AZ-204 Develop for Azure storage Practice Question
You are developing a .NET Core application that uploads large files (up to 50 GB) to Azure Blob Storage. The application must support resuming uploads that are interrupted due to network failures. Which approach should you use?
⚠ Common exam trap
Microsoft often tests the misconception that append blobs are suitable for large file uploads because they support appending, but the trap is that append blobs lack the block-level granularity needed for resumable uploads, unlike block blobs which are explicitly designed for this scenario.
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 a block blob and upload blocks in parallel, then commit the block list.
Block blobs are designed for large files and support uploading blocks in parallel, which improves throughput and reliability. By uploading individual blocks and then committing the block list, you can resume an interrupted upload by re-uploading only the missing blocks, as each block is identified by a unique block ID. This approach is ideal for files up to 50 GB and aligns with Azure's recommended pattern for resumable uploads.
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 an append blob and append blocks in sequence.
Why it's wrong here
Append blobs are specifically optimized for append operations, where new data is continuously added to the end of the blob, such as for logging or auditing. While they support appending blocks, they do not provide the block-level management or commit functionality necessary for efficient, resumable uploads of a large, single file like 50 GB. Their design prioritizes sequential writes without the ability to re-upload or manage individual parts for a complete file reconstruction.
- ✓
Use a block blob and upload blocks in parallel, then commit the block list.
Why this is correct
Block blobs are the most suitable type for storing large files, as they allow a file to be broken down into smaller, manageable blocks. These blocks can be uploaded independently and in parallel using the `Put Block` operation, significantly accelerating the upload process. Once all blocks are successfully uploaded, the `Put Block List` operation commits them in the correct order, enabling robust resumable uploads by only re-uploading failed or missing blocks, which is critical for a 50 GB file.
- ✗
Use the Put Blob API to upload the entire file in a single request.
Why it's wrong here
The `Put Blob` API is designed for uploading an entire blob in a single request. However, this method has a strict maximum size limit of 256 MB for block blobs and 64 MB for page blobs when uploaded directly. Attempting to upload a 50 GB file using a single `Put Blob` call would vastly exceed this limit, resulting in an immediate error and making it an entirely unviable option for such a large file.
- ✗
Use a page blob and upload pages in sequence.
Why it's wrong here
Page blobs are optimized for random read/write operations on fixed-size 512-byte pages, making them ideal for scenarios like virtual hard disk (VHD) files used by Azure Virtual Machines. While they can store large amounts of data, their architecture is not designed for efficient, resumable bulk uploads of sequential data. Uploading pages in sequence would be less performant and lacks the inherent resumability and parallel upload capabilities that block blobs offer for large file transfers.
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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