This architectural diagram depicts a system that streams data from thousands of devices. You want to ingest data into a pipeline, store the data, and analyze the data using SQL statements. Which…

The correct answer is D. 1. Pub/Sub. The canonical Google Cloud streaming architecture follows this pattern: (1) Pub/Sub - a fully managed, scalable message broker used to reliably ingest high-volume event streams from thousands of devices without data loss; (2) Dataflow - a managed Apache Beam service that…

Designing and Implementing Data Processing Solutions

Question

This architectural diagram depicts a system that streams data from thousands of devices. You want to ingest data into a pipeline, store the data, and analyze the data using SQL statements. Which Google Cloud services should you use for steps 1, 2, 3, and 4?

Exhibit

Options

A
1. App Engine
B
1. Dataflow
C
1. Pub/Sub
D
1. Pub/Sub

How the community answered

(35 responses)

A
6% (2)
B
3% (1)
D
91% (32)

Explanation

The canonical Google Cloud streaming architecture follows this pattern: (1) Pub/Sub - a fully managed, scalable message broker used to reliably ingest high-volume event streams from thousands of devices without data loss; (2) Dataflow - a managed Apache Beam service that processes and transforms the streaming data in real time; (3) BigQuery - a serverless data warehouse that stores the processed data and natively supports SQL-based analysis; (4) Data Studio / Looker Studio or another BI tool for visualization. Option D is the only answer that begins with Pub/Sub as the ingestion layer, which is the Google-recommended entry point for device telemetry pipelines. App Engine (A) is an application platform, not an ingestion service. Starting with Dataflow (B) skips the durable ingestion buffer that Pub/Sub provides.

Topics

#Streaming Data#Data Ingestion#Pub/Sub#Architectural Patterns

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