Monitor Azure Data Factory

  • Article

This article describes:

  • The types of monitoring data you can collect for this service.
  • Ways to analyze that data.

Note

If you're already familiar with this service and/or Azure Monitor and just want to know how to analyze monitoring data, see the Analyze section near the end of this article.

When you have critical applications and business processes that rely on Azure resources, you need to monitor and get alerts for your system. The Azure Monitor service collects and aggregates metrics and logs from every component of your system. Azure Monitor provides you with a view of availability, performance, and resilience, and notifies you of issues. You can use the Azure portal, PowerShell, Azure CLI, REST API, or client libraries to set up and view monitoring data.

Monitoring methods

There are several ways to monitor Azure Data Factory.

Azure Data Factory Studio

You can monitor all of your Data Factory pipeline runs natively in Azure Data Factory Studio. To open the monitoring experience, select Launch Studio from your Data Factory page in the Azure portal, and in Azure Data Factory Studio, select Monitor from the left menu.

For more information about monitoring in Azure Data Factory Studio, see the following articles:

Azure portal

You can also monitor Azure Data Factory directly from the Azure portal. Several metrics graphs appear on the Azure portal Overview page for your Data Factory. On the left sidebar menu, you can access the Azure Activity log, or select Alerts, Metrics, Diagnostic settings, or Logs from the Monitoring section.

Monitor programmatically

You can monitor Data Factory pipelines programmatically by using .NET, PowerShell, Python, or the REST API. For more information, see the following articles:

Resource types

Azure uses the concept of resource types and IDs to identify everything in a subscription. Azure Monitor similarly organizes core monitoring data into metrics and logs based on resource types, also called namespaces. Different metrics and logs are available for different resource types. Your service might be associated with more than one resource type.

Resource types are also part of the resource IDs for every resource running in Azure. For example, one resource type for a virtual machine is Microsoft.Compute/virtualMachines. For a list of services and their associated resource types, see Resource providers.

For more information about the resource types for Azure Data Factory, see Data Factory monitoring data reference.

Data storage

For Azure Monitor:

  • Metrics data is stored in the Azure Monitor metrics database.
  • Log data is stored in the Azure Monitor logs store. Log Analytics is a tool in the Azure portal that can query this store.
  • The Azure activity log is a separate store with its own interface in the Azure portal.

You can optionally route metric and activity log data to the Azure Monitor logs store. You can then use Log Analytics to query the data and correlate it with other log data.

Many services can use diagnostic settings to send metric and log data to other storage locations outside Azure Monitor. Examples include Azure Storage, hosted partner systems, and non-Azure partner systems, by using Event Hubs.

For detailed information on how Azure Monitor stores data, see Azure Monitor data platform.

Store Data Factory pipeline run data

Data Factory stores pipeline run data for only 45 days. Use Azure Monitor to route diagnostic logs if you want to keep the data longer.

Route data to Log Analytics if you want to analyze it with complex queries, create custom alerts, or monitor across data factories. You can route data from multiple data factories to a single Log Analytics workspace.

You can use a storage account or event hub namespace that isn't in the subscription of the resource that emits logs. The user who configures the setting must have appropriate Azure role-based access control (Azure RBAC) access to both subscriptions.

Azure Monitor platform metrics

Azure Monitor provides platform metrics for most services. These metrics are:

  • Individually defined for each namespace.
  • Stored in the Azure Monitor time-series metrics database.
  • Lightweight and capable of supporting near real-time alerting.
  • Used to track the performance of a resource over time.

Collection: Azure Monitor collects platform metrics automatically. No configuration is required.

Routing: You can also usually route platform metrics to Azure Monitor Logs / Log Analytics so you can query them with other log data. For more information, see the Metrics diagnostic setting. For how to configure diagnostic settings for a service, see Create diagnostic settings in Azure Monitor.

For a list of all metrics it's possible to gather for all resources in Azure Monitor, see Supported metrics in Azure Monitor.

For a list of available metrics for Data Factory, see Data Factory monitoring data reference.

Azure Monitor resource logs

Resource logs provide insight into operations that were done by an Azure resource. Logs are generated automatically, but you must route them to Azure Monitor logs to save or query them. Logs are organized in categories. A given namespace might have multiple resource log categories.

Collection: Resource logs aren't collected and stored until you create a diagnostic setting and route the logs to one or more locations. When you create a diagnostic setting, you specify which categories of logs to collect. There are multiple ways to create and maintain diagnostic settings, including the Azure portal, programmatically, and though Azure Policy.

Routing: The suggested default is to route resource logs to Azure Monitor Logs so you can query them with other log data. Other locations such as Azure Storage, Azure Event Hubs, and certain Microsoft monitoring partners are also available. For more information, see Azure resource logs and Resource log destinations.

For detailed information about collecting, storing, and routing resource logs, see Diagnostic settings in Azure Monitor.

All resource logs in Azure Monitor have the same header fields, followed by service-specific fields. The common schema is outlined in Azure Monitor resource log schema.

Azure activity log

The activity log contains subscription-level events that track operations for each Azure resource as seen from outside that resource; for example, creating a new resource or starting a virtual machine.

Collection: Activity log events are automatically generated and collected in a separate store for viewing in the Azure portal.

Routing: You can send activity log data to Azure Monitor Logs so you can analyze it alongside other log data. Other locations such as Azure Storage, Azure Event Hubs, and certain Microsoft monitoring partners are also available. For more information on how to route the activity log, see Overview of the Azure activity log.

Monitor integration runtimes

Integration runtime is the compute infrastructure Data Factory uses to provide data integration capabilities across different network environments. Data Factory offers several types of integration runtimes:

  • Azure integration runtime
  • Self-hosted integration runtime
  • Azure-SQL Server Integration Services (SSIS) integration runtime

Azure Monitor collects metrics and diagnostics logs for all types of integration runtimes. For detailed instructions on monitoring integration runtimes, see the following articles:

Analyze monitoring data

There are many tools for analyzing monitoring data.

Azure Monitor tools

Azure Monitor supports the following basic tools:

Tools that allow more complex visualization include:

  • Dashboards that let you combine different kinds of data into a single pane in the Azure portal.
  • Workbooks, customizable reports that you can create in the Azure portal. Workbooks can include text, metrics, and log queries.
  • Power BI, a business analytics service that provides interactive visualizations across various data sources. You can configure Power BI to automatically import log data from Azure Monitor to take advantage of these visualizations.

Azure Monitor export tools

You can get data out of Azure Monitor into other tools by using the following methods:

To get started with the REST API for Azure Monitor, see Azure monitoring REST API walkthrough.

For detailed instructions on configuring diagnostic logs by using the REST API, see Set up diagnostic logs via the Azure Monitor REST API.

Kusto queries

You can analyze monitoring data in the Azure Monitor Logs / Log Analytics store by using the Kusto query language (KQL).

Important

When you select Logs from the service's menu in the portal, Log Analytics opens with the query scope set to the current service. This scope means that log queries will only include data from that type of resource. If you want to run a query that includes data from other Azure services, select Logs from the Azure Monitor menu. See Log query scope and time range in Azure Monitor Log Analytics for details.

For a list of common queries for any service, see the Log Analytics queries interface.

For example queries, select Logs under Monitoring in the left navigation of your Data Factory page in the Azure portal, and then select the Queries tab. Here are some example queries:

PipelineRuns availability: Gives the availability of the pipeline runs.

ADFPipelineRun
| where Status != 'InProgress' and Status != 'Queued'
| where FailureType != 'UserError'
| summarize availability = 100.00 - (100.00*countif(Status != 'Succeeded') / count())  by bin(TimeGenerated, 1h)), _ResourceId
| order by TimeGenerated asc
| render timechart

Activity runs Top 5 failures: Returns top five activities failing with system errors.

ADFActivityRun 
| where TimeGenerated >= ago(24h)
| where Status != 'InProgress' and Status != 'Queued'
| where FailureType != 'UserError'
| where ActivityName  in (name)
| summarize failureCount = countif(Status != 'Succeeded') by bin(TimeGenerated, 1h), ActivityName
| top 5 by failureCount desc nulls last
| order by TimeGenerated asc
| render timechart

Pipeline runs latest status: Returns latest status of pipeline runs.

ADFPipelineRun
| summarize argmax(TimeGenerated, * ) by RunId, Status, _ResourceId

Alerts

Azure Monitor alerts proactively notify you when specific conditions are found in your monitoring data. Alerts allow you to identify and address issues in your system before your customers notice them. For more information, see Azure Monitor alerts.

There are many sources of common alerts for Azure resources. For examples of common alerts for Azure resources, see Sample log alert queries. The Azure Monitor Baseline Alerts (AMBA) site provides a semi-automated method of implementing important platform metric alerts, dashboards, and guidelines. The site applies to a continually expanding subset of Azure services, including all services that are part of the Azure Landing Zone (ALZ).

The common alert schema standardizes the consumption of Azure Monitor alert notifications. For more information, see Common alert schema.

Types of alerts

You can alert on any metric or log data source in the Azure Monitor data platform. There are many different types of alerts depending on the services you're monitoring and the monitoring data you're collecting. Different types of alerts have various benefits and drawbacks. For more information, see Choose the right monitoring alert type.

The following list describes the types of Azure Monitor alerts you can create:

  • Metric alerts evaluate resource metrics at regular intervals. Metrics can be platform metrics, custom metrics, logs from Azure Monitor converted to metrics, or Application Insights metrics. Metric alerts can also apply multiple conditions and dynamic thresholds.
  • Log alerts allow users to use a Log Analytics query to evaluate resource logs at a predefined frequency.
  • Activity log alerts trigger when a new activity log event occurs that matches defined conditions. Resource Health alerts and Service Health alerts are activity log alerts that report on your service and resource health.

Some Azure services also support smart detection alerts, or recommended alert rules.

For some services, you can monitor at scale by applying the same metric alert rule to multiple resources of the same type that exist in the same Azure region. Individual notifications are sent for each monitored resource. For supported Azure services and clouds, see Monitor multiple resources with one alert rule.

Data Factory alert rules

To create and manage alerts, select Alerts under Monitoring in the left navigation of your Data Factory page in the Azure portal.

The following table lists popular alert rules for Data Factory. This is just a recommended list. You can set alerts for any metric, log entry, or activity log entry that's listed in the Data Factory monitoring data reference.

Alert type Condition Description
Metric Failed pipeline runs metrics Whenever the total Failed pipeline runs metrics is greater than 0
Metric Total entities count Whenever the maximum Total entities count is greater than 1700000
Metric Maximum allowed entities count Whenever the maximum Total factory size (GB unit) is greater than 6

Notifications provide proactive alerting during or after execution of a pipeline.

Advisor recommendations

For some services, if critical conditions or imminent changes occur during resource operations, an alert displays on the service Overview page in the portal. You can find more information and recommended fixes for the alert in Advisor recommendations under Monitoring in the left menu. During normal operations, no advisor recommendations display.

For more information on Azure Advisor, see Azure Advisor overview.

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