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GCP Professional Data Engineer Practice Question

Your company ingests IoT telemetry at 30 000 messages per second via Cloud Pub/Sub. A streaming Dataflow job in us-central1 transforms the data and writes to a BigQuery dataset also in us-central1. The business requires that if the entire us-central1 region becomes unavailable, no more than 60 seconds of data may be lost (RPO ≤ 1 minute) and processing must resume in another region within 15 minutes (RTO ≤ 15 minutes) without manual code changes. Which design meets these objectives with the least operational overhead?

  • Modify the existing Dataflow job to enable drain-and-restore, set a 60-second checkpoint interval, and rely on BigQuery regional redundancy for protection.

  • Enable Pub/Sub topic replication to us-east1 and use a Cloud Composer DAG that launches the Dataflow template in us-east1 when a regional health check fails; keep the dataset in a us-east1 regional BigQuery location.

  • Create a second pull subscription to the Pub/Sub topic and deploy an identical streaming Dataflow Flex Template in us-east1 writing to a multi-region BigQuery dataset; run both pipelines continuously with idempotent writes.

  • Configure the job to autoscale across all zones in us-central1 and snapshot state to a dual-region Cloud Storage bucket every minute; redeploy the template manually in another region during an outage.

GCP Professional Data Engineer
Designing data processing systems
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