Google ACE Practice Question: Ensuring Successful Operation of a Cloud Solution

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

• ✗

  Create a Cloud Pub/Sub topic and configure a push subscription

  Why it's wrong here

  Creating a Cloud Pub/Sub topic and a push subscription is a valid Cloud Logging sink destination, but it is not required when the goal is to export logs into BigQuery. A Pub/Sub sink would only stream log entries into a message queue, requiring an additional subscriber and data pipeline to load them into BigQuery. Since the question explicitly targets BigQuery as the destination, you should configure the sink to write directly to a BigQuery dataset instead of introducing a separate, unnecessary message-passing layer.

• ✓

  Create a BigQuery dataset and grant the log sink's service account the BigQuery Data Editor role

  Why this is correct

  This is the correct approach because BigQuery must already exist as a dataset for the log sink to write into, and the sink's underlying writer identity (the service account) needs the BigQuery Data Editor role (roles/bigquery.dataEditor) on that dataset to create tables and insert log entries. You first create the dataset, then configure the log sink with BigQuery as its destination, and after the sink is created you copy its service account ID and grant that service account the required IAM role. Without that grant, the sink will fail with permission errors when trying to deliver logs to BigQuery.

• ✗

  Create a Cloud Storage bucket as a staging location

  Why it's wrong here

  A Cloud Storage bucket is not needed as a staging location because log exports to BigQuery use direct streaming writes from Cloud Logging into the dataset's tables. The sink's writer identity authenticates directly to the BigQuery API; logs are never buffered or temporarily stored in Cloud Storage. Introducing a staging bucket would add latency, cost, and an extra component that must be cleaned up, offering no benefit for the simple requirement of exporting logs to BigQuery.

• ✗

  Enable BigQuery's streaming buffer on the dataset

  Why it's wrong here

  The streaming buffer in BigQuery is an internal, automatic feature that provides high ingress throughput and weakly consistent reads for recently streamed data; it is not something you manually enable on a dataset as a prerequisite. Log sinks write to BigQuery using the Storage Write API, which is a streaming ingestion method that already utilizes the streaming buffer on the target tables. This option is irrelevant because the streaming buffer is always present for streamed data and does not need to be configured ahead of time for a log export.

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