You need to automatically scale an Azure SQL Database based on workload patterns. The solution must use built-in Azure features and minimize manual intervention. Which feature should you configure?
Autoscale automatically adjusts resources based on workload.
Why this answer
Azure SQL Database supports built-in autoscale through the 'Autoscale' feature (serverless compute tier or DTU-based scaling policies), which automatically adjusts resources based on workload patterns without manual intervention. This is the only option that leverages a native Azure feature for dynamic, reactive scaling rather than scheduled or manual actions.
Exam trap
The trap here is that candidates confuse 'automation' (Azure Automation runbooks) with 'automatic scaling' (built-in autoscale), or mistakenly think Azure Data Factory can manage database scaling, when only the native autoscale feature provides dynamic, policy-driven scaling without manual intervention.
How to eliminate wrong answers
Option A is wrong because Azure Data Factory is an ETL/integration service, not a database scaling mechanism; pipeline triggers cannot directly modify Azure SQL Database service tier or compute resources. Option B is wrong because Azure Automation runbooks require custom scripting and scheduled execution, which is not 'built-in' automatic scaling and introduces manual maintenance overhead. Option D is wrong because manually adjusting eDTUs in an elastic pool contradicts the requirement to 'minimize manual intervention' and does not provide automatic scaling based on workload patterns.