code workflows, and connect Lambda functions and other services for automated, scalable processes.

Explore creating a step function workflow using the hello world template, design or code your state machine, configure execution roles, run a sample start execution, and view the execution history.

Edit the state machine in workflow studio, add a wait state named silence to delay the flow, and route from hello to world to demonstrate step functions orchestration.

Learn how to make a wait state in AWS Step Functions read a dynamic wait time from input, using a seconds path, and debug input-output to avoid hardcoding.

Explore how the AWS Step Functions choice state enables branching logic based on input within a state machine, using dinner and food type examples.

Learn how a task state in AWS Step Functions invokes a Lambda function to process input and produce output, with hands-on examples using the Serverless Framework and AWS SAM.

Create and test AWS step functions with the SAM CLI and VS Code, exploring state machines and ASL graphs, downloading the definition, and running executions to verify outcomes.

Create a step function state machine from a template in VS Code with the AWS toolkit, render graph, publish to Step Functions, and run executions to observe success or failure.

Update and test a state machine locally, adjust next transitions and wait times, preview changes with IntelliSense, publish quick updates, and verify with true or false inputs before pushing.

Explore step functions by testing state machines locally, using templates and graph visualizations to see ASL flow, and deploy your own function with the S toolkit extension.

Set up a SAM project to create a thumbnail function, configure timeouts and memory, wire an S3 event, and add policies to grant S3 permissions.

Set up a thumbnail generator with aws sam and lambda, read thumbnail size from environment variables, and process s3 events to resize images and upload thumbnails back to s3.

Deploy a python thumbnail service with aws sam, review the created lambda, iam roles, and s3 bucket, then use cloudwatch logs to diagnose a pil import error and iterate.

Explore how to add a layer dependency to an AWS Lambda function using AWS SAM, including finding Pillow layers, handling region and runtime versions, and debugging thumbnail generation.

Learn to create and configure a DynamoDB table for image metadata, expose it via API Gateway, and connect S3, Lambda, and environment variables for put and scan operations.

Explore policy templates in the AWS SAM framework to grant lambda permissions with compact DynamoDB policies, pass table names, and simplify read, create, and update actions for secure access.

Implement dynamo db crud policy to save thumbnail metadata to the images dynamo table during thumbnail creation, recording url, size, and timestamps for each upload.

Create a list thumbnails function with AWS SAM to read thumbnail metadata from DynamoDB, expose it via a REST API gateway, deploy, and test to return thumbnail URLs.

Create a get thumbnail function in an AWS SAM project and read the item from DynamoDB by id via API gateway.

Perform a thorough cleanup by deleting the backend project, then empty the S3 bucket hosting thumbnails and retry deletions until the thumbnail service is fully removed.

Implement a delete item operation using a Lambda to remove an item by id in DynamoDB, returning a delete confirmation payload and optionally securing with an API key.

Conclude by illustrating how S3 triggers Lambda to generate thumbnails, stores them in S3, and saves metadata in DynamoDB, exposed via a rest api.