Explanation:
To enable the Cloud Dataflow pipeline to scale its compute power dynamically based on workload, updating D. The maximum number of workers is essential. This setting allows Cloud Dataflow to automatically adjust resources, efficiently managing increased data flows as MJTelco expands beyond 50,000 installations. It supports their requirement for a flexible, cost-effective solution to oversee their distributed telecom user community and extensive data pipelines.
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MJTelco, a startup with innovative optical communications hardware patents, is scaling its proof-of-concept (PoC) to support over 50,000 installations. They aim to refine their machine-learning models and maintain three separate operating environments: development/test, staging, and production. Given their need to dynamically scale compute power for their Google Cloud Dataflow pipeline as data flows increase, which configuration setting should be updated?
A
The zone
B
The disk size per worker
C
The number of workers
D
The maximum number of workers
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