Designer is a visual modeling tool in Platform for AI (PAI). You can use it to build a Workflow by dragging and dropping Algorithm Components, enabling a low-code, visual approach to model development. Designer also supports online deployment and offline timed scheduling.
Service architecture
Features
Create and manage workflows: You can create a workflow from a template or build one from scratch. After a completed run, you can deploy the model. For more information, see Create a workflow.
Rich library of components and data sources: Designer provides hundreds of AI development components and supports data sources, such as MaxCompute and Object Storage Service (OSS), letting you build models with algorithms that incorporate Alibaba's best practices.
Visualize and analyze the training process: During model training, use the visualization dashboard to analyze data, models, and evaluation metrics to help you find the optimal model.
Deploy and manage models: You can register models developed in a Designer workflow to the model management service, and deploy them with one click as an online service or package them as a composite model. For more information, see Model prediction and deployment.
Collaborate and share: Designer supports workflow collaboration and sharing within a workspace. You can also deploy a workflow that has run successfully to DataWorks for periodic scheduling or publish it as a custom template.
Accounts and permissions: Log in to Designer with an Alibaba Cloud Account or a RAM user. A RAM User requires the necessary permissions from its parent Alibaba Cloud Account. For more information, see Cloud product dependencies and permissions: Designer.
Workflow components
Designer provides hundreds of components for various use cases. For more information about the components, see Overview of Designer components.
Components are categorized into three types by use case:
Traditional machine learning components: Algorithm Components for data pre-processing, feature engineering, statistical analysis, anomaly detection, recommendation algorithms, time series, and network analysis.
Deep learning framework components: Vision algorithms and Natural Language Processing algorithms based on the PAI-Easy series, as well as Deep Learning frameworks like TensorFlow and PyTorch.
Custom algorithm components: Custom Algorithm Components such as SQL Script, Python Script, Notebook Script, and PyAlink Script for your custom requirements.
Usage flow
A workflow is a visual canvas that contains all component nodes and data flows. It is the starting point for model development.
Use pre-built algorithm components to build a model in a drag-and-drop interface. Select computing resources, such as MaxCompute, PAI-DLC, or Flink, to run the Workflow and complete model debugging and training.
After you train the model, use the visualization dashboard to view analysis reports and evaluate if the model meets expectations.
Deploy and predict models
Online prediction: After you train the model, you can deploy it as an online service with PAI-EAS to make predictions on new data.
Implement batch prediction: To perform scheduled, offline batch predictions, you can submit a Designer Workflow to DataWorks for periodic scheduling.
Billing
Designer billing is based on the resources that components consume at runtime. The details are as follows:
Billable item | Billing entity | Billing method | Stop billing | Billing rules |
Compute Unit-hour (CU-hour) usage | Component runtime | Pay-as-you-go | Stop the component | Resources consumed by a component are converted into Compute Unit (CU) hours. Billing formula: Where, |
For the unit prices of different Components and more billing details, see Billing for Designer.
Quick start
To get started, see the Quick start for Designer.
Scenarios
Artificial Intelligence Recommendation: Implement recommendation recall with FM-Embedding | FM recommendation based on the Alink framework.
Intelligent risk control: Financial risk control using graph algorithms | User churn risk warning.
General use cases: News Classification with Text Analysis | Smog Prediction | Power Plant Output Prediction.
Get help
If you encounter issues, such as workflow errors, problems with algorithm components, or data read failures, see the Designer FAQ.
Appendix: PAIFlow
PAIFlow is the workflow scheduling engine for Designer. You can submit workflow tasks from Designer to PAIFlow for execution.
The PAIFlow task management page contains all Pipeline tasks submitted through manual execution via Designer and periodic scheduling of Designer workflows in DataWorks. For more information, see Manage workflow tasks.