Google Professional Machine Learning Engineer
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In the context of designing a real-time analytics platform for a global e-commerce website, which Google Cloud service is the most suitable for creating and managing a high-throughput, low-latency streaming data pipeline that can process millions of events per second with minimal operational overhead? Consider the need for auto-scaling, fault tolerance, and the ability to handle both batch and streaming data within the same pipeline. Choose the best option from the following:
Explanation:
Dataflow is the correct choice because it is specifically designed for building and managing both batch and streaming data pipelines with features like auto-scaling and fault tolerance, making it ideal for real-time data processing. Pub/Sub is also a correct choice for event ingestion at scale, but it requires integration with other services like Dataflow for processing, hence it's the second correct option. BigQuery is not suitable for real-time processing, Cloud Storage lacks processing capabilities, and Dataproc is optimized for batch processing, not streaming.