AZ-305 Design infrastructure solutions Practice Question
You need to design a solution to store log data from multiple Azure services. The data must be retained for 7 years for compliance purposes and should be queryable for analysis. Which Azure service should you use as the primary storage for these logs?
⚠ Common exam trap
Watch out — candidates often choose Azure Blob Storage because it is cheap and can store logs for 7 years, but they overlook the requirement that the data must be 'queryable for analysis'—Blob Storage alone does not provide native querying, whereas Log Analytics does.
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 Log Analytics workspace
Azure Log Analytics workspace is the correct choice because it is purpose-built for ingesting, storing, and querying log data from Azure services. It supports long-term retention up to 7 years (via the Basic Logs tier or data archiving with Azure Data Explorer) and provides Kusto Query Language (KQL) for interactive analysis, meeting both compliance and queryability requirements.
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 Data Lake Storage
Why it's wrong here
Azure Data Lake Storage (Gen2) is a highly scalable, Hadoop-compatible data lake optimized for big-data analytics, not for log ingestion, indexing, or time-series queries. While it can store raw log files cheaply at massive scale, it lacks a native query language, alerting, and monitoring integration; you would need additional engines like Synapse or Databricks to even query the logs, making it a poor fit for a purpose-built log management solution.
- ✗
Azure SQL Database
Why it's wrong here
Azure SQL Database is a relational, row-based DBMS that requires upfront schema design, indexing, and partitioning to handle high-volume append-only log streams, and its provisioning and licensing costs grow quickly with ingestion volume. It supports T-SQL queries, but not KQL or Azure Monitor's built-in log collection pipelines, so you would have to build and maintain custom export/import logic, making it cost-ineffective and operationally heavy for log storage.
- ✗
Azure Blob Storage
Why it's wrong here
Azure Blob Storage is an excellent low-cost archive tier for cold logs, with lifecycle management and immutable storage, but it is an object store, not a queryable log analytics platform. To run KQL queries, create alerts, or visualize trends, you would need to export blobs into Log Analytics or attach Azure Data Explorer, and there is no built-in schema or retention-by-table capability, so it is unsuitable as the primary log store when querying is required.
- ✓
Azure Log Analytics workspace
Why this is correct
An Azure Log Analytics workspace is the correct destination because it is a purpose-built, managed log data store within Azure Monitor, where agents and other sources natively send data as structured tables. It provides Kusto Query Language (KQL) for powerful time-series filtering and joins, built-in alerting, dashboards, and configurable retention/archive policies (up to 730 days online) with long-term storage to cheaper tiers. This makes it the central repository for multi-source logs that require continuous querying and monitoring.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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