In Kubernetes, a pod is a process that is running on your Kubernetes cluster. A pod is a runnable unit of work, which can be a either a stand-alone application or a microservice.
In Watson Studio Local, if a process needs to run on multiple nodes, more pods are created and deployed for extra users or extra notebook servers and IDEs. Spark is deployed as a cluster with at least one pod in each compute node. Spark jobs are distributed as singleton containers, and are capped when they reach the limits of the VM.
You can view the list of pods that are used in your Watson Studio Local deployment from the Pods page. You can access the Pods page from the Menu icon: ( ).
From the Pods page, you can see:
- The names of the pods
- The status of the pods
- The node where each pod is deployed
- The CPU, memory, and disk usage for each pod
Additionally, you can click on the name of each pod to see the following information:
The IP address of the host where the pod is deployed
The name of the service that is running on the pod
The amount of CPU the pod is using and a graph of the CPU usage over the last 15 minutes.
The amount of memory that the pod is using and a graph of the memory usage over the last 15 minutes.
The amount of disk space that the pod is using and a graph of the disk space usage over the last 15 minutes.
Typically, all of the pods in your environment are running ( ). However, you might notice that the pods in your environment are in one of the following states:
Pending ( ) - The Kubernetes cluster is creating the Container images that are included in the pod.
Running ( ) - The pod is deployed on a node. At least one Container is running or is in the process of starting or restarting.
Succeeded ( ) - All of the Containers in the pod stopped successfully. The Containers are not restarted.
Failed ( ) - All of the Containers in the pod stopped successfully, but at least one Container stopped with an error or was stopped by Kubernetes.
Unknown ( ) - The state of the pod cannot be determined, which typically occurs when there is a communication issue with the node where the pod is deployed.
If you encounter an issue with a service, you might need to redeploy the pod.
If you cannot successfully redeploy a pod from the Pods page, contact IBM Software Support for assistance with resolving the issue.