Data Factory

Introduction

Data Factory is a cloud-based data integration service that allows you to create cloud-based data-driven workflows to orchestrate and automate the movement and transformation of data.

Once a Data Factory is associated with a Turbo360 Business Application, it is possible to perform a number of operations, which will be covered in this section.

Pipeline Triggers

Turbo360 introduces a feasible solution for managing all the trigger operations by providing Triggers functionality in Data Factory resources and continues to meet the needs of its customers on a regular basis.

The main function of this latest implementation is to start and stop Data Factory triggers directly from Turbo360.

Users can view the specifics of triggers associated with the respective Data Factory resource by using Triggers option.

Users can also view a brief description of the resources associated with the respective Data Factory triggers.

Trigger Runs

Turbo360 allows users to view all the trigger runs, including details such as the trigger type and the time the trigger was executed.

The trigger runs can be filtered based on their status. Following are the statuses of the trigger runs that helps in its filtration:

• Waiting
• Running
• Succeeded
• Failed
• Waiting on Dependency
• Cancelled

Integration Runtimes

Integration Runtimes can be viewed and filtered based on the following statuses:

• Online
• Access Denied
• Initial
• Limited
• Need Registration
• Offline
• Started
• Starting
• Stopped
• Stopping

Resource Dashboard

A default resource dashboard is available for Data Factory resources in the Overview section, allowing for enhanced data visualization and tracking of real-time data.

Users are provided with the following pre-defined Dashboard widgets, which can be customised to meet their specific needs.

1. Failed Pipeline Runs
2. Failed-Cancelled-Succeded Activity Runs
3. Trigger Runs Summary
4. Total Entities Count
5. Factory Details
6. SSIS Summary

Monitoring

1. Navigate to Data Factory -> Monitoring to configure the monitoring rules for Data Factories
2. Select the necessary monitoring metrics and configure the threshold values
3. Click Save

The threshold values can also be provided with any metric name, defining the monitoring rule to be violated when the metric value configured at threshold field is met.