Apache Kafka at Home: A Houseplant Alerting System with ksqlDB

The author built a system to monitor their houseplants' moisture levels using Apache Kafka, Confluent Cloud, Flink, and MongoDB. They created a Raspberry Pi-based system that collects data from capacitive sensors, which are then sent to Kafka topics for processing. The author used ksqlDB to process the data, creating a stream of enriched readings with metadata about each plant. They then created a new table, `houseplant_low_readings`, to store alerts when a plant's moisture level falls below a certain threshold. Finally, they used Confluent Cloud's HTTP Sink Connector to send these alerts directly to their phone via a Telegram bot. The system was successful in sending alerts only when necessary, reducing the need for manual checks on the plants.

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