PDE Storing the Data Practice Question
A company uses Cloud Storage as a data lake with raw, curated, and processed zones. Data in the raw zone should be automatically moved to a cheaper storage class after 30 days, and deleted after 1 year. What is the most efficient way to implement this?
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 Object Lifecycle Management with rules to transition to Coldline after 30 days and delete after 365 days.
Object Lifecycle Management in Cloud Storage allows you to set rules based on object age. You can transition objects to a lower-cost storage class (e.g., Nearline or Coldline) after 30 days and delete after 365 days.
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 Object Lifecycle Management with rules to transition to Coldline after 30 days and delete after 365 days.
Why this is correct
Object Lifecycle Management applies rule-based transitions and deletions natively at the bucket level, so no external scheduler or code is needed. Setting Age conditions of 30 days for Coldline transition and 365 days for deletion satisfies both stem constraints automatically and efficiently.
- ✗
Write a Cloud Function that runs daily, checks object ages, and moves/deletes them.
Why it's wrong here
A Cloud Function requires custom code, scheduling and error handling, duplicating lifecycle management that Cloud Storage performs natively. It is tempting because serverless functions are a common automation route, and would be correct for transformations or moves between buckets that Object Lifecycle Management cannot express.
- ✗
Use Cloud Scheduler to run a script that changes storage class and deletes objects.
Why it's wrong here
Cloud Scheduler triggers a script on a schedule, but this approach requires managing compute resources, authentication, and error handling for each execution, introducing operational overhead and potential failure points. It is tempting because scheduled tasks are a common pattern for periodic data management, and this method would be correct for ad-hoc or complex transformations that cannot be expressed declaratively, such as conditional logic beyond lifecycle rules.
- ✗
Set a retention policy on the raw zone to prevent deletion and manually clean up.
Why it's wrong here
A retention policy blocks deletion for a fixed period, directly contradicting the one-year deletion requirement, and manual cleanup is not automatic. It is tempting because retention policies govern object deletion, and would be correct when objects must be protected from removal rather than aged out.
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 |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This PDE 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 PDE exam.