AZ-204 Develop for Azure storage Practice Question
You need to store large binary files (up to 2 GB) that are frequently overwritten in place (entire file replaced). You want to minimize storage cost and write latency. Which Azure Blob Storage type should you use?
⚠ Common exam trap
Test-takers frequently confuse 'frequently overwritten' with 'random access' and choose Page Blob, forgetting that page blobs are optimized for small, random writes (like VHDs) and are more expensive, while block blobs are the correct choice for large file replacement with low 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
✓
Block Blob
Block blobs are optimized for storing large binary files (up to ~4.75 TB) and support high-throughput uploads via PutBlock and PutBlockList operations. They allow overwriting an entire blob by uploading a new set of blocks, which minimizes write latency compared to page blobs that require sector-aligned writes. Block blobs also offer lower storage cost than page blobs, making them the best choice for frequently overwritten large files.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Block Blob
Why this is correct
Block blobs are highly optimized for storing large binary files, including those up to 2 GB, by allowing data to be uploaded in manageable blocks. This architecture enables efficient replacement of the entire blob by committing a new block list, which is crucial for scenarios requiring frequent overwrites. Their low latency and cost-effectiveness for whole-file updates make them the ideal choice.
- ✗
Page Blob
Why it's wrong here
Page blobs are specifically designed for random read/write operations on fixed 512-byte pages, primarily used for virtual hard disk (VHD) files that back Azure Virtual Machines. While they support byte-range updates, their underlying structure is not optimized for replacing entire large files efficiently. Using page blobs for frequent whole-file overwrites would be less performant and significantly more expensive compared to block blobs.
- ✗
Append Blob
Why it's wrong here
Append blobs are uniquely optimized for append operations, meaning data can only be added to the end of the blob. This design makes them suitable for logging scenarios where new entries are continuously added without modifying existing content. Consequently, they fundamentally lack the capability to efficiently overwrite or modify existing parts of the blob, rendering them entirely unsuitable for frequently overwritten files.
- ✗
Archive Blob
Why it's wrong here
The Archive access tier is intended for long-term storage of rarely accessed data, offering the lowest storage costs but with significantly high retrieval latency, typically measured in hours. Frequent overwrites would necessitate moving the blob to a hot or cool tier for modification, incurring substantial rehydration costs and delays. This makes the Archive tier impractical and cost-prohibitive for files requiring frequent access and modification.
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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