Manage Azure Data Factory Monitoring with Nodinite
Don't let your business down! Get alerts for problems related to the Azure Data Factory. Users can gain access to the details without using the Azure portal using role-based Monitor Views.
You can manage Data Factory monitoring with Nodinite, and there is support for the following Data Factory services:
- Data Factory
- Pipelines
Use the Nodinite Database Monitoring Agent to monitor SSIS projects and packages.
For your business and other end-users; Delegate the power to manage, and gain insights to selected Data Factory in Azure. For example, the Nodinite Monitoring aids the support and maintenance team's people in having additional data for root cause analysis without having individual direct access to the Microsoft Azure Portal. Reducing access limits the number of attack vectors, and having fewer people with fewer access rights minimizes the risk for disruption of mission-critical services.
Application Management Team | IT Operations | Business |
---|---|---|
Let your AM team have the power to be proactive without disturbing the IT operations team | Stay in complete control with access to everything | Give your business information and self-service for solutions built using Data Factory in Azure |
Management Features
For Resources in the Role-based Monitor Views with the Remote Actions privilege grant; The following Remote Actions grouped by Category are available to manage the Data Factory:
Category | Monitoring | Actions | Metrics/Statistics |
---|---|---|---|
Data Factory | Details | - | |
Pipelines | Details Edit | - |
As an Administrator with access to the Configuration for Monitoring Agents, the additional Monitoring options are available:
Monitoring | Remote Configuration |
---|---|
Monitoring Data Factory |
|
Monitoring Data Factory Pipelines |
|
Here's an example of a Nodinite Monitor View with Data Factory related resources.
Data Factory
The 'Data Factory' Category provides one Resource for each Data Factory found using the configuration with the specified display name as the Resource name.
Example from a Monitor View with a list of 'Data Factory'.
The Data Factory category provides Resources that displays the evaluated monitored state according to built-in rules.
The following Remote Actions are available for the Data Factory Category:
Here's an example of Remote Actions for Data Factory.
Data Factory Details
To view the details about the selected Data Factory Resource; Click the Action button and then click on the Details menu item within the 'Control Center' section.
Use the 'Details' action menu item to open the details modal for the selected Data Factory.
Next, click the option to present the modal.
Here's an example of details for the selected Data Factory.
The Pipelines available within the selected Data Factory is listed within the Pipelines accordion at the bottom of the modal:
Here's an example of existing pipelines within the selected Data Factory.
Pipelines
The 'Data Factory Pipeline' Category provides one Resource for each pipeline per Data Factory found using the configuration with the deployed name as the Resource name.
Example from a Monitor View with a list of 'Data Factory Pipelines'.
The Data Factory Pipeline category provides Resources that displays the evaluated monitored state according to built-in rules, review the Monitoring Data Factory user guide for details.
The following Remote Actions are available for the Data Factory Category:
Example with the Data Factory Remote Actions.
Pipeline Details
To view the details about the selected Data Factory Pipeline Resource; Click the Action button and then click on the Details menu item within the 'Control Center' section.
Use the 'Details' action menu item to open the details modal for the selected Data Factory Pipeline.
Next, click the option to present the modal.
Example with Details about selected Data Factory Pipeline.
Edit Pipeline thresholds
You can Edit the monitoring thresholds, click on the Action button and then click on the Edit menu item within the 'Control Center' section.
Example: Edit thresholds Action button menu item.
Next, click the option to present the modal.
Here's an example of editing monitoring thresholds for selected 'Data Factory Pipeline'.
You can manage the following monitoring properties:
- Use global thresholds - When checked, the monitoring thresholds uses the global settings
- Lookback period - How far back in time to look for problems. The monitoring evaluation uses this value if the current time is higher than the last clear date-time + the lookback period
- Min Execution count -Min execution count (Warning)
- Min execution count (Error) - Enter the monitoring thresholds for the count-based evaluation. -1 means that the check is disabled (default)
- Max Execution count - Max execution count (Warning)
- Max execution count (Error) - Enter the monitoring thresholds for the count-based evaluation. -1 means that the check is disabled (default)
- Duration (ms) - Set the threshold for the maximum duration
- Warning
- Error
- Warning - Number of days before Data Factory expires to trigger the Warning alert
- Error- Number of days before Data Factory expires to trigger the Error alert
- Description - The user-friendly description of this specific Data Factory monitoring configuration
Click the Save button to persist changes.
Save button.
Next Step
Related
Azure Logging and Monitoring Overview
Prerequisites for Azure Agent