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POSIT WORKBENCH
Scaling R and Python,
made easy
Posit Workbench is the place for teams to collaboratively build open source data science projects at scale. It supports both R and Python, giving data scientists access to all the development environments they love, including RStudio, Jupyter and VS Code. Workbench provides enterprise-friendly features, such as centralized management, security, and commercial support.
Jump into your first line of code immediately. Posit Workbench supports both R and Python and gives data scientists access to all the development environments they love, including RStudio, Jupyter and VS Code.
You can switch between languages, or use different languages for different projects, without adding work for your IT team. Posit Workbench is built to keep data scientists doing what they love to do: creating insights.
The teams that get the most out of their investments in data science work from a centralized server. Their data scientists can focus on doing collaborative data science instead of on software installation and management.
Posit Workbench removes common collaboration and resource challenges, opening up development possibilities between data scientists on teams of all sizes in any industry, using any language.
With the ability to launch jobs remotely, data science teams can make use of IT-managed computing resources in Kubernetes or Slurm clusters, with load balancing and scalable cluster management.
Individual data scientists can launch RStudio, Jupyter, or VS Code sessions directly through Posit Workbench while leveraging the hardware that is available to their organization’s computing cluster.
Posit Workbench has incredible security features, and we built them with IT in mind from the start. Integrate with Active Directory, LDAP, and more. Kerberos, PAM, and proxied authentication are supported. Encrypt traffic using TLS/SSL and restrict IP addresses.
Posit Workbench is now available on Amazon SageMaker! Learn more on how you can utilize this for deep learning capabilities, scaling compute and RAM resources.