AZ-204 Develop for Azure storage Practice Question
A Cosmos DB workload for telemetry events has predictable traffic during business hours and almost no traffic overnight. The team wants to reduce cost while keeping performance during peak hours. What should be configured?
⚠ Common exam trap
It's easy for candidates to confuse 'autoscale' with 'manual throughput' and assume manual throughput set to peak is the safest choice, but they overlook the cost of idle capacity; Microsoft often tests the understanding that autoscale is the only option that dynamically matches cost to actual usage while preserving peak performance.
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
✓
Autoscale throughput with an appropriate maximum RU/s
Autoscale throughput (option B) is correct because it dynamically scales the provisioned RU/s between 10% of the configured maximum and the maximum itself based on actual demand. For a workload with predictable peak traffic during business hours and near-zero traffic overnight, autoscale eliminates the cost of provisioning for peak capacity 24/7 while ensuring performance is not throttled during high-demand periods. This directly addresses the cost-reduction goal without sacrificing peak-hour performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Analytical store only
Why it's wrong here
The analytical store in Azure Cosmos DB is optimized for large-scale analytical queries, utilizing a columnar format for efficient data aggregation and analysis without impacting transactional throughput. However, it is a separate operational store and does not directly provide or scale the transactional Request Units per second (RU/s) needed for ingesting and processing a high volume of telemetry events. Relying solely on it would neglect the primary transactional write requirements of the workload.
- ✓
Autoscale throughput with an appropriate maximum RU/s
Why this is correct
Autoscale throughput dynamically adjusts the provisioned Request Units per second (RU/s) for a Cosmos DB container or database within a user-defined minimum and maximum range. This feature is ideal for telemetry workloads with predictable peaks and troughs, as it automatically scales up during high demand to ensure performance and scales down during idle periods to optimize costs. It effectively eliminates the need for manual throughput adjustments, ensuring efficient resource utilization.
- ✗
Manual throughput set permanently to peak RU/s
Why it's wrong here
Setting manual throughput permanently to the peak RU/s ensures that the Cosmos DB instance can always handle the highest expected load for telemetry event ingestion. However, for workloads with predictable fluctuations, this approach leads to significant over-provisioning and wasted expenditure during periods of lower activity. Resources are paid for even when they are not fully utilized, making it an economically inefficient choice compared to dynamic scaling options.
- ✗
Disable indexing entirely
Why it's wrong here
Disabling indexing entirely in Azure Cosmos DB would severely degrade query performance for most operational workloads, including those involving telemetry events, making data retrieval impractical or impossible for many common query patterns. While indexing consumes Request Units during write operations, it is a fundamental component for efficient data access and is not an appropriate or primary mechanism for managing or scaling transactional throughput. Such an action would compromise the ability to query the ingested telemetry data effectively.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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