A real-time grid pipeline playbook for Heads of Data Platform - Kafka as the event backbone, Flink for stateful stream processing, and the operational discipline that makes the difference between a streaming platform that runs and one that pages.
Every grid signal lands in Kafka. SCADA, PMU, AMI, weather, market signals - one ingestion contract, one source of truth, one place every downstream workload subscribes to.
Flink handles the windowed aggregations, anomaly detection features, and joins between streams. Flink jobs are version-controlled, deployed with explicit checkpointing, and monitored with watermark-aware metrics.
Some workloads need exactly-once semantics - settlement-relevant aggregations, regulatory reporting feeds, customer-facing alerts. Others tolerate at-least-once. Choosing per workload keeps the platform fast where it can be and correct where it must be.
Every grid signal lands in Kafka. SCADA, PMU, AMI, weather, market signals.
Flink handles the windowed aggregations, anomaly detection features, and joins between streams. Flink jobs are version-controlled, deployed with explicit checkpointing, and monitored with watermark-aware metrics.
Some workloads need exactly-once semantics. Settlement-relevant aggregations, regulatory reporting feeds, customer-facing alerts.
Migrate the batch use cases that benefit most from real-time first. Build the operational runbook - watermark drift, backpressure, checkpoint recovery - that the on-call team will use at 3 a.m.
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