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.
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Stateful Flink pipelines for windowed aggregates and anomaly detection.
Daily Spark jobs that build curated datasets and archive history.
The alert pipeline is driven end-to-end by the streaming side of this system: