Custom metrics in Azure Monitor (preview) - Azure Monitor (2023)

  • Article

As you deploy resources and applications in Azure, start collecting telemetry to gain insights into their performance and health. Azure makes some metrics available to you out of the box. These metrics are called standard or platform.

Collect custom performance indicators or business-specific metrics to provide deeper insights. These custom metrics can be collected via your application telemetry, an agent that runs on your Azure resources, or even an outside-in monitoring system. They can then be submitted directly to Azure Monitor. Once custom metrics are published to Azure Monitor, you can browse, query, and alert on them for your Azure resources and applications along side the standard Azure metrics.

Azure Monitor custom metrics are currently in public preview.

Methods to send custom metrics

Custom metrics can be sent to Azure Monitor via several methods:

  • Instrument your application by using the Azure Application Insights SDK and send custom telemetry to Azure Monitor.
  • Install the Azure Monitor agent (preview) on your Windows or Linux Azure VM. Use a data collection rule to send performance counters to Azure Monitor metrics.
  • Install the Azure Diagnostics extension on your Azure VM, Virtual Machine Scale Set, classic VM, or classic cloud service. Then send performance counters to Azure Monitor.
  • Install the InfluxData Telegraf agent on your Azure Linux VM. Send metrics by using the Azure Monitor output plug-in.
  • Send custom metrics directly to the Azure Monitor REST API, https://<azureregion><AzureResourceID>/metrics.

Pricing model and retention

For details on when billing is enabled for custom metrics and metrics queries, check the Azure Monitor pricing page. In summary, there's no cost to ingest standard metrics (platform metrics) into an Azure Monitor metrics store, but custom metrics incur costs when they enter general availability. Queries to the metrics API do incur costs.

Custom metrics are retained for the same amount of time as platform metrics.


Metrics sent to Azure Monitor via the Application Insights SDK are billed as ingested log data. They incur additional metrics charges only if the Application Insights feature Enable alerting on custom metric dimensions has been selected. This checkbox sends data to the Azure Monitor metrics database by using the custom metrics API to allow the more complex alerting. Learn more about the Application Insights pricing model and prices in your region.

How to send custom metrics

When you send custom metrics to Azure Monitor, each data point, or value, reported in the metrics must include the following information.


To submit custom metrics to Azure Monitor, the entity that submits the metric needs a valid Azure Active Directory (Azure AD) token in the Bearer header of the request. Supported ways to acquire a valid bearer token include:

  • Managed identities for Azure resources. You can use a managed identity to give resources permissions to carry out certain operations. An example is allowing a resource to emit metrics about itself. A resource, or its managed identity, can be granted Monitoring Metrics Publisher permissions on another resource. With this permission, the managed identity can also emit metrics for other resources.

  • Azure AD service principal. In this scenario, an Azure AD application, or service, can be assigned permissions to emit metrics about an Azure resource. To authenticate the request, Azure Monitor validates the application token by using Azure AD public keys. The existing Monitoring Metrics Publisher role already has this permission. It's available in the Azure portal.

    The service principal, depending on what resources it emits custom metrics for, can be given the Monitoring Metrics Publisher role at the scope required. Examples are a subscription, resource group, or specific resource.


When you request an Azure AD token to emit custom metrics, ensure that the audience or resource that the token is requested for is Be sure to include the trailing slash.


The subject property captures which Azure resource ID the custom metric is reported for. This information is encoded in the URL of the API call. Each API can submit metric values for only a single Azure resource.


You can't emit custom metrics against the resource ID of a resource group or subscription.


The region property captures the Azure region where the resource you're emitting metrics for is deployed. Metrics must be emitted to the same Azure Monitor regional endpoint as the region where the resource is deployed. For example, custom metrics for a VM deployed in West US must be sent to the WestUS regional Azure Monitor endpoint. The region information is also encoded in the URL of the API call.


During the public preview, custom metrics are available in only a subset of Azure regions. A list of supported regions is documented in a later section of this article.


Each data point sent to Azure Monitor must be marked with a timestamp. This timestamp captures the date and time at which the metric value is measured or collected. Azure Monitor accepts metric data with timestamps as far as 20 minutes in the past and 5 minutes in the future. The timestamp must be in ISO 8601 format.


Namespaces are a way to categorize or group similar metrics together. By using namespaces, you can achieve isolation between groups of metrics that might collect different insights or performance indicators. For example, you might have a namespace called contosomemorymetrics that tracks memory-use metrics which profile your app. Another namespace called contosoapptransaction might track all metrics about user transactions in your application.


The name property is the name of the metric that's being reported. Usually, the name is descriptive enough to help identify what's measured. An example is a metric that measures the number of memory bytes used on a VM. It might have a metric name like Memory Bytes In Use.

Dimension keys

A dimension is a key/value pair that helps describe other characteristics about the metric that's being collected. By using the other characteristics, you can collect more information about the metric, which allows for deeper insights.

For example, the Memory Bytes In Use metric might have a dimension key called Process that captures how many bytes of memory each process on a VM consumes. By using this key, you can filter the metric to see how much memory specific processes use or to identify the top five processes by memory usage.

Dimensions are optional, and not all metrics have dimensions. A custom metric can have up to 10 dimensions.

Dimension values

When you're reporting a metric data point, for each dimension key on the reported metric, there's a corresponding dimension value. For example, you might want to report the memory that ContosoApp uses on your VM:

  • The metric name would be Memory Bytes in Use.
  • The dimension key would be Process.
  • The dimension value would be ContosoApp.exe.

When you're publishing a metric value, you can specify only a single dimension value per dimension key. If you collect the same memory utilization for multiple processes on the VM, you can report multiple metric values for that timestamp. Each metric value would specify a different dimension value for the Process dimension key.

Although dimensions are optional, if a metric post defines dimension keys, corresponding dimension values are mandatory.

Metric values

Azure Monitor stores all metrics at 1-minute granularity intervals. During a given minute, a metric might need to be sampled several times. An example is CPU utilization. Or a metric might need to be measured for many discrete events, such as sign-in transaction latencies.

To limit the number of raw values that you have to emit and pay for in Azure Monitor, locally pre-aggregate and emit the aggregated values:

  • Min: The minimum observed value from all the samples and measurements during the minute.
  • Max: The maximum observed value from all the samples and measurements during the minute.
  • Sum: The summation of all the observed values from all the samples and measurements during the minute.
  • Count: The number of samples and measurements taken during the minute.

For example, if there were four sign-in transactions to your app during a minute, the resulting measured latencies for each might be:

Transaction 1Transaction 2Transaction 3Transaction 4
7 ms4 ms13 ms16 ms

Then the resulting metric publication to Azure Monitor would be:

  • Min: 4
  • Max: 16
  • Sum: 40
  • Count: 4

If your application can't pre-aggregate locally and needs to emit each discrete sample or event immediately upon collection, you can emit the raw measure values. For example, each time a sign-in transaction occurs on your app, you publish a metric to Azure Monitor with only a single measurement. So, for a sign-in transaction that took 12 milliseconds, the metric publication would be:

  • Min: 12
  • Max: 12
  • Sum: 12
  • Count: 1

With this process, you can emit multiple values for the same metric/dimension combination during a given minute. Azure Monitor then takes all the raw values emitted for a given minute and aggregates them.

Sample custom metric publication

In the following example, you create a custom metric called Memory Bytes in Use under the metric namespace Memory Profile for a virtual machine. The metric has a single dimension called Process. For the timestamp, metric values are emitted for two processes.

{ "time": "2018-08-20T11:25:20-7:00", "data": { "baseData": { "metric": "Memory Bytes in Use", "namespace": "Memory Profile", "dimNames": [ "Process" ], "series": [ { "dimValues": [ "ContosoApp.exe" ], "min": 10, "max": 89, "sum": 190, "count": 4 }, { "dimValues": [ "SalesApp.exe" ], "min": 10, "max": 23, "sum": 86, "count": 4 } ] } } }


Application Insights, the diagnostics extension, and the InfluxData Telegraf agent are already configured to emit metric values against the correct regional endpoint and carry all the preceding properties in each emission.

Custom metric definitions

Each metric data point published contains a namespace, name, and dimension information. The first time a custom metric is emitted to Azure Monitor, a metric definition is automatically created. This new metric definition is then discoverable on any resource that the metric is emitted from via the metric definitions. There's no need to predefine a custom metric in Azure Monitor before it's emitted.


Azure Monitor doesn't support defining Units for a custom metric.

Using custom metrics

After custom metrics are submitted to Azure Monitor, you can browse through them via the Azure portal and query them via the Azure Monitor REST APIs. You can also create alerts on them to notify you when certain conditions are met.


You need to have a reader or contributor role to view custom metrics. See Monitoring Reader.

Browse your custom metrics via the Azure portal

  1. Go to the Azure portal.
  2. Select the Monitor pane.
  3. Select Metrics.
  4. Select a resource that you've emitted custom metrics against.
  5. Select the metrics namespace for your custom metric.
  6. Select the custom metric.

For more information on viewing metrics in the Azure portal, see Getting started with Azure Metrics Explorer.

Supported regions

During the public preview, the ability to publish custom metrics is available only in a subset of Azure regions. This restriction means that metrics can be published only for resources in one of the supported regions. For more information on Azure regions, see Azure geographies.

The following table lists supported Azure regions for custom metrics. It also lists the corresponding endpoints that metrics for resources in those regions should be published to. The Azure region code used in the endpoint prefix is just the name of the region with whitespace removed.

Azure regionRegional endpoint prefix
All Public Cloud Regionshttps://<azure_region_code>

Latency and storage retention

A newly added metric or a newly added dimension to a metric might take up to 3 minutes to appear. After the data is in the system, it should appear in less than 30 seconds 99 percent of the time.

If you delete a metric or remove a dimension, the change can take a week to a month to be deleted from the system.

Quotas and limits

Azure Monitor imposes the following usage limits on custom metrics:

Total active time series in a subscription per region50,000
Dimension keys per metric10
String length for metric namespaces, metric names, dimension keys, and dimension values256 characters
The combined length of all custom metric names, using utf-8 encoding64 KB

An active time series is defined as any unique combination of metric, dimension key, or dimension value that has had metric values published in the past 12 hours.

To understand the limit of 50,000 on time series, consider the following metric:

Server response time with Dimensions: Region, Department, CustomerID

With this metric, if you have 10 regions, 20 departments, and 100 customers, that gives you 10 x 20 x 100 = 20,000 time series.

If you have 100 regions, 200 departments, and 2,000 customers, that gives you 100 x 200 x 2,000 = 40 million time series, which is far over the limit just for this metric alone.

Again, this limit isn't for an individual metric. It's for the sum of all such metrics across a subscription and region.

Follow the steps below to see your current total active time series metrics, and more information to assist with troubleshooting.

  1. Navigate to the Monitor section of the Azure portal.
  2. Select Metrics on the left hand side.
  3. Under Select a scope, check the applicable subscription and resource groups.
  4. Under Refine scope, choose Custom Metric Usage and the desired location.
  5. Select the Apply button.
  6. Choose either Active Time Series, Active Time Series Limit, or Throttled Time Series.

There is a limit of 64 KB on the combined length of all custom metrics names, assuming utf-8 or 1 byte per character. If the 64-KB limit is exceeded, metadata for additional metrics won't be available. The metric names for additional custom metrics won't appear in the Azure portal in selection fields, and won't be returned by the API in requests for metric definitions. The metric data is still available and can be queried.

When the limit has been exceeded, reduce the number of metrics you're sending or shorten the length of their names. It then takes up to two days for the new metrics' names to appear.

To avoid reaching the limit, don't include variable or dimensional aspects in your metric names.For example, the metrics for server CPU usage,CPU_server_12345678-319d-4a50-b27e-1234567890ab and CPU_server_abcdef01-319d-4a50-b27e-abcdef012345 should be defined as metric CPU and with a Server dimension.

Design limitations and considerations

Using Application Insights for the purpose of auditing. The Application Insights telemetry pipeline is optimized for minimizing the performance impact and limiting the network traffic from monitoring your application. As such, it throttles or samples (takes only a percentage of your telemetry and ignores the rest) if the initial dataset becomes too large. Because of this behavior, you can't use it for auditing purposes because some records are likely to be dropped.

Metrics with a variable in the name. Don't use a variable as part of the metric name. Use a constant instead. Each time the variable changes its value, Azure Monitor generates a new metric. Azure Monitor then quickly hits the limit on the number of metrics. Generally, when developers want to include a variable in the metric name, they really want to track multiple time series within one metric and should use dimensions instead of variable metric names.

High-cardinality metric dimensions. Metrics with too many valid values in a dimension (a high cardinality) are much more likely to hit the 50,000 limit. In general, you should never use a constantly changing value in a dimension. Timestamp, for example, should never be a dimension. You can use server, customer, or product ID, but only if you have a smaller number of each of those types.

As a test, ask yourself if you would ever chart such data on a graph. If you have 10 or maybe even 100 servers, it might be useful to see them all on a graph for comparison. But if you have 1,000, the resulting graph would likely be difficult or impossible to read. A best practice is to keep it to fewer than 100 valid values. Up to 300 is a gray area. If you need to go over this amount, use Azure Monitor custom logs instead.

If you have a variable in the name or a high-cardinality dimension, the following issues can occur:

  • Metrics become unreliable because of throttling.
  • Metrics Explorer won't work.
  • Alerting and notifications become unpredictable.
  • Costs can increase unexpectedly. Microsoft isn't charging for custom metrics with dimensions while this feature is in public preview. After charges start in the future, you'll incur unexpected charges. The plan is to charge for metrics consumption based on the number of time series monitored and number of API calls made.

If the metric name or dimension value is populated with an identifier or high-cardinality dimension by mistake, you can easily fix it by removing the variable part.

But if high cardinality is essential for your scenario, the aggregated metrics are probably not the right choice. Switch to using custom logs (that is, trackMetric API calls with trackEvent). However, consider that logs don't aggregate values, so every single entry will be stored. As a result, if you have a large volume of logs in a small time period (1 million a second, for example), it can cause throttling and ingestion delays.

Next steps

Use custom metrics from various services:

  • Virtual machine
  • Virtual Machine Scale Set
  • Azure virtual machine (classic)
  • Linux virtual machine using the Telegraf agent
  • Classic cloud service


What are the limitations of Azure Monitor? ›

Data collection rules
Maximum number of data flows10
Maximum number of data streams10
Maximum number of extensions10
Maximum size of extension settings32 Kb
6 more rows
May 31, 2023

How do I create a custom metric in Azure Monitor? ›

Browse your custom metrics via the Azure portal
  1. Go to the Azure portal.
  2. Select the Monitor pane.
  3. Select Metrics.
  4. Select a resource that you've emitted custom metrics against.
  5. Select the metrics namespace for your custom metric.
  6. Select the custom metric.
Feb 15, 2023

What is the difference between Azure metrics and Azure Monitor? ›

Azure Monitor Metrics can only store numeric data in a particular structure, whereas Azure Monitor Logs can store a variety of data types that have their own structures. You can also perform complex analysis on Azure Monitor Logs data by using log queries, which can't be used for analysis of Azure Monitor Metrics data.

How long are Azure metrics retained for within Azure Monitor? ›

Platform and custom metrics are stored for 93 days with the following exceptions: Classic guest OS metrics: These performance counters are collected by the Windows diagnostic extension or the Linux diagnostic extension and routed to an Azure Storage account.

What are the limitations of real user monitoring? ›

Limitations of Real User Monitoring

Equally, traffic volumes are often quite low in pre-production environments, which makes it hard to gain statistically significant results. This is where synthetic testing can help, and why RUM and synthetic testing work together to provide useful performance data.

How many types of data does Azure Monitor collect? ›

Azure Monitor collects data from various sources. These sources include logs and metrics from the Azure platform and resources, custom applications, and agents running on virtual machines.

What are the three main functions of Azure Monitor? ›

Accelerate time to market, deliver innovative experiences, and improve security with Azure application and data modernization. Seamlessly integrate applications, systems, and data for your enterprise. Run your Oracle database and enterprise applications on Azure.

What are the two main kinds of data Azure Monitor works with? ›

All data collected by Azure Monitor fits into one of two fundamental types: metrics and logs.

What is the difference between Max and average in Azure metrics? ›

Average – the average of the metric values captured over the aggregation interval. For most metrics, this value is Sum/Count. Min – the smallest value captured over the aggregation interval. Max – the largest value captured over the aggregation interval.

Where does Azure Monitor store even data? ›

Azure Monitor stores data in data stores for each of the pillars of observability: metrics, logs, distributed traces, and changes. Each store is optimized for specific types of data and monitoring scenarios.

How many minutes downtime is 99.99 Azure? ›

Identify dependencies
SLADowntime per weekDowntime per year
99%1.68 hours3.65 days
99.9%10.1 minutes8.76 hours
99.95%5 minutes4.38 hours
99.99%1.01 minutes52.56 minutes
1 more row
May 30, 2023

How long does Azure Monitor keep data? ›

You can keep data in interactive retention between 4 and 730 days. You can set the archive period for a total retention time of up to 2,556 days (seven years). To set the retention and archive duration for a table in the Azure portal: From the Log Analytics workspaces menu, select Tables.

How do you use custom metrics? ›

Set up custom metrics
  1. Sign in to Google Analytics.
  2. Click Admin, and navigate to the property to which you want to add custom metrics.
  3. In the PROPERTY column, click Custom Definitions > Custom Metrics.
  4. Click the New Custom Metric button.
  5. Add a Name. ...
  6. From the Formatting Type dropdown, select an Integer, Currency, or Time.

Can we create rules in Azure Monitor to autoscale resources in Azure? ›

You can define one or more rules for both scale-in and scale-out actions. Define up to a total of 10 rules per profile. Each scale condition or profile defines the default, maximum, and minimum number of instances that can run under that profile.

Which of the following metrics do you need to design a custom CloudWatch metric? ›

The correct answer is option A (Memory Utilization of an EC2 instance).

What are the challenges of monitoring system? ›

What are some common challenges of Monitoring and Evaluation?
  • Time and Resource. Not surprisingly, one of the major challenges in effective monitoring and evaluation processes is in finding the time and resource to do it well. ...
  • Technical Expertise. ...
  • Culture/Attitudes. ...
  • Lack of Focus.
Jul 15, 2021

What is the difference between synthetic monitoring and real user monitoring? ›

While real user monitoring tracks the level of satisfaction of your customers in real-time, synthetic monitoring tests the performance of your website in a controlled environment by running predefined scripts against your website to track service availability, benchmark performance against competitors, and response ...

What are the disadvantages of synthetic monitoring? ›

Narrow view of performance: Synthetic Monitoring can't match the rich diversity of performance variables that exist in the real world. Because you are not monitoring actual users, you aren't really getting any data on how your product is used in the real world.

What are the 3 types of data that can be stored in Azure? ›

There are 4 types of storage in Azure, namely:
  • File.
  • Blob.
  • Queue.
  • Table.
May 3, 2017

What is the difference between Azure Monitor and Log Analytics? ›

Azure Monitor builds on top of Azure Log Analytics, the platform service that gathers log and metrics data from all your resources. The easiest way to think about Azure Monitor vs Log Analytics is that Azure Monitor is the marketing name, whereas Azure Log Analytics is the technology that powers it.

What is the difference between Azure Monitor workbook and dashboard? ›

Azure dashboards are useful in providing a "single pane of glass" of your Azure infrastructure and services. While a workbook provides richer functionality, a dashboard can combine Azure Monitor data with data from other Azure services.

What are the three alert states in Azure Monitor? ›

Alert severity
Sev 0Critical
Sev 1Error
Sev 2Warning
Sev 3Informational
1 more row

Can Azure Monitor send alerts? ›

Alerts help you detect and address issues before users notice them by proactively notifying you when Azure Monitor data indicates there might be a problem with your infrastructure or application. You can alert on any metric or log data source in the Azure Monitor data platform.

Which is the best monitoring service in Azure? ›

Top 7 Azure Monitoring Tools [Azure Monitors For 2023]
  • Comparison of Best Azure Monitors.
  • #1) Serverless360 (Best Overall)
  • #2) Site24x7.
  • #3) ManageEngine M365 Manager Plus.
  • #4) Application Insights.
  • #5) Azure Monitor.
  • #6) Service Bus Explorer.
  • #7) Cerebrata.
May 9, 2023

What are the roles in Azure Monitor? ›

Azure Monitor provides two out-of-the-box roles: Monitoring Reader and Monitoring Contributor. Azure Monitor Logs also provides built-in roles for managing access to data in a Log Analytics workspace, as described in Manage access to Log Analytics workspaces.

What features are provided by Azure Monitor? ›

Azure Monitor.

Collects and analyzes performance metrics as well as diagnostic and activity logs from cloud environments to determine application availability and performance. Azure Monitor can also provide insight into the operation of applications, containers and VMs running in the cloud.

Which two features can be integrated with Azure Monitor? ›

Microsoft combined three unique services—Azure Monitor, Log Analytics, and Application Insights—under the umbrella of Azure Monitor to provide powerful end-to-end monitoring of your applications and the components they rely on. Log Analytics and Application Insights are now features of Azure Monitor.

Which metric is used to Monitor the performance in Azure data Factory? ›

With Azure Monitor, you can gain visibility into the performance and health of your Azure workloads. The most important type of Monitor data is the metric, which is also called the performance counter.

What are the dotted lines in Azure metrics? ›

Azure metrics charts use dashed line style to indicate that there is a missing value (also known as “null value”) between two known time grain data points.

How do I create a dashboard with Azure Monitor data? ›

Create a blank dashboard
  1. In the Azure portal, select the menu at the top left of the screen.
  2. Select Dashboard from the menu. Your default Azure dashboard will appear.
  3. Select + New Dashboard and then Blank dashboard.
  4. Give your dashboard a name.
  5. Select Save.
Jul 27, 2022

What are the three pillars of observability in Azure? ›

Metrics, logs, and distributed traces are commonly referred to as the three pillars of observability.

What is the difference between Azure Monitor and Event Hub? ›

Here's how the solution fits together: Azure Monitor collects logs for most Microsoft Azure services and streams the data to an Azure Event Hub. Azure Event Hubs is a data streaming platform and event ingestion service. In this pipeline, an Event Hub streams the logs collected by Azure Monitor to an Azure function.

What are the benefits of Azure Monitor? ›

Azure Monitor is a powerful reporting and analytics tool. Azure Monitor maximizes the supply and performance of your applications and services by delivering an inclusive solution for collecting, analyzing, and working on telemetry from the user's cloud and on-premises environments.

What is the lowest SLA in Azure? ›

The SLA starts at a lowly 95% on Single Instance Virtual Machines using Standard HDD Disks to 99,99% for multi-instance Virtual Machines deployed across two or more Availability Zones in the same Azure region. SLAs are updated regularly and therefore always have a version number.

What happens if Azure does not meet SLA? ›

SLAs For Azure Products And Services

Performance-target range from 99.9% (three nines) to 99.99% (four nines). If a service fails to meet the guarantees, a percentage of the monthly service fees can be credited to you.

How much downtime do you get with a 99.95% availability? ›

Percentage calculation
Availability %Downtime per yearDowntime per month
99.95% ("three nines five")4.38 hours21.92 minutes
99.99% ("four nines")52.60 minutes4.38 minutes
99.995% ("four nines five")26.30 minutes2.19 minutes
99.999% ("five nines")5.26 minutes26.30 seconds
12 more rows

What is the difference between Azure Advisor and Azure Monitor? ›

Azure Advisor provides personalized recommendations to optimize Azure resources for performance, security, reliability, and cost-effectiveness. On the other hand, Azur Monitor provides a platform for collecting, analyzing, and acting on telemetry data generated by Azure resources and applications.

What is the limitation of Azure? ›

A single user can belong to a maximum of 500 Azure AD tenants as a member or a guest. A single user can create a maximum of 200 directories. You can add no more than 5,000 managed domain names.

What are the limitations of Azure functions? ›

During scale-out, there's currently a limit of 500 instances per subscription per hour for Linux apps on a Consumption plan. In some regions, Linux apps on a Premium plan can scale to 100 instances. For more information, see the Premium plan article.

What are the limitations of Azure cognitive search? ›

Index limits
ResourceFreeBasic 1
Maximum indexes35 or 15
Maximum simple fields per index 21000100
Maximum complex collections per index4040
Maximum elements across all complex collections per document 330003000
4 more rows
Dec 7, 2022

What are the limitations of Azure cognitive services? ›

Overall limits on the content in the project:
  • Length of answer text: 25,000 characters.
  • Length of question text: 1,000 characters.
  • Length of metadata key text: 100 characters.
  • Length of metadata value text: 500 characters.
  • Supported characters for metadata name: Alphabets, digits, and _
Feb 28, 2023

What are the biggest challenges of working on Azure? ›

Microsoft Azure Challenges (in-depth)
  • Scaling Up – When you need more computing power, get more powerful processing hardware for your solution.
  • Scaling Out – Spread your processing power across a cluster of hardware that can be increased or decreased based on your needs.
Feb 24, 2020

What are some of the limitations with a free Azure account? ›

You get a limited quantity of free services each month with your Azure free account. The free quantity expires at the end of the month and doesn't roll over to the next month. For example, you get 5 GB of File storage each month. If in a month, you only use 2 GB, the remaining 3 GB doesn't roll over to the next month.

What is the limitation of Azure data sync? ›

Limitations on service and database dimensions
Maximum number of sync groups any database can belong to.5
Maximum number of endpoints in a single sync group30
Maximum number of on-premises endpoints in a single sync group.5
Database, table, schema, and column names50 characters per name
3 more rows
Mar 3, 2023

What are functions limitations? ›

Informally, a function f assigns an output f(x) to every input x. We say that the function has a limit L at an input p, if f(x) gets closer and closer to L as x moves closer and closer to p. More specifically, when f is applied to any input sufficiently close to p, the output value is forced arbitrarily close to L.

What are the project limitations in Azure boards? ›

Projects. Azure DevOps Services limits each organization to 1000 projects per organization, an increase over the previous limit of 300 projects. Above 300 projects certain experiences, such as connecting to a project from Visual Studio, may start to degrade.

What is the top limit for Azure search? ›

Azure Cognitive Search uses server-side paging to prevent queries from retrieving too many documents at once. The default page size is 50, while the maximum page size is 1000. This means that by default Search Documents returns at most 50 results if you don't specify $top.

What are the limits of Azure artifact? ›

Azure Artifacts is free for every organization up to 2 GiB of storage. Once you reach the maximum storage limit, you can no longer upload new artifacts and need to delete some of your existing artifacts or set up billing to increase your storage limit.

What is the limit of cognitive search index? ›

An Azure Cognitive Search index can only contain up to 1000 fields.

What is the limitation of Azure Virtual Desktop? ›

You can currently deploy up to 132 VMs in a single ARM template deployment in the Azure Virtual Desktop portal. To create more than 132 VMs, run the ARM template deployment in the Azure Virtual Desktop portal multiple times.


Top Articles
Latest Posts
Article information

Author: Francesca Jacobs Ret

Last Updated: 19/11/2023

Views: 5561

Rating: 4.8 / 5 (48 voted)

Reviews: 87% of readers found this page helpful

Author information

Name: Francesca Jacobs Ret

Birthday: 1996-12-09

Address: Apt. 141 1406 Mitch Summit, New Teganshire, UT 82655-0699

Phone: +2296092334654

Job: Technology Architect

Hobby: Snowboarding, Scouting, Foreign language learning, Dowsing, Baton twirling, Sculpting, Cabaret

Introduction: My name is Francesca Jacobs Ret, I am a innocent, super, beautiful, charming, lucky, gentle, clever person who loves writing and wants to share my knowledge and understanding with you.