Monitor Azure SignalR Service

This article describes:

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


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.

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 SignalR Service, see Azure SignalR Service 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.

Azure SignalR Service logs are stored in the storage account configured in diagnostic settings. A container named insights-logs-alllogs is created automatically to store resource logs. Inside the container, logs are stored in the file resourceId=/SUBSCRIPTIONS/XXXXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXXXX/RESOURCEGROUPS/XXXX/PROVIDERS/MICROSOFT.SIGNALRSERVICE/SIGNALR/XXX/y=YYYY/m=MM/d=DD/h=HH/m=00/PT1H.json. Basically, the path is a combination of resource ID and Date Time. The log files are split by hour. Therefore, the minutes are always m=00.

All logs are stored in JavaScript Object Notation (JSON) format. The following code is an example of an archive log JSON string:

    "properties": {
        "message": "Entered Serverless mode.",
        "type": "ConnectivityLogs",
        "collection": "Connection",
        "connectionId": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
        "userId": "User",
        "transportType": "WebSockets",
        "connectionType": "Client"
    "operationName": "ServerlessModeEntered",
    "category": "AllLogs",
    "level": "Informational",
    "callerIpAddress": "",
    "time": "2019-01-01T00:00:00Z",
    "location": "xxxx"

Field names for Storage destinations differ slightly from field names for Log Analytics. For details about the field name mapping between Storage and Log Analytics tables, see Resource Log table mapping.

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.

Azure SignalR Service metrics

For the list of all available metrics for Azure SignalR Service, see Azure SignalR Service monitoring data reference.

Message Count granularity

The minimum Message Count granularity is 2 KB of outbound data traffic. If a client sends small or infrequent messages totaling less than 2 KB in a sampling time period, the message count is zero (0) even though messages were sent. The way to check for a small number or size of messages is by using the metric Outbound Traffic, which is a count of bytes sent.

System Errors and User Errors

The User Errors and System Errors metrics are the percentage of attempted operations, such as connecting or sending a message, that failed. A system error is a failure in the internal system logic. A user error is generally an application error, often related to networking. Normally, the percentage of system errors should be low, near zero.


In some situations, the User errors rate is very high, especially in Serverless mode. In some browsers, the SignalR client doesn't shut down gracefully when a user closes the web page. A connection may remain open but unresponsive until Azure SignalR Service finally closes it because of timeout. The timeout closure is counted in the User Errors metric.

Metrics suitable for autoscaling

Connection Quota Utilization and Server Load show the percentage of utilization or load compared to the currently allocated unit count. These metrics are commonly used in autoscaling rules. For example, if the current allocation is one unit and there are 750 connections to the service, the Connection Quota Utilization is 750/1000 = 0.75. Server Load is calculated similarly, using values for compute capacity. For more information, see Automatically scale units of an Azure SignalR Service.


Autoscaling is a Premium Tier feature only.

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.

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.

Resource log categories

Resource logs are grouped into category groups. Category groups are a collection of different logs to help you achieve different monitoring goals. Azure SignalR supports connectivity logs, messaging logs, and Http request logs.

Connectivity logs

Connectivity logs provide detailed information for SignalR hub connections. For example:

  • Basic information like user ID, connection ID, and transport type
  • Event information like connect, disconnect, and abort events

Therefore, the connectivity log is helpful to troubleshoot connection related issues. For typical connection related troubleshooting, see connection related issues.

Messaging logs

Messaging logs provide tracing information for the SignalR hub messages received and sent via SignalR service, for example tracing ID and message type of the message. The tracing ID and message type is also logged in app server. Typically the message is recorded when it arrives at or leaves from service or server. Therefore messaging logs are helpful for troubleshooting message related issues. For typical message related troubleshooting, see message related issues.


This type of log is generated for every message. If the messages are sent frequently, messaging logs might impact the performance of the SignalR service. However, you can choose different collecting behaviors to minimize the performance impact. See resource logs collecting behaviors.

Http request logs

Http request logs provide detailed information for the HTTP requests received by Azure SignalR, for example status code and URL of the request. Http request log is helpful to troubleshoot request-related issues.

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

Resource logs collecting behaviors

There are two typical scenarios for using resource logs, especially for messaging logs.

  • Message quality logs whether the message was sent or received successfully, or records every message that is delivered via SignalR service.
  • Performance logs message latency, or tracks the message in a few connections instead of all the connections.

Therefore, SignalR service provides two kinds of collecting behaviors:

  • Collect all collects logs in all connections.
  • Collect partially collects logs in some specific connections.

For more details about resource log collecting behaviors and how to configure them, see Resource logs collecting behaviors.

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.

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.
  • Grafana, an open platform tool that excels in operational dashboards. You can use Grafana to create dashboards that include data from multiple sources other than Azure Monitor.
  • 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).


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 Kusto queries for Azure SignalR Service, see Queries for the SignalRServiceDiagnosticLogs table.


Query field names for Storage destinations differ slightly from field names for Log Analytics. For details about the field name mappings between Storage and Log Analytics tables, see Resource Log table mapping.


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, Prometheus 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.

Azure SignalR Service alert rules

The following table lists some suggested alert rules for Azure SignalR Service. These alerts are just examples. You can set alerts for any metric, log entry, or activity log entry listed in the Azure SignalR Service monitoring data reference.

Alert type Condition Description
Platform metrics Connection Quota Utilization Whenever the maximum Connection Quota Utilization is greater than dynamic threshold
Platform metrics Delete SignalR Whenever the Activity Log has an event with Category='Administrative', Signal name='Delete SignalR (SignalR)'

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.