A streaming migration playbook for Data Engineering Leads moving healthcare workloads to real-time - bounded scope, managed Kafka and Flink, and a one-workload-per-week migration cadence with the batch path running in parallel.
Identify the three to five workloads where streaming matters most. Healthcare typically picks: ED throughput, clinical alerts, eligibility verification, care gap notification, and sepsis prediction. Everything else stays batch until the streaming layer has earned the right to expand.
Deploy a managed Kafka and Flink stack. Confluent Cloud, AWS MSK with Managed Flink, or equivalent. Self-building the streaming infrastructure consumes the entire migration window before any workload ships.
Migrate one workload per week to the streaming stack. Each migration ships behind a feature flag with the batch path still running in parallel, so rollback is one toggle and the team learns the streaming stack in production before it is the only path.
Identify the three to five workloads where streaming matters most. Healthcare typically picks: ED throughput, clinical alerts, eligibility verification, care gap notification, sepsis prediction.
Deploy a managed Kafka and Flink stack. Confluent Cloud, AWS MSK with Managed Flink, or equivalent.
Migrate one workload per week to the streaming stack. Each migration ships behind a feature flag with the batch path still running in parallel.
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