How can you test and ensure fault tolerance and data recovery in a complex data workflow involving multiple Azure services like Data Lake Storage, Databricks, and Synapse Analytics, especially in cases of partial failures?

Real Exam

Relying on Azure‘s built-in service redundancy and recovery features, assuming automatic fault tolerance without specific testing.

10.1%

Implementing manual switchovers to backup data pipelines and storage accounts in the event of a failure detected by monitoring alerts.

10.1%

Creating a custom simulation of partial failures (like network outages or service disruptions) in non-production environments and testing the workflow‘s response using Azure Chaos Studio.

53.2%

Using Databricks Delta Lake‘s transaction log features to rollback changes in case of failures, combined with Azure Site Recovery for service disruptions.

26.6%

Databricks Certified Data Engineer - Professional

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How can you test and ensure fault tolerance and data recovery in a complex data workflow involving multiple Azure services like Data Lake Storage, Databricks, and Synapse Analytics, especially in cases of partial failures?