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Industrial IoT + analytics
Device telemetry through IoT Core’s Rules Engine, dual-written to a hot path (MSK → Lambda → Timestream → CloudWatch) and a cold path (Firehose → S3 lake → Glue + EMR → Redshift → QuickSight).
IoT Core’s account-wide publish quota near saturation, and one ingested message feeding both a real-time and a historical analytics path.
- Throughput: 16,000 req/sec
- First to saturate: Delivery Stream
- Estimated cost: $381k/mo
How it works
- IoT Core
- Fifty thousand devices publishing into one account-wide quota. This is deliberately run close to that ceiling, because that ceiling, not compute, is what stops a fleet from growing.
- Telemetry Stream
- The hot path. Kafka rather than a queue because the same telemetry is replayed by more than one consumer and messages have to stay in order per device.
- Live Metrics
- Recent readings stay in memory for twelve hours and then age down to cheap magnetic storage automatically. That tiering is the reason to use a time-series store instead of a general database.
- Delivery Stream
- The cold path gets the same messages, buffered for a minute before landing. Nobody is waiting on this, so batching wins over latency here.
- Telemetry Lake
- Full-fidelity history, kept because the question you will want to ask in a year has not been thought of yet.