AZ-305 Design data storage solutions Practice Question
A company stores log data in Azure Blob Storage. Logs are accessed frequently for the first 30 days, then rarely accessed but must be retained for 7 years for compliance. They want to minimize storage costs. Which storage tier and lifecycle management rule should they use?
⚠ Common exam trap
The trap here is that candidates may overcomplicate by adding an intermediate Cool tier (Option B) or incorrectly assume Archive can be used for initial storage (Option D), failing to recognize that direct transition to Archive after the hot period is the most cost-effective for long-term retention with minimal access.
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 the Hot tier for initial storage, and a lifecycle rule to move to Archive after 30 days.
The Hot tier is optimal for frequent access during the first 30 days, and a lifecycle rule moving directly to Archive after 30 days minimizes costs by immediately transitioning to the lowest-cost storage tier for long-term retention. The Archive tier is the most cost-effective for data that is rarely accessed and must be retained for 7 years, as it offers the lowest storage cost but higher retrieval latency and cost.
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 the Cool tier for initial storage, and a lifecycle rule to move to Archive after 30 days.
Why it's wrong here
Cool tier is for data accessed infrequently but with immediate availability. Using Cool for the first 30 days may increase cost compared to Hot because Cool has higher read costs and lower storage cost, but Hot is cheaper for frequent access. More importantly, the requirement is to minimize cost, and Hot then Archive is the optimal path.
- ✗
Use the Hot tier for initial storage, and a lifecycle rule to move to the Cool tier after 30 days, then to Archive after 7 years.
Why it's wrong here
This two-step transition is inefficient and more expensive. Moving blobs from Hot to Cool after 30 days incurs a write operation cost, and then moving them again from Cool to Archive after 7 years incurs an additional transition cost, but the data is rarely accessed and can go directly from Hot to Archive. Moreover, Cool tier storage is more expensive than Archive, so holding the data in Cool for nearly the entire 7-year retention period defeats the goal of minimizing cost. A single lifecycle rule from Hot to Archive after 30 days achieves the same retention with lower operational and storage costs.
- ✓
Use the Hot tier for initial storage, and a lifecycle rule to move to Archive after 30 days.
Why this is correct
Hot tier optimizes for frequent access during the first 30 days. Moving directly to Archive after 30 days minimizes storage cost during the long retention period, as Archive has the lowest storage cost for rarely accessed data.
- ✗
Use the Archive tier for initial storage, and a lifecycle rule to move to Hot for the first 30 days.
Why it's wrong here
Storing logs in Archive from day one is impractical because Archive is optimized for rarely accessed data with retrieval latency measured in hours. Any reads to these logs during the first 30 days would trigger rehydration, incurring substantial costs and delays, and the lifecycle rule to move them to Hot would also require rehydration and a costly archival read operation. This arrangement inverts the required access pattern: frequent reads require Hot, not Archive. The correct design is to keep data hot for initial access and then transition to Archive to minimize cost.
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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