This topic describes the FAQ about billing.

Which projects incur fees?

  • Experiments that run in Machine Learning Studio incur fees. In detail, the algorithm components of experiments incur fees during computing.
  • Instances that run in Data Science Workshop (DSW) incur fees caused by computing resources. We recommend that you stop instances that you no longer use, avoiding unnecessary costs.
  • Services of shared resource groups on Elastic Algorithm Service (EAS) incur fees regardless of whether the services are called. Services that run in dedicated pay-as-you-go resource groups incur fees because these resource groups are pay-as-you-go. Services that run in dedicated subscription resource groups do not incur fees because these resource groups have been paid when you buy them.
    The following content describes the billing rules: (For more information, see Billing of EAS.)
    • Dedicated pay-as-you-go resource groups in Running state are billable.
      Note When you scale in or out a dedicated resource group that is in running state, the group enters an intermediate state, which is Scaling out or Scaling in. Resources that are used while the group is in this intermediate state are also billable.
    • Services that are deployed in shared resource groups and are in Running state are billable.
      Note When you scale out a deployed service, the service enters an intermediate state, which is Pending. Resources that are used while the service is in this intermediate state are also billable.

How do I stop an project that is being billed?

  • To stop a billable visual modeling project on the Machine Learning Studio page, perform the following steps:
    1. Log on to the Machine Learning Platform for AI (PAI) console.
    2. In the left-side navigation pane, choose Model Training > Studio-Modeling Visualization.
    3. On the PAI Visualization Modeling page, find the project and click Machine Learning.Go to the Machine Learning Studio page
    4. In the left-side navigation pane of the Machine Learning Studio page, click Experiments.
    5. Click the experiment that you want to stop and then click Stop in the upper part of the canvas.
  • To stop a billable Notebook modeling project in DSW, perform the following steps:
    • Log on to the Machine Learning Platform for AI (PAI) console.
    • In the left-side navigation pane, choose Model Training > DSW-Notebook Service.
    • On the Notebook Models page, find the instance that you want to stop and then click Stop in the Actions column.

      After the instance is stopped, the status in the Status column changes to Stopped. If the instance is a pay-as-you-go instance, the system stops billing the instance. Before you exit DSW, make sure that unwanted instances are in the Stopped state. Otherwise, these instances continue to incur fees.

  • To stop a billable service in EAS, perform the following steps:
    • For a running service in a dedicated pay-as-you-go resource group:
      Reduce the number of ECS instances in the dedicated resource group to 0 by performing the following steps:
      1. On the Elastic Algorithm Service page, find the pay-as-you-go resource group and click Scale in/Stop.
      2. If you are sure that you no longer want to use the resource group, click I know in the message.
      3. On the Update page, set Number Of Nodes to 0 and select EAS Resource Group (Pay-As-You-Go) Agreement of Service.
      4. Click Activate.
    • For a running service in a shared resource group
      On the Elastic Algorithm Service page, find the service that you want to stop and click Stop in the Operating column. The billing for the service is also stopped.
      Note To avoid unnecessary business losses, make sure that the stopped service is no longer required.
      Stop billing

How do I query deductions and details?

In the top navigation bar, choose Expenses > Bills. On the Bills page, you can set the filter conditions to view bill details. For more information, see . In particular, on the Bills tab, the Product Detail column indicates the module that generates the expense. The following content describes the values related to PAI:
  • PaiEasPostpay: fees incurred by dedicated pay-as-you-go resource groups in EAS.
  • Machine Learning Platform for AI: fees incurred by training of experiments on the Machine Learning Studio page, pay-as-you-go instances on DSW, and services of shared resource groups on EAS. To view the bill details, click the Details tab and view the Billing Item column. The following table describes the mapping between the billing items and expenses.
    Product Billing item Instance ID Expense source
    Machine Learning Platform for AI CUUsage
    • text_analysis
    • data_analysis
    • data_manipulation
    • deep_learning
    • default
    		 The fees incurred by training of experiments on the Machine Learning Studio page.
    Machine Learning Platform for AI DSW_CPU_Large Usage None The fees incurred by pay-as-you-go instances on DSW.
    Machine Learning Platform for AI EAS CPU Usage None The fees incurred by services of shared resource groups on EAS.
  • pai_eas_prepay: fees incurred by dedicated subscription resource groups on EAS.
  • PAI Prepay: fees incurred by subscription computing resources on DSW.

Why are fees deducted after I stop a billable project?

Fees are not immediately deducted after you stop a project. Instead, fees are deducted after a bill is generated for the project. A delay occurs between the time the bill is generated and the time you stop the project. For example, fees incurred by resource usage between 10:00 and 11:00 may be deducted and billed several hours later. Therefore, even if you have stopped the project at 11:00, you may still receive a bill for the project later. Although billing is delayed, only the fees incurred before you stop the project are deducted.