Optimizing energy consumption analytics using data from AWS IoT Core processed in Lambda and stored in TimestreamPython
Sure! Given your goal, the relevant resources we'll need are:
- AWS IoT Core - We'll define an IoT Topic Rule which sends IoT event data to a particular Lambda function.
- AWS Lambda - A serverless service that can be used to process the IoT data coming from the IoT Core.
- Timestreamwrite Table - A time-series database from AWS, which is good for storing energy consumption data.
Here is a sample Pulumi program which sets up this architecture:
The above program will send data from AWS IoT Core to a Lambda function for processing, and the Lambda function (which you would need to complete) will then store the data in Timestream. Take note that while the function's code property is provided as a string here, it's more likely you'll want to read this from an existing Python file.
Also, this code creates a new Timestream database but you'll need to ensure that the Lambda function has permissions to write data to it. The IAM role attached to the function should have the relevant Timestream write policies attached to do so.
Relevant Pulumi API documentation: