Near Real-Time IoT Data Insights with Open Source Tools on AWS | S02 EP42 | Lets Talk About Data

The show focused on leveraging AWS services to ingest and process real-time smart meter data. The guests walked through an architecture using AWS IoT Core to receive time series data from devices, with the messages then flowing through Amazon MSK (Managed Streaming for Apache Kafka) and Amazon Managed Apache Flink for transformation and analysis. The transformed data is loaded into Amazon Timestream, a time series database, and then visualized in real-time with Amazon Managed Grafana. An anomaly detection model is also trained in Amazon SageMaker to find unexpected patterns in the data.

The presenters also demonstrated additional capabilities like using Amazon QuickSight's natural language processing to generate executive data summaries and visualizations. Viewer questions touched on ensuring data quality, connecting devices to AWS IoT Core, leveraging different database options.

Highlights:

- AWS IoT Core used as scalable gateway to receive and route messages from connected devices

- Open source Amazon MSK and Amazon Managed Apache Flink services used for streaming, transforming, and analyzing real-time data

- Transformed data stored in time series optimized Amazon Timestream database

- Real-time monitoring and anomaly detection enabled through integrated dashboard visualizations in Amazon Managed Grafana

- Machine learning models for forecasting and detecting anomalies trained in Amazon SageMaker

Ibrahim Emara, RDS Specialist Solutions Architect @ AWS

Arun Sankaranarayanan Specialist Solutions Architect - Database @ AWS

Gabrielle Dompreh GenAI/AI/ML Solutions Architect @ AWS