Monitoring sessions and deployments

Anaconda Enterprise enables you to see which sessions and deployments are running on specific nodes or by specific users, so you can monitor cluster resource usage. You can also view session details for a specific user in the Authorization Center. See Managing users for more information.

  1. Log in to Anaconda Enterprise, select the Menu icon icon in the top right corner and click the Administrative Console link displayed at the bottom of the slide out window.

  1. Click Manage Resources.

  2. Log in to the Operations Center using the Administrator credentials configured after installation.

  3. Select Monitoring from the menu on the left to display the monitoring dashboards.

../../_images/monitor-cluster-usage.png

Individual pod

To display the monitoring graph for a user session or deployment you’ll need to identify the appropriate Kubernetes pod name.

For an editor session the Kubernetes pod name corresponds to the hostname of the session container. Run hostname in a terminal window. For deployments the pod name is available from the logs tab of the deployment under the heading name.

  1. Click the Monitoring tab from the menu on the left

  2. Click Cluster at the top left of the dashboard

  3. Select Compute Resource / Workload

../../_images/workload-monitoring.png

To display the monitoring graph for an individual pod

  1. Select default from the namespace menu

  2. Select the desired pod from the the workload menu

../../_images/pod-monitor.png

Scroll down further to display the memory usage.

../../_images/pod-monitor-memory.png

Using the CLI:

  1. Open an SSH session on the master node in a terminal by logging into the Operations Center and selecting Servers from the menu on the left.

  2. Click on the IP address for the Anaconda Enterprise master node and select SSH login as root.

  3. In the terminal window, run sudo gravity enter.

To view total node CPU and memory utilization run

kubectl top nodes --heapster-namespace=monitoring

To view CPU and memory utilization per pod run

kubectl top pods --heapster-namespace=monitoring