AZ-204 Practice Question: Connect to and consume Azure services and third-party services
A developer needs to store a large number of binary files (images) that are accessed frequently from a web app. Which Azure storage solution is most cost-effective?
⚠ Common exam trap
Many candidates confuse Azure Files with Blob Storage because both store files, but Azure Files is designed for SMB-based file shares (e.g., for legacy apps or shared drives) and is more expensive per GB than Blob Storage, making it the wrong choice for cost-effective, high-frequency binary file serving.
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
✓
Azure Blob Storage
Azure Blob Storage is the most cost-effective solution for storing large numbers of binary files like images because it is optimized for massive scale, high-throughput, and low-cost object storage. It supports hot, cool, and archive access tiers to balance cost and access frequency, and it integrates directly with web apps via HTTP/HTTPS REST APIs or SDKs, making it ideal for frequently accessed static content.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Azure Queue Storage
Why it's wrong here
Azure Queue Storage is fundamentally designed for asynchronous message passing between decoupled application components, facilitating communication rather than persistent file storage. Messages in a queue are typically small (up to 64 KB) and transient, intended for processing by a consumer service. Storing large binary files directly in Queue Storage is impractical due to these size limitations and its purpose, which is not optimized for file access or long-term data retention.
- ✗
Azure Files
Why it's wrong here
Azure Files provides fully managed file shares in the cloud, accessible via industry-standard Server Message Block (SMB) or Network File System (NFS) protocols, making it suitable for 'lift-and-shift' scenarios requiring file system semantics. While it can store files, it is not optimized for serving a large number of individual images directly to web applications or for the extreme scale and cost efficiency of object storage for unstructured data. Its cost model and access patterns are better suited for traditional file share workloads.
- ✓
Azure Blob Storage
Why this is correct
Azure Blob Storage is purpose-built for storing massive amounts of unstructured object data, such as binary files, images, videos, and documents, at a highly scalable and cost-effective rate. It offers various access tiers (Hot, Cool, Archive) to optimize costs based on access frequency and provides direct HTTP/S access to individual blobs. Its design makes it ideal for cloud-native applications requiring global accessibility, high availability, and efficient storage for large volumes of binary content.
- ✗
Azure Cosmos DB
Why it's wrong here
Azure Cosmos DB is a globally distributed, multi-model NoSQL database service optimized for high-throughput, low-latency transactional workloads on structured and semi-structured data. While it can technically store small binary data embedded within documents, it is prohibitively expensive and inefficient for storing large binary files like images. Its Request Unit (RU/s) cost model and document size limits are not designed for raw binary storage, making it an unsuitable and costly choice for this specific requirement.
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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