Machine Learning Studio (classic) pricing

GUI-based integrated development environment for constructing and operationalizing Machine Learning workflows

Azure Machine Learning is the new service which includes designer for drag-and-drop workflows. Learn more about Azure Machine Learning.

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Studio pricing

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

Features by tier are compared in the table below:

Free Standard
Price Free $- per ML studio workspace 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 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.

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Additional resources

Machine Learning Studio (classic) details

Learn more about Machine Learning Studio (classic) features and capabilities.

Pricing calculator

Estimate your expected monthly costs for using any combination of Azure products.

SLA

Review the service-level agreement for this product.

Documentation

Review technical tutorials, videos and more Machine Learning Studio (classic) resources.

Frequently asked questions

  • 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 (classic), 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.
  • Machine Learning 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 Machine Learning.

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

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

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