AZ-204 Develop for Azure storage Practice Question
Your company stores backup files in an Azure Blob Storage account. These files are written once and then need to be retained for 7 years. During the first year, the files are accessed weekly. After the first year, they are accessed rarely (once per month). You want to minimize storage costs. Which combination of access tiers and lifecycle management should you apply?
⚠ Common exam trap
A common mix-up: candidates assume the Hot tier is always the best starting point for any access pattern, ignoring that Cool tier is cheaper for data accessed less than once a month, and that Archive tier is not suitable for data that requires regular access within the first year due to its high rehydration latency and cost.
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
✓
Store in Hot tier and move to Cool after 1 year, then to Archive after 7 years.
For data accessed weekly during the first year, the Hot tier is appropriate, or the Cool tier if storage cost savings significantly outweigh transaction costs. For data accessed monthly after the first year, the Cool tier is the most cost-effective choice, balancing lower storage costs with reasonable access costs without incurring rehydration fees or significant latency. The Archive tier is suitable only for data that is rarely accessed (e.g., less than once a year) and can tolerate significant retrieval latency and cost. Therefore, the optimal strategy among the given options is to store in Hot for the first year, move to Cool for the subsequent years of monthly access, and then to Archive only after the 7-year retention period if access truly ceases.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Store in Hot tier and move to Cool after 1 year, then to Archive after 7 years.
Why this is correct
Moving to Cool after 1 year is too late; the data is already rarely accessed. Also moving to Archive after 7 years is unnecessary because the retention period ends. The data should be in Archive for most of the retention.
- ✗
Store in Cool tier and move to Archive after 1 year.
Why it's wrong here
This strategy is optimal because the Cool tier is cost-effective for data accessed infrequently, such as weekly backups, offering lower storage costs than Hot while maintaining acceptable access times. After one year, when access frequency is expected to drop significantly, transitioning to the Archive tier provides the lowest storage cost for long-term retention. Azure Blob Storage lifecycle management policies can automate this tier transition, ensuring cost efficiency throughout the data's seven-year retention period.
- ✗
Store directly in Archive tier and rehydrate to Cool when needed for access.
Why it's wrong here
Storing directly in the Archive tier is unsuitable for data accessed weekly during the first year. While Archive offers the lowest storage cost, accessing data requires rehydration, which incurs significant retrieval costs and can take hours (up to 15 hours for standard priority). This high latency and expense for frequent access make it impractical and costly for regularly accessed backups, negating any initial storage cost savings.
- ✗
Store in Hot tier and move to Archive after 90 days.
Why it's wrong here
This approach is suboptimal as the Hot tier is the most expensive storage tier, designed for frequently accessed data, making it an inefficient choice for backup files accessed only weekly. Furthermore, moving to Archive after just 90 days is premature because the data is still accessed weekly during the first year. The Archive tier's high retrieval costs and rehydration latency would make weekly access prohibitively expensive and slow, failing to meet operational requirements for the majority of the first year.
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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