awslambda_stepfunc.txt

https://github.com/ACloudGuru-Resources/content-processing-serverless-data-aws-lambda/tree/main
{
  "Comment": "Rewards Processor State Machine",
  "StartAt": "AssessStudent",
  "States": {
    "AssessStudent": {
      "Type": "Choice",
      "Choices": [
        {
          "Variable": "$.Score",
          "NumericGreaterThan": 74,
          "Next": "UnlockPremiumCourses"
        },
        {
          "Variable": "$.Score",
          "NumericLessThan": 75,
          "Next": "UnlockPremiumLessons"
        }
      ]
},

    "UnlockPremiumCourses": {
      "Type": "Task",
      "Resource": "Insert the ARN of your UnlockPremiumCoursesFunction",
      "End": true
    },
    "UnlockPremiumLessons": 
    {
      "Type": "Task",
      "Resource": "Insert the ARN of your UnlockPremiumLesson",
      "End": true
    }
  }
}


log in to the AWS Management Console using the credentials provided on the lab instructions page. Make sure you're using the us-east-1 Region.

Set Up S3
Navigate to the S3 console by searching for and selecting S3 in the top search bar, or selecting it from Recently Visited.
On the right, click Create bucket.
Under Bucket name, enter miths-rewards-datafeed followed by some characters to make it unique.
Leave the other settings at default, and click Create bucket.
Under Buckets, click on the miths-rewards-datafeed bucket.
Under Objects, click Create folder.
Under Folder name, enter miths-premium-courses.
Click Create folder.
Click Create folder again; under Folder name, enter miths-premium-lessons.
Click Create folder.
Populate the Buckets with CSV Files
To populate the buckets with the CSV files, navigate to the GitHub repository and download the CSV files.
Note: If necessary, review the How to Download a CSV from GitHub page.

Click on the miths-premium-courses folder.
In the upper right corner, click Upload.
Next to Files and folders, click Add files.
Select the premium-courses.csv file, and click Open.
Click Upload.
In the upper right corner, click Close.
In the upper left breadcrumb trail, click on your bucket name.
Under Objects, click miths-premium-lessons.
In the upper right corner, click Upload.
Next to Files and Folders, click Add files.
Select the premium-lessons.csv file, and click Open.
Click Upload.
Create the Lambda Functions
Create the First Lambda Function
In the search bar at the top, search for and select Lambda.
In the upper right corner, click Create function.
Under Create function, ensure Author from scratch is selected.
Under Basic information, set the following values:
Function name: Enter UnlockPremiumCourses.
Runtime: Select Python 3.9.
Architecture: Select x86_64.
Leave the other settings at default, and click Create function; this may take a few minutes.
Once the function is created, under Code source > lambda_function, delete the code and paste in the code found in the GitHub repository under unlock_premium_courses_lambda_function.
Update the bucket name on line 4 to match your bucket name (e.g., miths-rewards-datafeed).
At the top, click Deploy to save the changes.
Toward the top, under Function overview, click Layers.
Next to Layers, click Add a layer.
Under Choose a layer, set the following values:
Layer source: Ensure AWS layers is selected.
AWS layers: Select AWSSDKPandas-Python39.
Version: Select the available version.
Click Add.
Under Function overview, on the right, copy the function ARN and paste it in a separate text file for use later.
Create the Second Lambda Function
In the upper left breadcrumb trail, click Functions.
In the upper right corner, click Create Function.
Under Create function, ensure Author from scratch is selected.
Under Basic Information, set the following values:
Function name: Enter UnlockPremiumLessons.
Runtime: Select Python 3.9.
Architecture: Select x86_64.
Leave the other settings at default, and click Create function; this may take a few minutes.
Toward the top, under Function overview, click Layers.
Next to Layers, click Add a layer.
Under Choose a layer, set the following values:
Layer source: Ensure AWS layers is selected.
AWS layers: Select AWSSDKPandas-Python39.
Version: Select the available version.
Click Add.
Under Code source > lambda_function, delete the code and paste in the code found in the GitHub repository under unlock_premium_lessons_lambda_function.py.
Update the bucket name on line 4 to match your bucket name.
At the top, click Deploy to save the changes.
Under Function overview, on the right, copy the function ARN and paste it in a separate text file for use later.
Grant Functions Access to S3
Click on the Configuration tab.
In the left navigation menu, under General configuration, click Permissions.
Under Execution role, click on the listed role name.
Next to Permissions policies, click on the Add permissions dropdown menu and select Attach policies.
In the upper right corner, click Create policy.
In the Visual editor tab, click on Service to expand the menu.
In the search bar, search for and select S3.
Expand the Actions menu. Under Access level, expand the List sub-menu, and select ListBucket.
Expand the Read sub-menu, and select GetObject.
Expand the Resources menu.
Next to bucket, click on the Add ARN hyperlink.
In the Add ARN(s) pop-up menu, next to Bucket name, enter the name of your bucket.
Copy your bucket name, then click Add.
Next to object, click on the Add ARN hyperlink and set the following values:
Bucket name: Paste in your bucket name.
Object name: Select Any.
Click Add.
Click Next until you get to Create policy.
Next to Name, enter ReadS3RewardsDatafeed; copy ReadS3RewardsDatafeed for later.
Click Create policy.
Attach Policies
In the left navigation menu under Access management, click Roles.
In the Roles search bar, enter courses.
Click on the UnlockPremiumCourses role.
Next to Permissions policies, click on the Add permissions dropdown menu and select Attach policies.
In the Other permissions policies search bar, paste in ReadS3RewardsDatafeed and press Enter.
Click on the checkbox next to ReadS3RewardsDatafeed.
Click Attach policies.
In the upper left breadcrumb trail, click Roles.
In the Roles search bar, enter lesson, and select the UnlockPremiumLessons role.
Next to Permissions policies, click on the Add permissions dropdown menu and select Attach policies.
In the Other permissions policies search bar, paste in ReadS3RewardsDatafeed and press Enter.
Click on the checkbox next to ReadS3RewardsDatafeed.
Click Attach policies.
Set Up IAM Roles
In the left navigation menu, under Access management, click Roles.
In the upper right corner, click Create role.
Under Trusted entity type, ensure AWS service is selected.
Under Use case, beneath Use cases for other AWS services, click on the dropdown menu and select Step Functions (in the search bar, you can search Step Functions).
Underneath the Step Functions dropdown menu, click on the radio button next to Step Functions.
Click Next.
Under Permissions policies, click on the + icon next to AWSLambdaRole to confirm the Step Functions can invoke Lambda.
Click Next.
Under Role details > Role name, enter StepFunctionsInvokeLambdaRole.
Leave the other settings at default, scroll down, and click Create role


Set Up AWS Step Functions
In the search bar at the top, search for and select Step Functions.
Under Get started on the right, click Get started.
In the line of text under Review Hello World example, click on the here hyperlink.
Under Choose authoring method, select Write your workflow in code.
Under Definition, delete the code and paste in the code found in the GitHub repository under state-machine-code.json.
Scroll down to line 23, and replace Insert the ARN of your UnlockPremiumCoursesFunction with the corresponding ARN you previously pasted in the separate text file.
On line 29, replace Insert the ARN of your UnlockPremiumLesson with the corresponding ARN you previously pasted in the separate text file.
Click Next.
Under Name, enter RewardsProcessorStateMachine.
Under Permissions, select Choose an existing role.
Leave the other settings at default, and click Create state machine.
Test the Step Functions
In the upper right corner, click Start execution.
In the Start execution pop-up menu, under Input, update the following values:
Highlight and delete Comment, then type Score.
Highlight and delete "Insert your JSON here", then type 30.
Click Start execution.
Under Graph view, click on the UnlockPremiumLessons button.
To the right of Graph view, ensure the Input and output provides the correct output (i.e., the state machine triggers the Lambda function that returns the premium lessons).
In the upper right corner, click New execution.
In the Start execution pop-up menu, replace 30 with 80.
Click Start execution.
Under Graph view, click on the UnlockPremiumCourses button.
To the right of Graph view, ensure the Input and output provides the correct output (i.e., the state machine triggers the Lambda function that returns the premium courses).
Conclusion