AZ-305 Design data storage solutions Practice Question
A company needs a data storage solution for a global application that frequently accesses recent data and less frequently older data. Data is unstructured blobs. They want to automatically move blobs to cool storage after 30 days and to archive storage after 90 days. Additionally, blobs must be retained for 7 years and cannot be deleted or modified during that period. Which Azure Blob Storage features should they combine?
⚠ Common exam trap
Candidates often confuse legal hold (which is indefinite and manually managed) with time-based retention (which has a fixed expiry), leading candidates to choose Option A when they need a defined retention period.
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 blob lifecycle management policies and time-based retention policies.
Blob lifecycle management policies automatically transition blobs from hot to cool after 30 days and to archive after 90 days, while time-based retention policies enforce immutability for a fixed period (7 years), preventing deletion or modification. This combination meets both the tiering and retention requirements without manual intervention.
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 blob lifecycle management policies and legal hold (immutable blobs).
Why it's wrong here
While blob lifecycle management policies correctly automate tiering, legal hold (immutable blobs) provides indefinite retention until explicitly removed, failing to meet the specific 7-year fixed retention period required. This option is tempting because legal hold does prevent deletion and modification, making it suitable for scenarios demanding indefinite data preservation for compliance or litigation purposes, where the retention duration is not predetermined.
- ✓
Use blob lifecycle management policies and time-based retention policies.
Why this is correct
Blob lifecycle management policies automate cost-efficient data tiering, moving blobs from hot to cool to archive tiers based on age or last modification, thereby reducing storage costs as data ages. Time-based retention policies, a form of immutable blob storage with a fixed retention interval, prevent blobs from being modified or deleted for a specified period—here, 7 years—which satisfies regulatory compliance. Together they meet the global application's need for both automated tiering and fixed-duration write-once-read-many (WORM) protection, whereas a legal hold would leave retention indefinite and untethered to a specific deadline.
- ✗
Use Azure Storage Analytics and immutability policies.
Why it's wrong here
Azure Storage Analytics provides metrics and logs that help monitor storage account health and debug request failures, but it performs no data lifecycle operations and cannot move blobs between access tiers or enforce retention. Immutability policies alone—whether time-based or legal hold—guard against modification and deletion, but without lifecycle management, data never automatically transitions to cool or archive tiers, leaving early-stage hot-storage costs unoptimized. Selecting this combination would still require separate lifecycle rules to manage tiering, so it is incomplete and fails to fully address the data storage and cost requirements of a global application.
- ✗
Use Azure File Sync and lifecycle management.
Why it's wrong here
Azure File Sync is designed to synchronize server files with mounted Azure file shares for hybrid file workloads; it does not operate on blob storage or provide blob-tiering controls like hot/cool/archive transitions. While File Sync does offer cloud tiering to move infrequently accessed files to an archive tier within a file share, that mechanism is based on file-level access patterns and does not honor time-based retention or WORM immutability for blobs. Consequently, combining File Sync with lifecycle management would not produce the required fixed 7-year retention and would not store data in the blob storage architecture typical for a global application's object data.
Quick reference
Azure Blob Storage Tier Comparison
| Tier | Storage Cost | Retrieval Cost | Latency | Use Case |
|---|---|---|---|---|
| Hot | Highest | Lowest | Immediate | Active data, frequent reads |
| Cool | Lower | Higher | Immediate | Data accessed < once / month |
| Cold | Lower still | Higher | Immediate | Data accessed < once / quarter |
| Archive | Lowest | Highest + rehydration delay | Hours | Long-term compliance retention |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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