How themarck/hermesys works
HermeSys is an edge-to-cloud telemetry pipeline. Its principal workflow publishes readings from a configurable source over MQTT, passes them through Telegraf for validation and metric standardization, streams them through Kafka, and analyzes them in a consumer that maintains current field state and checks configured thresholds. The README also describes downstream data management, but the available tree does not show a corresponding implementation. Telegraf and broker behavior is based on README documentation and configuration filenames; those configuration contents were not sampled.
Main entry points: telegraf.conf Telegraf ingestion · kafka_consumer.py Kafka consumer · docker-compose.yml Kafka stream · producer_energy.py Telemetry producer
Components 12
Data Acquisition
- Telemetry producer
producer_energy.py
Ingestion
- MQTT broker
mosquitto.conf - Telegraf ingestion
telegraf.conf - JSON validation
telegraf.conf - Metric standardization
telegraf.conf
Streaming
- Kafka stream
docker-compose.yml
Telemetry Analysis
- Kafka consumer
kafka_consumer.py - Telemetry state
kafka_consumer.py - Threshold analysis
kafka_consumer.py - Operational information
Other components
- API or dataset
- Data management
Connections 12
- API or dataset → Telemetry producer: supplies readings
- Telemetry producer → MQTT broker: publishes readings
- MQTT broker → Telegraf ingestion: provides telemetry
- Telegraf ingestion → JSON validation: validates JSON
- Telegraf ingestion → Metric standardization: standardizes metrics
- JSON validation → Kafka stream: forwards valid data
- Metric standardization → Kafka stream: forwards metrics
- Kafka stream → Kafka consumer: streams messages
- Kafka consumer → Telemetry state: updates fields
- Kafka consumer → Threshold analysis: checks limits
- Threshold analysis → Operational information: produces status
- Operational information → Data management: supports integration