Cloud Digital Leader Scaling with Google Cloud operations Practice Question
A cloud team wants to understand their current Google Cloud resource inventory — specifically, which VMs are running in each region, their machine types, and whether they have public IP addresses. Which approach most efficiently provides this across all projects?
⚠ Common exam trap
A common mix-up: candidates confuse Cloud Billing reports (cost-focused) or VPC flow logs (traffic-focused) with inventory tools, or assume manual per-project inspection is acceptable, when Cloud Asset Inventory is the only option designed for cross-project resource discovery at scale.
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
✓
Use Cloud Asset Inventory to run a single org-wide query that returns all VM instances, their regions, machine types, and network configurations across all projects
Cloud Asset Inventory provides a single, unified API to query resources across all projects in an organization. By using the `gcloud asset search-all-resources` command with the `--asset-types=compute.googleapis.com/Instance` filter, you can retrieve all VM instances along with their regions, machine types, and network configurations (including public IP addresses) in one operation, without needing to access each project individually.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Log into each Google Cloud project individually through the Console and manually record VM details in a spreadsheet
Why it's wrong here
The Console is project-scoped; manually visiting each project in an organization (which can number in hundreds) is not only tedious but relies on a human transcription process that introduces errors and immediately goes stale. It yields a point-in-time spreadsheet with no API-level automation, versioning, or audit trail, and cannot be refreshed programmatically, so it fails as a scalable, accurate org-wide inventory mechanism.
- ✓
Use Cloud Asset Inventory to run a single org-wide query that returns all VM instances, their regions, machine types, and network configurations across all projects
Why this is correct
Cloud Asset Inventory provides a single, org-wide searchable view of all compute.googleapis.com/Instance assets via the Cloud Asset API or Console asset search. It returns complete VM metadata—zone/region, machine type, network interfaces, external IP, labels, and status—without per-project login, and can be exported or queried programmatically, making it the only option that directly and comprehensively answers the request.
- ✗
Check the Cloud Billing reports, which list all resources that have incurred charges by resource type
Why it's wrong here
Cloud Billing reports and BigQuery billing exports aggregate costs by SKU, service, and project, but they do not enumerate individual VM configurations such as machine type, attached networks, or public IP assignment. A resource might be listed only as compute-engine line items or absent entirely if preemptible/discounts apply, so billing data cannot reconstruct an accurate configuration inventory.
- ✗
Enable VPC flow logs in each project to capture VM network activity
Why it's wrong here
VPC flow logs sample metadata about IP traffic leaving/entering network interfaces (five-tuples, bytes, packets) and are useful for network forensics and cost analysis, not asset discovery. They never include the VM's configured machine type, zone, or static network settings, and a stopped instance with no flows would be invisible, so this approach fundamentally cannot produce a VM inventory.
Go deeper
Related to this question
Learn chapter
Data Types and Analytics Workloads
Key term
Region
A region is a distinct geographic location where a cloud provider operates multiple data centers that are connected by low-latency networks and provide cloud services.
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 by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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