| ID | product.processing |
|---|---|
| Description | Real-time and batch processing of telemetry. |
| Key | processing |
| Type | system |
| Team | Stream Processing |
| Owner | stream-processing@iotgateway.example |
| Status | active |
| Technologies | Apache Flink, Apache Spark, Kafka |
| Attributes | latency: <2s, throughput: 1M events/s |
| Tags |
Stream Processing is where raw telemetry becomes useful. It runs the real-time pipelines that power live dashboards and alerts, and the nightly batch jobs that produce curated, query-ready datasets for analytics.
Responsibility in one sentence
Consume the telemetry firehose, compute aggregates and anomalies in near real time, and archive curated history to object storage.
Could not build diagram for model "example-iot".
The alert pipeline is driven end-to-end by the streaming side of this system:
2 incoming links · 2 outgoing links
| Source object | Label | Link type | Relation | Raw id | Required | Description | |
|---|---|---|---|---|---|---|---|
| builds pipelines in | — | links | product.processing | — | — | ||
| feeds | — | links | product.processing | — | — |
| Target object | Label | Link type | Relation | Raw id | Required | Description | |
|---|---|---|---|---|---|---|---|
| feeds dashboards in | — | links | product.user_facing | — | — | ||
| archives to | — | links | external_systems.object_storage | — | — |