Google PCA Practice Question: Managing and Provisioning a Solution Infrastructure
A team wants to collect and analyze logs from multiple projects into a centralized BigQuery dataset for long-term retention and SQL querying. They want to exclude health check logs to reduce costs. Which approach should they use?
⚠ Common exam trap
PCA often tests the difference between log metrics and log sinks; candidates mistakenly think a log metric can exclude logs from export, but only a sink exclusion filter prevents export.
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
✓
Create a log sink to BigQuery and add a log exclusion filter for health check logs
A log sink routes log entries from Cloud Logging to a destination such as BigQuery, and an exclusion filter on the sink prevents matching entries (health check logs) from being exported, reducing cost. This is the native, supported way to centralize logs in BigQuery while filtering out unwanted entries at the source. The sink can be created at the organization or folder level to aggregate multiple projects.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use Cloud Monitoring to exclude health check logs
Why it's wrong here
Cloud Monitoring handles metrics, uptime checks and alerting, not log routing; its exclusion filters do not stop logs reaching a BigQuery sink. Monitoring exclusion is correct when suppressing metric-based alert noise, whereas log cost control requires a Logging query or sink exclusion filter.
- ✗
Create a log metric for health check logs and filter in BigQuery
Why it's wrong here
A log metric counts matching entries but leaves the underlying health check logs flowing into BigQuery, so storage and query costs remain. Metrics suit alerting or dashboards on log patterns; excluding entries from a sink requires a Logging exclusion filter, not downstream filtering in BigQuery.
- ✓
Create a log sink to BigQuery and add a log exclusion filter for health check logs
Why this is correct
A BigQuery log sink routes selected log entries into a dataset for SQL querying and retention, while an exclusion filter drops health check entries before ingestion. It satisfies both the centralisation and cost-reduction constraints in the stem.
- ✗
Set up a Cloud Function to delete health check logs from BigQuery
Why it's wrong here
A Cloud Function deleting rows after ingestion still pays for storing and streaming those health check logs, and adds bespoke code to maintain. It suits post-hoc remediation of malformed records, but exclusion must happen at the logging layer before the sink exports to BigQuery.
Go deeper
Related to this question
Learn chapter
Billing, Budgets, and Cost Management
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.
Key term
Organization
An Organization is a top-level container in Google Cloud that represents your company or entities and serves as the root node for all your cloud resources, policies, and access control.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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