Data and AI Operations

Data Science & AI Operations Development Environments

DataOps and AIOps strive to make data engineers and scientists more productive. Coder removes the hassle of setting up a development environment while giving developers access to their favorite IDEs and server compute that exceeds any laptop.

The ubiquity of VS Code with the web access of Jupyter

Jupyter is limited to Python use cases and is difficult to configure, causing delays in model development. With Coder you can use the world's most popular IDE, VS Code, to access your Jupyter Notebooks with the ease and convenience of a browser. Developer infrastructure and DevOps teams can support one IDE that powers both Jupyter and full-stack development use cases.
Jupyter VS Code

Your own dedicated Python kernel

Data science projects have grown in effort and number of developers, increasing the importance of source code version control and workload isolation. Each Coder workspace is isolated to a single user, with more compute possible than a local machine. We provide a local development experience with server-tiered CPUs, GPUs, and RAM. Coder gives you the freedom to use your favorite IDE, whether that's Jupyter, RStudio, MATLAB, Apache Airflow, etc.
Jupyter VS Code

Governance and control

Coder moves development activity from decentralized laptops and desktops into your secured cloud. Monitor workspace activity, automatically shutdown unused environments, roll out security updates, and integrate with VPNs—all without disrupting users. Rest easy knowing that laptops left behind in Ubers contain no source code or training data.

Cost-effective Compute Power

Enterprise data projects quickly outgrow the capabilities of local workstations. Coder's provisioning layer supports all cloud machine types, including cutting-edge GPU offerings.

Remove financial barriers to cloud adoption with workspace cost controls. Coder automatically stops machines when they're no longer in use, starts them back up on user-defined schedules, and limits total resource consumption per developer.
Jupyter Lab

Next Steps

Say goodbye to hardware limitations and hello to accelerated code execution and increased productivity. Empower your organization to innovate at lightning speed and stay ahead of the competition.