Architecture & Stream Processing Pipeline:
- Goal: Ingest sensor telemetry (temperature, vibration, pressure) from 500,000 IoT devices emitting readings every 2 seconds, detecting anomalies within 5 seconds.
1. Edge Protocol & Ingestion Gateway:
- Devices publish telemetry over lightweight MQTT / CoAP protocols to an MQTT broker cluster (e.g., EMQX) bridged to an API gateway.
- Ingestion gateway authenticates devices via mTLS (mutual TLS certificates), validates schema, and writes raw events into Kafka.
2. Real-Time Stream Processing & Anomaly Detection:
- Apache Flink / Spark Streaming consumes sensor streams using sliding time windows (e.g., 10-second tumbling windows).
- Runs statistical anomaly detection (Z-score, moving averages, or lightweight machine learning inference) against incoming sensor readings.
- If readings cross safety thresholds (e.g., vibration > 3 standard deviations), Flink immediately publishes an alert event to an urgent alerting topic.
3. Tiered Storage:
- Hot Tier: Time-series database (TimescaleDB / ClickHouse) storing recent high-resolution metrics for real-time dashboards.
- Cold Tier: Parquet files compacted and archived to S3 for deep analytical training and compliance auditing.