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Before deploying a new data ingestion pipeline into production, you need to benchmark its performance. Which tool or approach would you use to simulate real-world data loads and measure ingestion rates and latency?
A
Create a custom simulation in Databricks notebooks that generates data at varying loads and measures ingestion times directly.
B
Manually inject data using Azure Data Factory and monitor the ingestion performance through Databricks Spark UI.
C
Utilize Apache JMeter to generate data ingestion requests to the pipeline and monitor performance metrics in Azure Monitor.
D
Employ Azure Load Testing service to simulate high-volume data ingestion and capture performance metrics using Databricks‘ built-in monitoring.
