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Answer: Setting up Azure Databricks to stream logs to Azure Event Hubs and correlate with Azure Monitor alerts for real-time analysis
Setting up Azure Databricks to stream logs to Azure Event Hubs and correlate with Azure Monitor alerts for real-time analysis is the most effective method for diagnosing intermittent failures in a data pipeline. This approach allows for immediate detection and analysis of failures as they occur, leveraging real-time analysis for unpredictable and sporadic failures. Correlation with Azure Monitor alerts helps in quickly identifying anomalies or patterns indicating the cause of failure, with scalability and flexibility provided by Azure Databricks for handling large volumes of data and complex analytics. Integration with Azure services ensures a comprehensive root cause analysis approach, improving the reliability and performance of your data pipeline.
Author: LeetQuiz Editorial Team
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How can you effectively diagnose intermittent failures in a data pipeline through advanced monitoring?
A
Utilizing complex event processing in Azure Stream Analytics to detect anomalies and trigger detailed logging in Databricks
B
Setting up Azure Databricks to stream logs to Azure Event Hubs and correlate with Azure Monitor alerts for real-time analysis
C
Implementing a custom solution that uses Azure Functions to analyze logs in real-time and apply machine learning for prediction of failures
D
Configuring Azure Monitor for Databricks with a custom dashboard to visualize failure patterns and trigger in-depth analysis on demand
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