Cloud Digital Leader Why Cloud Technology Can Transform Business Practice Question
A company uses multiple public clouds (AWS, Azure, Google Cloud) for different workloads. They want to centralize monitoring and logging. Which Google Cloud service can aggregate logs from all clouds?
⚠ Common exam trap
GCDL often tests the boundary between Cloud Logging (logs) and Cloud Monitoring (metrics), and whether candidates know Cloud Audit Logs are Google-Cloud-only and cannot aggregate AWS/Azure logs.
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
✓
Cloud Logging
Cloud Logging (formerly Stackdriver Logging) is Google Cloud's centralized log ingestion, storage, and analysis service, and it can ingest logs from AWS, Azure, and other sources via the BindPlane/Cloud Logging agent or the Logging API. It provides a single pane for querying and routing logs across clouds, making it the correct choice for aggregating multi-cloud logs. Cloud Monitoring handles metrics and dashboards, not log aggregation.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
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Cloud Audit Logs
Why it's wrong here
Cloud Audit Logs are narrow in scope: they capture administrative activity and access events within Google Cloud resources, such as changes to IAM permissions, bucket creations, or service account usage. They are generated by Google Cloud's own services and cannot ingest AWS or Azure audit trails, making them unsuitable as a centralized multi-cloud logging repository. While they are a useful component of security monitoring, they lack the vendor-neutral ingestion capability required for aggregating logs from multiple public clouds.
- ✗
Cloud Console
Why it's wrong here
Cloud Console is the web-based management interface for Google Cloud, providing a GUI to view resources, deploy GCP services, and inspect logs through the built-in Logs Explorer. However, it is purely a user-interface layer and not an autonomous log aggregation service; it does not collect, index, or store logs by itself. Moreover, it offers no API or agent framework to pull logs from AWS or Azure, so it cannot serve as a cross-cloud log sink. At best, it provides a convenient way to interact with Cloud Logging's data, but it is not the underlying service that aggregates logs.
- ✗
Cloud Monitoring
Why it's wrong here
Cloud Monitoring is an observability tool designed for time-series metrics, uptime checks, and alerting policies, not for ingesting raw log messages. It can pull metric data from AWS and Azure via API integrations, but that data is numerical telemetry (e.g., CPU utilization, request latency), not unstructured application logs. While Cloud Monitoring can derive metric data from logs through log-based metrics, that is a downstream processing feature—it does not aggregate, store, or provide a searchable interface for multi-cloud raw logs. Therefore, it is the wrong choice for a centralized log aggregation platform.
- ✓
Cloud Logging
Why this is correct
Cloud Logging is the correct answer because it is a fully managed, real-time log aggregation service capable of ingesting logs from any source, including AWS and Azure, via the Logging API, Fluent Bit agents, or SDK integrations. It accepts structured and unstructured logs, applies indexes for queryability, and supports exports to BigQuery, Pub/Sub, or cloud storage for long-term archiving. In a multi-cloud environment, you can install an agent on AWS EC2 or Azure VMs to forward logs to a centralized sink, giving you a single Logs Explorer to search across all clouds. This directly fulfills the requirement of aggregating logs from multiple public clouds.
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
Go deeper
Related to this question
Learn chapter
Hybrid and Multi-Cloud Strategy
Key term
Cloud logging
Cloud logging is the practice of collecting, storing, and analyzing log data generated by cloud-based resources and applications to monitor performance, troubleshoot issues, and maintain security.
Key term
Cloud Monitoring
Cloud monitoring is the process of observing, measuring, and managing an organization's cloud infrastructure and applications to ensure performance, availability, and security.
About these practice questions
This GCDL question is part of Courseiva's 848-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
JA
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
This GCDL 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 GCDL exam.