This folder starts with a basic example of integrating put_events into your Personalize Campaigns by using Lambda functions processing new data from S3.
To get started here, first complete the getting_started notebook collection, including the second notebook that creates your initial Event Tracker.
Inside this folder you'll see a notebook Sending_Events_to_S3.ipynb it contains the boilerplate code to send a series of messages to your S3 bucket.
This will be key for using your Lambda function which will then send them to Personalize.
The notebook will now reliabily write files to your S3 bucket, the next task is to build a lambda function to invoke on the S3 trigger. The code for the Lambda is provided inside event_processor.py
First visit the Lambda console then click Create Function, give it any name you like and select Python 3.6 for the runtime.
You will need a new IAM role for this Lambda function, allow a default one first. Later it will be updated to work with Personalize and S3. Next hit Create function
Now click the + Add trigger, search for S3, select your bucket, select All object create events for demo purposes, then for Suffix add .json. Lastly on this page click Add
Next click the icon for your Lamda function, when the editor appears below, copy the contents of event_processor.py into the editor and save it. Replace all the existing content.
Scroll down below the editor and for Environment Variables enter trackingId for a key, and for the value provide your tracking ID from the second notebook.
This is almost ready to go, the last configuration bit is to handle IAM, scroll below until you see Execution role, at the bottom you'll see a link View the .... right click and open that in a new tab.
Click Attach policies, add both AmazonS3FullAccess and AmazonPersonalizeFullAccess then click Attach policy. These configurations are not ideal for security but will illustrate the point. For a production workload create custom policies tailored explicitly to the resources you are working with.
Once attached, close the tab and revisit the Lambda Console page you left. Click Save in the top right corner.
Scroll back to the top, and select Monitoring, then go back to your notebook that simulates the events and execute that cell again to write new files and execute the Lambda function.
After a few seconds you can refresh the page and see the invocations were successful.