Monitor Azure AI Search

  • Article

This article describes:

  • The types of monitoring data you can collect for this service.
  • How 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.

Note

Azure AI Search doesn't monitor individual user access to content on the search service. If you require this level of monitoring, you need to implement it in your client application.

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 AI Search, see Azure AI Search 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 database store so you can query the data and correlate it with other log data using Log Analytics.

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

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.

In Azure AI Search, platform metrics measure query performance, indexing volume, and skillset invocation. For a list of available metrics for Azure AI Search, see Azure AI Search monitoring data reference.

To learn how to analyze query and index performance, see Analyze performance in Azure AI Search.

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 by category. 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 Azure 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.

For a list of all available resource log categories in Azure Monitor, see Supported resource logs 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.

For the available resource log categories, their associated Log Analytics tables, and the logs schemas for Azure AI Search, see Azure AI Search monitoring data reference.

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 Azure monitoring partners are also available. For more information on how to route the activity log, see Overview of the Azure activity log.

In Azure AI Search, activity logs reflect control plane activity such as service creation and configuration, or API key usage or management. Entries often include Get Admin Key, one entry for every call that provided an admin API key on the request. There are no details about the call itself, just a notification that the admin key was used.

The following screenshot shows Azure AI Search activity log signals you can configure in an alert.

Screenshot of the activity log signals that can be used in an alert.

For other entries, see the Management REST API reference for control plane activity that might appear in the log.

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.

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.

The following queries can get you started. See Analyze performance in Azure AI Search for more examples and guidance specific to search service.

List metrics by name

Return a list of metrics and the associated aggregation. The query is scoped to the current search service over the time range that you specify.

AzureMetrics
| project MetricName, Total, Count, Maximum, Minimum, Average

List operations by name

Return a list of operations and a count of each one.

AzureDiagnostics
| summarize count() by OperationName

Long-running queries

This Kusto query against AzureDiagnostics returns Query.Search operations, sorted by duration (in milliseconds). For more examples of Query.Search queries, see Analyze performance in Azure AI Search.

AzureDiagnostics
| project OperationName, resultSignature_d, DurationMs, Query_s, Documents_d, IndexName_s
| where OperationName == "Query.Search"
| sort by DurationMs

Indexer status

This Kusto query returns the status of indexer operations. Results include the operation name, description of the request (which includes the name of the indexer), result status (Success or Failure), and the HTTP status code. For more information about indexer execution, see Monitor indexer status.

AzureDiagnostics
| project OperationName, Description_s, Documents_d, ResultType, resultSignature_d
| where OperationName == "Indexers.Status"

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 key alert metrics, dashboards, and guidelines for Azure Landing Zone (ALZ) scenarios.

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.

You can also create the following types of alerts for some Azure services:

  • Smart detection alerts on an Application Insights resource automatically warn you of potential performance problems and failure anomalies in your web application. You can migrate smart detection on your Application Insights resource to create alert rules for the different smart detection modules.
  • Prometheus alerts alert on Prometheus metrics stored in Azure Monitor managed services for Prometheus . The alert rules are based on the PromQL open-source query language. Your service may not support this type of alert. Currently, Prometheus is used on a limited set of services with a guest operating system, such as Azure Virtual Machine and Azure Container Instances.
  • Recommended alert rules are available out-of-box for some Azure resources, including virtual machines, Azure Kubernetes Service (AKS) resources, and Log Analytics workspaces.

Monitor multiple resources

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.

Azure AI Search alert rules

The following table lists common and recommended alert rules for Azure AI Search. On a search service, throttling or query latency that exceeds a given threshold are the most commonly used alerts, but you might also want to be notified if a search service is deleted.

Alert type Condition Description
Search Latency (metric alert) Whenever the average search latency is greater than a user-specified threshold (in seconds) Send an SMS alert when average query response time exceeds the threshold.
Throttled search queries percentage (metric alert) Whenever the total throttled search queries percentage is greater than or equal to a user-specified threshold Send an SMS alert when dropped queries begin to exceed the threshold.
Delete Search Service (activity log alert) Whenever the Activity Log has an event with Category='Administrative', Signal name='Delete Search Service (searchServices)', Level='critical' Send an email if a search service is deleted in the subscription.

Advisor recommendations

If critical conditions or imminent changes occur during resource operations, an alert displays on the Overview page in the portal.

You can find more information and recommended fixes for the alert in Advisor recommendations under Monitoring. During normal operations, no advisor recommendations display.

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

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