Machine Learning pricing

Powerful cloud-based predictive analytics

Microsoft Azure Machine Learning is a suite of offerings designed to enable customers to easily build, deploy, and share advanced analytics solutions in the cloud.

Pricing details

Studio pricing

Machine Learning Studio is offered in two tiers—Free and Standard.

Features by tier are compared in the table below:

Free Standard
Price Free $- per seat per month
$- per studio experimentation hour
Azure subscription Not required Required
Max number of modules per experiment 100 Unlimited
Max experiment duration 1 hour per experiment Up to 7 days per experiment with a maximum of 24 hours per module
Max storage space 10 GB Unlimited - BYO
Read data from On-Premises SQL Preview No Yes
Execution/performance Single node Multiple nodes
Production Web API No Yes
SLA No Yes

Hourly charges only apply to active use of the service. Where multiple meters are present they are applied concurrently.

Production Web API pricing

Azure Machine Learning enables you to deploy predictive analytics solutions as web services.

The deployed web services (new version) are subject to the following plans:

Dev/Test* Standard S1 Standard S2 Standard S3
Tier Price per month $- $- $- $-
Features
Included transactions (per month) 1,000 100,000 2,000,000 50,000,000
Included compute hours (per month) 2 25 500 12,500
Total number of web services1 2 10 100 500
Overage rates N/A

$- per 1,000 transactions

$- per API compute hour

$- per 1,000 transactions

$- per API compute hour

$- per 1,000 transactions

$- per API compute hour

* API usage restrictions apply on the testing tier—Limited to two concurrent RRS calls.
1 Number of web services customer can associate with a plan at any given point of time.

The classic version of web services is still available at the following pricing:

  • $-/production API compute hour (hourly unit)
  • $-/1,000 production API transactions (transactions unit)

Hourly charges only apply to active use of the service. Where multiple meters are present they are applied concurrently.

For more information between the classic web services and the new web services, please refer to the documentation.

Support & SLA

  • We provide technical support for all Azure services released to general availability, including Machine Learning standard tier, through Azure Support starting at $29/month. Billing and subscription management support is provided at no cost.
  • Technical support for the Machine Learning Free tier is only available through community forums. Training videos and documentation are also available to support the user community.
  • SLA—For the Request Response Service (RRS), we guarantee 99.95% availability of API transactions. For the Batch Execution Service (BES) and management APIs, we guarantee 99.9% availability of API transactions. We do not provide an SLA for Machine Learning Free tier. To learn more about the SLA, please visit the SLA page.

FAQ

  • The Azure Machine Learning Free tier is intended to provide an in-depth introduction to the Azure Machine Learning Studio. All you need to sign up is a Microsoft account. The Free tier includes free access to one Azure Machine Learning Studio workspace per Microsoft account. It includes the ability to use up to 10 GB of storage, and the ability to operationalize models as staging APIs. Free tier workloads are not covered by an SLA and are intended for development and personal use only. Free tier workloads can’t access data by connecting to an on-premises SQL server. The table above outlines many differences between the Free and Standard tiers, however other differences may exist and Free tier features are subject to change at any time.

  • All you need is a Microsoft account. Go to Azure Machine Learning home, and click on the Start Now button. Sign in with your Microsoft account and a workspace in Free tier is created for you. You can start to explore and create Machine Learning experiments right away.

  • You must first have access to an Azure subscription in order to create a Standard Machine Learning workspace. You can sign up for a 30-day free trial Azure subscription and later upgrade to a paid Azure subscription, or purchase a paid Azure subscription outright. You can then create a Machine Learning workspace from the Microsoft Azure classic portal after gaining access to the subscription. Please view the step-by-step instructions.

    Alternatively, you can be invited by a Standard Machine Learning workspace owner to access the owner’s workspace.

  • No, you can't specify your own blob storage account to use with the Free tier. To use your own Azure storage you must use the Standard tier.

  • Yes, you can operationalize machine learning models to staging API services as part of the free tier. In order to put the staging API service into production and get a production end point for the operationalized service, you must use the Standard tier.

  • The Microsoft Azure free trial offers credits that can be applied to any Azure service for one month while the Azure Machine Learning Free tier offers continuous access specifically to the Azure Machine Learning service for non-production workloads.

  • To copy your experiments from the Free tier to the Standard tier, follow the steps described below:

    1. Sign in to Azure Machine Learning Studio, and make sure you can see both the Free workspace and the Standard workspace in the workspace selector in the top navigation bar.
    2. Switch to Free workspace if you are in the Standard workspace.
    3. In the experiment list view, select an experiment you’d like to copy, and click the Copy command button.
    4. Select the Standard workspace from the pop-up dialog box and click the Copy button.
    5. Please note that all the associated datasets, trained model, etc. will be copied together with the experiment into the Standard workspace.
    6. You will need to re-run the experiment and republish your web service in the Standard workspace.
  • The Machine Learning service supports high availability by pairing across two regions within the same geography. US South Central is paired with US North Central.

  • Production API call times can vary significantly, generally ranging from hundreds of milliseconds to a few seconds, but may require minutes depending on the complexity of the data processing and machine learning model. The best way to estimate production API call times is to benchmark a model on the Machine Learning service.

  • The Machine Learning service is a multitenant service, and actual compute resources used on the backend will vary and are optimized for performance and predictability.

  • Workspace charges will be broken out separately for each applicable meter on a single bill.

For more information about Pricing FAQ, please refer to the documentation FAQ.

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