Managed Server Solutions

cynkra Managed RStudio Workbench

A Managed Workbench solution provides an ideal environment for data analysis and data science in smaller and larger teams. Instead of installing RStudio professional products yourself, we can use our extensive experience to greatly facilitate the setup and maintenance process and maximize the user experience.

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Situation Analysis IT

A Managed RStudio Workbench solution is typically installed on a server machine provided by the customer or in a container platform (OpenShift, Kubernetes). The Managed Workbench runs in a container, which is agnostic to the host operating system. cynkra analyzes the installation setup with the IT team of the client and provides customized configurations.

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Included Software

The RStudio Workbench allows you to use different R versions efficiently, balance the server resources, and connect to identity providers (e.g. Active Directory, OpenID, SAML). It also has tools for user-defined control of database connections. The Managed Workbench also provides software often used in conjunction with R, such as Git, LaTeX, and Pandoc.

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Training and Support

cynkra supports you with training and support. We introduce all team members to the new product and provide support to them in their daily work. We maintain and regularly update both the RStudio products and the additional software. We guarantee the functionality of the Workbench and quickly react to problems within tailored response times.

Advantages of a Managed RStudio Workbench

An ideal environment for data analysis

A Managed RStudio Workbench solution provides an ideal environment for data analysis and data science in smaller and larger teams. It simplifies the use of R, makes production processes more reliable, and is more flexible than a local solution. A cynkra Managed Solution eases the strain on IT resources and ensures professional installation and maintenance.

Simple

  • No local installation required, accessed via browser
  • Benefit from our experience with RStudio products
  • Setup analysis with IT by cynkra
  • No restriction through IT policy

Reliable

  • Installation, operation and support by cynkra
  • Uniform R versions and packages
  • Central administration of the installation
  • Centralized storage minimizes the risk of data loss

Flexible

  • Free choice of packages
  • Additional software (LaTeX, Git)
  • Python support
  • Continue to use existing scripts
Smart configurations, dockerized environment

Under the hood

Besides finding the optimal combination of different software provided by RStudio, our Managed RStudio solutions come with smart defaults and individualized configurations – such as local package repositories or preconfigured database setups. They are built in dockerized environments and allow for substantial speed gains compared to a local installation.

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Smart configurations

We set appropriate configuration settings so users can use the full power of the RStudio product suite. Our product saves the IT team from going through the complete admin guide with the potential of missing something important. We have experience configuring RStudio products in almost all possible configuration scenarios including in highly secured enterprise environments and most user authentication systems.

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Dockerized environment

Our products come in a containerized environment, making them agnostic to any underlying operating system. Using a containerized environment also simplifies update tasks (for the client and us) due to the independence of the underlying operating system. By relying on the stable Ubuntu LTS environment as the base layer, we can provide a stable LaTeX / Pandoc environment that eliminates almost all problems for users in this area.

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Performance

Centralized, server-based installations can be very efficient both in speed and battery consumption. This applies to all RStudio products but in particular to RStudio Workbench and RStudio Package Manager. This blog post details some of the substantial speed gains that users experience compared to a local installation. In addition to startup, calculation speed and the time for package installation are also vastly improved.