Designing a logistics optimization platform using AWS Lambda, Amazon Aurora, and real-time analytics with KinesisTypeScript
The program consists of four parts:
Part 1: Set up an AWS RDS Aurora database. This will store your logistics data.
Part 2: Create an AWS Kinesis Data Stream. This will be used to ingest real-time logistics data.
Part 3: Create an AWS Lambda function. This function will read data from the Kinesis Stream, process it, and store it in the Aurora database for analytics.
Part 4: Define an Event Source Mapping to trigger the Lambda function whenever new data is added to the Kinesis Stream.
Here is the pulumi program:
Notes & Assumptions
You'll need to replace the placeholder values for
<password>, and the path to your lambda function handler file code in the
This setup uses NodeJS runtime for AWS Lambda. If you're using a different runtime, please update
handler: "lambda-handler.handler"to reflect your actual setup.
IAM Policies and instance classes are placeholders. Modify them based on your requirements.
This is a base setup. For a production setup, consider enabling encryption, setting up backups, and adjusting capacity based on expected load.