AZ-204 Develop for Azure storage Practice Question
An application writes millions of small log entries (500 bytes each) daily. The logs are rarely read, and when read, they are accessed sequentially. You need to minimize storage costs and maximize write throughput. Which Azure Blob Storage type should you use?
⚠ Common exam trap
Watch out — candidates often confuse 'Append Blob' with 'Block Blob' because both support blocks, but they fail to recognize that Append Blob is specifically designed for append-only workloads, while Block Blob is not optimized for sequential writes and incurs higher overhead per operation.
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
✓
Append Blob
Append Blob is optimized for append operations, making it ideal for logging scenarios where new data is continuously added to the end of the blob. It provides high write throughput for small, sequential writes (like 500-byte log entries) and lower storage costs compared to Block Blob for this pattern, as it avoids the overhead of managing multiple blocks per append. Additionally, Append Blob supports sequential read access efficiently, matching the rare, sequential read requirement.
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 it's wrong here
Block Blobs are optimized for storing large, discrete objects like documents, images, or videos, and for efficient upload and download of entire files or large chunks. While technically possible to append data by downloading, modifying, and re-uploading, or by adding new blocks and committing an updated block list, this process incurs significant transaction overhead and latency for millions of small, frequent append operations. It is not designed for the high-throughput, sequential write pattern required for logging.
- ✗
Page Blob
Why it's wrong here
Page Blobs are specifically designed for random read/write operations on fixed-size 512-byte pages, making them ideal for virtual hard disk (VHD) files used by Azure Virtual Machines. They are not optimized for sequential append-only workloads like log entries. Using Page Blobs for logging would result in high transaction costs due to numerous small page writes and would not leverage their random access capabilities, making them an inefficient and expensive choice for this specific use case.
- ✓
Append Blob
Why this is correct
Append Blobs are purpose-built for scenarios requiring fast, sequential writes to the end of a blob, making them the optimal choice for logging, auditing, and IoT data streams. Each new block is added atomically to the end of the blob, ensuring data integrity and high throughput for millions of small log entries without modifying existing content. This design minimizes transaction costs and maximizes efficiency for append-only workloads, perfectly matching the requirement.
- ✗
Archive Blob
Why it's wrong here
The Archive access tier provides the lowest storage cost and is intended for rarely accessed, long-term retention data with flexible latency requirements. While cost-effective for dormant data, it is entirely unsuitable for an application that is actively writing millions of log entries. Data retrieval from the Archive tier can take hours, making it impractical for any scenario requiring frequent writes or near real-time access for monitoring, troubleshooting, or immediate analysis.
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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Senior Network & Security Engineer · founder of Courseiva
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