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Answer: Use Azure Monitor to track CPU usage and memory utilization, and Azure Data Factory monitoring to check pipeline run status.
Monitoring data pipeline performance involves using Azure Monitor to track critical metrics such as CPU usage, memory utilization, and network latency. Additionally, Azure Data Factory monitoring provides insights into the pipeline run status, which is essential for ensuring that the pipeline is functioning optimally. Ignoring either aspect could lead to suboptimal performance or missed errors.
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You are tasked with monitoring the performance of a data pipeline in Azure that processes large volumes of financial transaction data. The pipeline uses Azure Data Factory for orchestration and Azure Synapse Analytics for data warehousing. Describe the steps you would take to monitor the data pipeline performance, including the tools you would use and how you would interpret the results to ensure optimal performance.
A
Use Azure Monitor to track CPU usage and memory utilization, and Azure Data Factory monitoring to check pipeline run status.
B
Only use Azure Data Factory monitoring to check pipeline run status and manually review logs for any errors.
C
Use Azure Monitor to track network latency and Azure Data Factory monitoring to check pipeline run status.
D
Only use Azure Synapse Analytics monitoring to check query performance and ignore pipeline orchestration monitoring.
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