Quick Answer
The answer is Cloud Audit Logs, BigQuery, and Cloud Logging. Cloud Audit Logs capture every IAM policy change and access attempt across projects, while Cloud Logging aggregates these logs into a centralized sink. BigQuery then serves as the analytics destination, allowing you to run SQL queries for anomaly detection across all projects. On the Google Professional Cloud Security Engineer exam, this scenario tests your understanding of the centralized IAM audit logging pipeline, where a common trap is to forget that Cloud Logging is the intermediary that routes logs to BigQuery—candidates often jump straight to exporting directly from Cloud Audit Logs to BigQuery. The key concept is that Cloud Logging’s sinks enable project-wide aggregation, while BigQuery provides the scalable query layer for monitoring. Memory tip: think “Logs sink to BigQuery” to remember the three-service chain—Cloud Audit Logs feed into Cloud Logging, which sinks into BigQuery for analysis.
This PCSE practice question tests your understanding of managing operations in a cloud solution environment. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A security engineer is designing a solution to monitor and detect anomalous IAM role usage across multiple Google Cloud projects. The engineer wants to create a centralized logging solution that captures all IAM policy changes and access attempts. Which THREE services should the engineer use together to achieve this?
BigQuery
Used to store and analyze logs forwarded from Cloud Logging via log sinks.
Cloud Logging
Centralized log management service where all logs are aggregated.
Cloud Audit Logs
Captures all IAM policy changes and access attempts.
Cloud Monitoring
Why wrong: Used for monitoring and alerting based on metrics, not for centralized log storage.
Cloud Functions
Why wrong: Can be used to process logs but is not required for centralized logging.
Answer choices
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
BigQuery
BigQuery is correct because it serves as the centralized analytics destination for Cloud Audit Logs, enabling the security engineer to run SQL queries across IAM policy changes and access attempts from multiple Google Cloud projects. By exporting audit logs to BigQuery, you can perform complex aggregations and anomaly detection at scale, which is essential for monitoring IAM role usage across a fleet of projects.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
For each option: why learners choose it and why it is or isn't the right answer here.
BigQuery
Why this is correct
Used to store and analyze logs forwarded from Cloud Logging via log sinks.
Related concept
Read the scenario before looking for a memorised answer.
Cloud Logging
Why this is correct
Centralized log management service where all logs are aggregated.
Related concept
Read the scenario before looking for a memorised answer.
Cloud Audit Logs
Why this is correct
Captures all IAM policy changes and access attempts.
Related concept
Read the scenario before looking for a memorised answer.
Cloud Monitoring
Why it's wrong here
Used for monitoring and alerting based on metrics, not for centralized log storage.
Cloud Functions
Why it's wrong here
Can be used to process logs but is not required for centralized logging.
Common exam traps
Google Cloud often tests the distinction between logging/audit services (Cloud Logging, Cloud Audit Logs, BigQuery) and monitoring/alerting services (Cloud Monitoring), so candidates mistakenly choose Cloud Monitoring for log analysis when it is only for metrics and dashboards.
Detailed technical explanation
Cloud Audit Logs capture three types of logs: Admin Activity, Data Access, and System Events, each with different retention periods (400 days for Admin Activity, 30 days for Data Access by default). To extend retention and enable cross-project analysis, you can route these logs to BigQuery via log sinks, where you can use SQL to detect patterns like sudden spikes in AssumeRole calls or unauthorized access attempts across projects. This architecture leverages BigQuery's columnar storage and partitioning to handle terabytes of audit log data efficiently.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
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FAQ
Managing operations in a cloud solution environment — This question tests Managing operations in a cloud solution environment — Read the scenario before looking for a memorised answer..
The correct answer is: BigQuery — BigQuery is correct because it serves as the centralized analytics destination for Cloud Audit Logs, enabling the security engineer to run SQL queries across IAM policy changes and access attempts from multiple Google Cloud projects. By exporting audit logs to BigQuery, you can perform complex aggregations and anomaly detection at scale, which is essential for monitoring IAM role usage across a fleet of projects.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Read the scenario before looking for a memorised answer.
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Last reviewed: Jun 30, 2026
This PCSE 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 PCSE exam.
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