The answer is Azure Log Analytics Workspace, because it is purpose-built for centralized log storage and query with Azure Log Analytics Workspace, supporting append-only ingestion from multiple applications while retaining data for up to 30 days in its interactive retention tier. This workspace leverages the Kusto Query Language (KQL) to deliver fast query performance even when analysis is infrequent, making it the ideal choice for scenarios where log data must be quickly searchable on demand. On the Microsoft Azure Solutions Architect Expert AZ-305 exam, this question tests your ability to match workload characteristics—like append-only patterns and short retention windows—to the correct Azure data platform service, often contrasting Log Analytics with Azure Data Lake or Azure SQL Database. A common trap is choosing Azure Storage or Azure Data Explorer for cost reasons, but the exam emphasizes that Log Analytics is the native, integrated solution for operational logs. Memory tip: think “LAW for logs” — Log Analytics Workspace is the default home for Azure Monitor log data, and its 30-day interactive retention is a key exam boundary.
AZ-305 Design data storage solutions Practice Question
This AZ-305 practice question tests your understanding of design data storage solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company wants to store log data from multiple applications for up to 30 days for analysis. The data is append-only, and queries are infrequent but need to be fast when run. Which Azure data storage solution should you recommend?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Azure Log Analytics Workspace
Azure Log Analytics Workspace is the correct choice because it is purpose-built for ingesting, storing, and querying log data from multiple sources. It supports append-only log ingestion, retains data for up to 30 days in its interactive retention tier (configurable), and provides fast Kusto Query Language (KQL) queries for infrequent analysis. The workspace integrates natively with Azure Monitor and other services, making it ideal for centralized log analysis.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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 Log Analytics Workspace
Why this is correct
Log Analytics is built for log data, fast queries, and configurable retention.
Related concept
Read the scenario before looking for a memorised answer.
✗
Azure Table Storage
Why it's wrong here
Table Storage is for NoSQL structured data, not ideal for log analysis.
✗
Azure Data Lake Storage Gen2
Why it's wrong here
Data Lake is for big data analytics with high throughput, but more expensive for simple log storage.
✗
Azure Blob Storage (archive tier)
Why it's wrong here
Archive tier is for long-term cold storage; querying is slow and not cost-effective for 30 days.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often choose Azure Blob Storage (archive tier) for cost savings, overlooking the explicit requirement for fast query performance, which the archive tier cannot provide due to its multi-hour rehydration latency.
Detailed technical explanation
How to think about this question
Under the hood, Log Analytics Workspaces use a columnar storage format and a distributed query engine that indexes log data by time and other fields, enabling sub-second query responses even on terabytes of data. The 30-day retention is the default interactive retention period, after which data can be moved to a long-term retention tier (up to 7 years) at lower cost, but queries on archived data incur higher latency. In real-world scenarios, this workspace is used for Azure activity logs, resource diagnostics, and custom application logs, with KQL supporting complex aggregations and joins across multiple tables.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this AZ-305 question in full detail.
Design data storage solutions — This question tests Design data storage solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Azure Log Analytics Workspace — Azure Log Analytics Workspace is the correct choice because it is purpose-built for ingesting, storing, and querying log data from multiple sources. It supports append-only log ingestion, retains data for up to 30 days in its interactive retention tier (configurable), and provides fast Kusto Query Language (KQL) queries for infrequent analysis. The workspace integrates natively with Azure Monitor and other services, making it ideal for centralized log analysis.
What should I do if I get this AZ-305 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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