Gemini Enterprise Agent Platform Notebooks
Choose from Colab Enterprise or Gemini Enterprise Agent Platform Workbench. Access every capability in Agent Platform to work across the entire data science workflow—from data exploration to prototype to production.
Natively analyze your data with a reduction in context switching between services
Data to training at scale. Build and train models 5x faster, compared to traditional notebooks
Scale up model development with simple connectivity to Agent Platform services
Benefits
Easy exploration and analysis
Easy exploration and analysis
Simplified access to data and in-notebook access to machine learning with BigQuery, Managed Service for Apache Spark, Spark, and Agent Platform integration.
Rapid prototyping and model development
Rapid prototyping and model development
Take advantage of the power of infinite compute with Agent Platform Training for experimentation and prototyping, to go from data to training at scale.
End-to-end notebook workflows
End-to-end notebook workflows
Using Colab Enterprise or Agent Platform Workbench you can implement your training and deployment workflows on Agent Platform from one place.
Key features
Key features
Colab Enterprise
Colab Enterprise combines the notebook developed by Google Research and used by over 7 million data scientists with Google Cloud enterprise level security and compliance. Get started quickly with a zero-config, serverless, and collaborative environment.
AI-powered code assistance features like code completion and code generation make it easier to build AI/ML models in Python, reducing the need to write repetitive code, so you can focus on your data and models.
Agent Platform Workbench
Agent Platform Workbench provides a JupyterLab experience and advanced customization capabilities.
Fully managed compute
Agent Platform Notebooks provide fully managed, scalable, enterprise-ready compute infrastructure with security controls and user management capabilities.
Interactive data and ML experience
Explore data and train ML models with easy connections to Google Cloud's big data solutions.
Portal to complete end-to-end ML training
Develop and deploy AI solutions on Agent Platform with minimal transition.
Documentation
Technical resources
All features
All features
| Simplified data access | Extensions will seamlessly connect to the entire data estate including BigQuery, Data Lake, Managed Service for Apache Spark, and Spark. Seamlessly scale up or scale out depending on your analytic and AI needs. |
| Explore data sources using a catalog | Write SQL, Spark queries from a syntax-aware, auto-complete enabled notebook cell. |
| Data visualization | Integrated, intelligent visualization tools will provide easy insights into data. |
| Hands-off, cost-effective infrastructure | All aspects of the compute are managed. Idle timeout and auto shutdown will optimize total cost of ownership. |
| Enterprise security, simplified | Out-of-the-box Google Cloud security controls. Single sign-on and simple authentication to other Google Cloud services. |
| Data Lake and Spark in one place | Whether you use TensorFlow, PyTorch, or Spark, you can run any engine from Agent Platform Workbench. |
| Deep Git, training, and MLOps integration | With few clicks, plug notebooks into established Ops workflows. Use notebooks for distributed training, hyper-parameter optimization, or scheduled or triggered continuous training. Deep integration with Agent Platform services brings MLOps into the notebook without the need to rewrite code or new workflows. |
| Seamless CI/CD | Kubeflow Pipelines integration to use Notebooks as an ideal, tested, and verified deployment target. |
| Notebook viewer | Share output of periodically updated notebook cells for reporting and bookkeeping purposes. |
Pricing
Pricing
Colab Enterprise pricing details.
Agent Platform Workbench pricing details.
Pricing models are based upon compute and services based on the infrastructure you use, as well as other services consumed from within Agent Platform Notebooks.
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