How to deploy multiple pods with same a helm chart?

Question

I want to deploy multiple ML models in different pods within the same namespace. But whenever I pull a new image from aws ECR and deploy it using helm it terminates the current running pod and makes a new one. So I am unable to deploy multiple models. Every time it kills the previous one and makes a new pod.

helm upgrade --install tf-serving ./charts/tf-serving/ --namespace mlhub

OR

helm upgrade --recreate-pods --install tf-serving ./charts/tf-serving/ --namespace mlhub

tf-serving-8559fb87d-2twwl        1/1     Running       0          37s  
tf-serving-8559fb87d-m6hgs        0/1     Terminating   0          45s

It kills the previous one and makes a new, but the images of both models are different with different tags also.

Answer 1

You can use one Helm chart to create multiple Releases. For example to deploy first model:

helm install ./charts/tf-serving/ --name tf-serving --namespace mlhub

And if you later want to add another one:

helm install ./charts/tf-serving/ --name tf-serving2 --namespace mlhub

Now when you run helm list you will be able to see both tf-serving and tf-serving2.

Be aware that you can not have multiple Kubernetes resources of the same Kind with the same name, so I would recommend using {{ .Release.Name }} value in your chart, as a prefix for all deployed resources.