Merge pull request #129 from DimmestP/example-workflow

EIDFGPU Service example k8s workflow

docs/services/gpuservice/index.md

@@ -33,6 +33,11 @@ The current full specification of the EIDF GPU Service as of 14 February 2024:
 
     Changes to the default quota must be discussed and agreed with the EIDF Services team.
 
+> **NOTE**
+>
+> If you request a GPU on the EIDF GPU Service you will be assigned one at random unless you specify a GPU type.
+> Please see [Getting started with Kubernetes](training/L1_getting_started.md) to learn about specifying GPU resources.
+
 ## Service Access
 
 Users should have an [EIDF Account](../../access/project.md).
@@ -82,6 +87,7 @@ This tutorial teaches users how to submit tasks to the EIDF GPU Service, but it
 | [Getting started with Kubernetes](training/L1_getting_started.md)                             | a. What is Kubernetes?<br>b. How to send a task to a GPU node.<br>c. How to define the GPU resources needed.  |
 | [Requesting persistent volumes with Kubernetes](training/L2_requesting_persistent_volumes.md) | a. What is a persistent volume? <br>b. How to request a PV resource.                                          |
 | [Running a PyTorch task](training/L3_running_a_pytorch_task.md)                               | a. Accessing a Pytorch container.<br>b. Submitting a PyTorch task to the cluster.<br>c. Inspecting the results. |
+| [Template workflow](training/L4_template_workflow.md)                               | a. Loading large data sets asynchronously.<br>b. Manually or automatically building Docker images.<br>c. Iteratively changing and testing code in a job. |
 
 ## Further Reading and Help