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Answer: Drain the old pipeline, then start the new pipeline.
The correct answer is C: Drain the old pipeline, then start the new pipeline. Draining the old pipeline ensures it processes all existing data in its buffers and watermarks before shutting down, which prevents data loss or inconsistencies. This approach also keeps the latency increase within the acceptable 10-minute threshold. Option B, while saving a snapshot, introduces complexity and potential for data duplication on restart, making Option C more suitable for a smooth transition.
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You recently developed an updated version of a Dataflow streaming data ingestion pipeline, which reads data from Pub/Sub and writes it to BigQuery. The current version of the pipeline that is currently operational in the production environment uses a 5-minute window for processing. Your task is to deploy the new version of the pipeline in such a way that there is no data loss, no creation of inconsistencies, and the processing latency is not increased by more than 10 minutes. What steps should you take to achieve this deployment successfully?
A
Update the old pipeline with the new pipeline code.
B
Snapshot the old pipeline, stop the old pipeline, and then start the new pipeline from the snapshot.
C
Drain the old pipeline, then start the new pipeline.
D
Cancel the old pipeline, then start the new pipeline.