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Answer: Configuring Azure Automation Runbooks to restart clusters based on alerts from Azure Monitor for any performance degradation or downtime
Configuring Azure Automation Runbooks to restart clusters based on alerts from Azure Monitor is the most efficient and automated solution for ensuring high availability of Databricks clusters. This approach leverages automation, integration, scalability, and reliability to minimize downtime and performance issues for critical data pipelines. Azure Monitor's real-time monitoring and alerting capabilities, combined with the automation provided by Azure Automation Runbooks, offer a comprehensive solution for maintaining cluster performance and availability.
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How can you ensure the high availability of Databricks clusters for critical 24/7 data pipelines, including automatic responses to downtime or performance issues?
A
Setting up a custom solution using Azure Functions to continuously check the status of Databricks clusters and perform restarts as needed
B
Configuring Azure Automation Runbooks to restart clusters based on alerts from Azure Monitor for any performance degradation or downtime
C
Utilizing Databricks cluster event logs to manually monitor and restart clusters upon detecting downtime
D
Employing a third-party APM (Application Performance Management) tool that supports Databricks integration for 24/7 monitoring and alerting