YohannadeOliveira-7180 120 Reputation points

What is the best way to display detailed error messages in Azure Data Factories?

Create a log workspace, configure Data Factories to send logs there, query it every 5 minutes using alerts, and trigger an action group through a webhook in a Logic App when the query returns a row. In the alert, I include dimensions for each column, such as start, end, and status. I then extract these dimensions from the JSON and transform them into a message in Slack.

Set up a 5-minute recurrence in a Logic App. Each time, query the logs with a condition "time generated >= ago(5m)." If it returns rows, post the information in Slack; otherwise, stop the execution.

Which approach would be more efficient and cost-effective?

Azure Monitor
Azure Monitor
An Azure service that is used to collect, analyze, and act on telemetry data from Azure and on-premises environments.
2,477 questions
Azure Logic Apps
Azure Logic Apps
An Azure service that automates the access and use of data across clouds without writing code.
2,542 questions
Azure Data Factory
Azure Data Factory
An Azure service for ingesting, preparing, and transforming data at scale.
8,465 questions
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Accepted answer
  1. Ritik Raj 225 Reputation points

    Both of the approaches you've described can be used to display detailed error messages in Azure Data Factories, and the choice between them depends on your specific requirements, preferences, and cost considerations. Let's analyze both options:

    1. Using Azure Monitor and Logic App with Alerts:
    • This approach leverages Azure Monitor and Logic Apps to create a robust and automated solution for error monitoring and notification.
    • You can configure alerts in Azure Monitor to trigger Logic Apps when specific conditions are met, such as when error logs are generated in Azure Data Factory.
    • It provides flexibility to set complex conditions and filter logs based on your criteria.
    • You can easily integrate with various notification channels, including Slack, to inform the relevant teams when issues occur.
    • Offers more advanced capabilities and customization options.

    Efficiency: This approach is highly efficient as it automates the monitoring process and sends notifications only when specific conditions are met, reducing noise.

    Cost-Effectiveness: While it might involve additional costs associated with Azure Monitor and Logic Apps, the cost can be justified by its automation and flexibility, especially in larger and more complex environments.

    1. Using a Recurrence in Logic App:
    • This approach relies solely on a Logic App with a 5-minute recurrence schedule and queries the logs in Azure Data Factory directly.
    • It's a simpler approach and may be suitable for smaller and less complex scenarios.
    • It doesn't offer the same level of advanced filtering and conditional monitoring as the first approach.
    • Simplicity can be an advantage if your use case is straightforward and doesn't require complex alert conditions.

    Efficiency: This approach is efficient for basic monitoring, but it's less flexible and may generate more noise if logs are checked frequently without strong filtering criteria.

    Cost-Effectiveness: This approach is likely more cost-effective as it doesn't require additional services like Azure Monitor. You'll mainly incur Logic App costs.

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