Managing compute resources
Managing compute resources If you have the Admin role or Editor in a project, you can perform management tasks for environments. * [Create an environment template](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/create-customize-env-definition.html) * [Customize an environment template](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/customize-envs.html) * [Stop active runtimes](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/manage-envs-new.html?context=cdpaas&locale=enstop-active-runtimes) * [Promote an environment template to a space](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/promote-envs.html) * [Track capacity unit consumption of runtimes](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/track-runtime-usage.html) Stop active runtimes You should stop all active runtimes when you no longer need them to prevent consuming extra capacity unit hours (CUHs). Jupyter notebook runtimes are started per user and not per notebook. Stopping a notebook kernel doesn't stop the environment runtime in which the kernel is started because you could have started other notebooks in the same environment. You should only stop a notebook runtime if you are sure that no other notebook kernels are active. Only runtimes that are started for jobs are automatically shut down after the scheduled job has completed. For example, if you schedule to run a notebook once a day for 2 months, the runtime instance will be activated every day for the duration of the scheduled job and deactivated again after the job has finished. Project users with Admin role can stop all runtimes in the project. Users added to the project with Editor role can stop the runtimes they started, but can't stop other project users' runtimes. Users added to the project with the viewer role can't see the runtimes in the project. You can stop runtimes from: * The Environment Runtimes page, which lists all active runtimes across all projects for your account, by clicking Administration > Environment runtimes from the Watson Studio navigation menu. * Under Tool runtimes on the Environments page on the Manage tab of your project, which lists the active runtimes for a specific project. * The Environments page when you click the Notebook Info icon (![Notebook Info icon](https://dataplatform.cloud.ibm.com/docs/content/wsj/console/images/get-information_32.png)) from the notebook toolbar in the notebook editor. You can stop the runtime under Runtime status. Idle timeouts for: * [Jupyter notebook runtimes](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/manage-envs-new.html?context=cdpaas&locale=encpu) * [Spark runtimes for notebooks and Data Refinery](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/manage-envs-new.html?context=cdpaas&locale=enspark) * [Notebook with GPU runtimes](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/manage-envs-new.html?context=cdpaas&locale=engpu) * [RStudio runtimes](https://dataplatform.cloud.ibm.com/docs/content/wsj/analyze-data/manage-envs-new.html?context=cdpaas&locale=enrstudio) Jupyter notebook idle timeout Runtime idle times differ for the Jupyter notebook runtimes depending on your Watson Studio plan. Idle timeout for default CPU runtimes Plan Idle timeout Lite - Idle stop time: 1 hour <br>- CUH limit: 10 CUHs Professional - Idle stop time: 1 hour <br>- CUH limit: no limit Standard (Legacy) - Idle stop time: 1 hour <br>- CUH limit: no limit Enterprise (Legacy) - Idle stop time: 3 hours <br>- CUH limit: no limit All plans <br>Free runtime - Idle stop time: 1 hour <br>- Maximum lifetime: 12 hours Important: A runtime is started per user and not per notebook. Stopping a notebook kernel doesn't stop the environment runtime in which the kernel is started because you could have started other notebooks in the same environment. Only stop a runtime if you are sure that no kernels are active. Spark idle timeout All Spark runtimes, for example for notebook and Data Refinery, are stopped after 3 hours of inactivity. The Default Data Refinery XS runtime that is used when you refine data in Data Refinery is stopped after an idle time of 1 hour. Spark runtimes that are started when a job is started, for example to run a Data Refinery flow or a notebook, are stopped when the job finishes. GPU idle timeout All GPU runtimes are automatically stopped after 3 hours of inactivity for Enterprise plan users and after 1 hour of inactivity for other paid plan users. RStudio idle timeout An RStudio is stopped for you after an idle time of 2 hour. During this idle time, you will continue to consume CUHs for which you are billed. Long compute-intensive jobs are hard stopped after 24 hours. Parent topic:[Projects](https://dataplatform.cloud.ibm.com/docs/content/wsj/manage-data/manage-projects.html)