DP-900 Practice Question: Identify considerations for relational data on Azure
A company has an Azure SQL Database and needs to run a weekly data aggregation job that takes several hours. They want to minimize cost and avoid impacting production workload. Which approach should they use?
⚠ Common exam trap
A common mix-up: candidates confuse Azure Elastic Jobs as a workload isolation tool, when in fact it only schedules jobs on the same database and does not provide a separate compute resource.
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
✓
Create a read-only replica and run the aggregation on the replica
Creating a read-only replica allows the weekly aggregation job to run against a separate copy of the database without affecting the production workload. Since the replica is read-only, it incurs additional compute costs only during the aggregation window, and you can scale it down or stop it when not in use, minimizing overall cost.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Migrate the database to the Hyperscale service tier
Why it's wrong here
Migrating to the Hyperscale service tier does not isolate the aggregation workload from production traffic. Hyperscale provides scalable compute and storage, and the ability to rapidly scale, but all connections still hit the same writable primary unless you separately configure a named replica. The aggregation would continue to consume CPU, IO, and memory on the same database engine, potentially contending with production queries and slowing them down.
- ✗
Use Azure Elastic Jobs to run the aggregation during off-peak hours
Why it's wrong here
Azure Elastic Jobs is a job scheduler for executing T-SQL scripts across one or more databases, but it does not provision dedicated compute for job execution. The aggregation job would simply run against the primary database as a normal connection, with no resource isolation from production workloads. Scheduling it during off-peak hours only reduces the likelihood of user concurrency; it does nothing to prevent the job from consuming resources that other active transactions may need.
- ✗
Increase the DTU or vCore size of the database to handle the load
Why it's wrong here
Increasing the DTU or vCore size gives the logical server more CPU and memory, but the added capacity is shared by every workload on that same database, including both the aggregation and production. This approach does not create a separate execution environment; heavy aggregation can still spike resource usage and degrade response times for online users. It also increases licensing and operational costs, and the scale operation itself may briefly interrupt connectivity, so it is not a clean solution for workload isolation.
- ✓
Create a read-only replica and run the aggregation on the replica
Why this is correct
Creating a read-only replica and directing the weekly aggregation to it is the correct approach because it physically separates the heavy read workload from the primary write workload. Azure SQL Database read scale-out (Premium and Business Critical) or a geo-replicated secondary can serve read-only connections with ApplicationIntent=ReadOnly, allowing the aggregation to run on a separate compute and storage footprint. This offloading ensures the primary remains dedicated to production OLTP transactions, minimizing contention and preserving performance.
Go deeper
Related to this question
Learn chapter
Data Roles and Core Concepts
Key term
Azure SQL Database
Azure SQL Database is a fully managed relational database-as-a-service (DBaaS) in Microsoft Azure, based on the SQL Server engine, that handles scaling, backups, patching, and high availability automatically.
Key term
Data
Data is raw, unprocessed information, like numbers, words, or measurements, that can be stored, processed, and analyzed by computers.
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