Analytics architecture brief
IoT Sensor Data Lake
A telemetry pipeline for hardware data with attention to storage format, query cost, retention, and latency tradeoffs.
Sensor device
AWS IoT Core rule
IoT Core
Kinesis Data Firehose
Firehose
S3 data lake
S3
Athena SQL queries
Athena
Problem
Hardware telemetry is useful for trend analysis, maintenance, and anomaly review, but it should not require a constantly running database or server.
Design
- IoT Core authenticates devices and receives MQTT messages.
- Rules route accepted messages into Firehose.
- Firehose batches records and can convert JSON into a query-friendly layout.
- S3 stores the durable data lake, and Athena queries it only when analysis is needed.
Tradeoff
Firehose introduces buffering delay, which is fine for analytical storage but not ideal for immediate safety alerts. If real-time action is required, the design should add an event path through Lambda or Kinesis Data Streams.