Google ACE Practice Question: Ensuring Successful Operation of a Cloud Solution
You need to export all Cloud Logging logs from a specific project to BigQuery for long-term analysis. What should you create?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
A log sink with BigQuery as the destination
Log sinks in Cloud Logging allow you to route logs to destinations like BigQuery, Cloud Storage, or Pub/Sub. You create a sink with BigQuery as the destination.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
A log-based metric with BigQuery as destination
Why it's wrong here
A log-based metric is a monitoring construct that counts or samples log entries matching a specified filter, then sends that metric data to Cloud Monitoring, not to BigQuery. It cannot export the underlying raw log entries to any storage destination, so it would never satisfy a requirement to export all logs. While a log-based metric could be used alongside a sink for observability, it is not a substitute for an export mechanism.
- ✓
A log sink with BigQuery as the destination
Why this is correct
A log sink is the correct Cloud Logging resource for streaming log entries to a supported destination, and BigQuery is a first-class destination. When you create a sink with `gcloud logging sinks create` or in the console, you specify a BigQuery dataset as the destination; Cloud Logging then continuously routes exported log entries into a partitioned table. This satisfies the requirement to export all logs from the project, optionally filtered by a log query.
- ✗
A Pub/Sub subscription that pushes logs to BigQuery
Why it's wrong here
A Pub/Sub subscription does not directly export all Cloud Logging logs to BigQuery; Cloud Logging requires a Log Sink to route logs to any destination, including BigQuery, for comprehensive long-term analysis. This option is tempting because Cloud Logging *can* export logs to a Pub/Sub topic via a Log Sink. This setup is appropriate when logs need real-time processing by custom applications or serverless functions for event-driven workflows, rather than direct archival.
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An export job from Logging to BigQuery using gcloud logging export
Why it's wrong here
There is no `gcloud logging export` command; the Google Cloud CLI includes `gcloud logging sinks create` to manage log sinks. An 'export job' is not a concept in Cloud Logging—exports are continuous via sinks, not one-time batch jobs. Attempting to run a non-existent command would fail, and even conceptually, a one-time job would not provide ongoing export of all logs.
Go deeper
Related to this question
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Google Cloud Platform Overview
Key term
Cloud storage
Cloud storage is a service that lets you save data on remote servers accessed over the internet instead of on your computer's hard drive.
Key term
BigQuery
BigQuery is a fully managed, serverless data warehouse on Google Cloud that lets you run fast SQL queries on massive datasets without managing any infrastructure.
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This ACE practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the ACE exam.