This section includes a list of known issues with troubleshooting and recovery steps for Learning Center.
The training portal stays in a "pending" state.
Explanation
The TLS secret tls
is not available.
Solution
-
Access the operator logs by running:
kubectl logs deployment/learningcenter-operator -n learningcenter
-
Observe that the TLS secret
tls
is not available. The TLS secret should be on the Learning Center operator namespace. If the TLS secret is not on the Learning Center operator namespace, the operator logs contain the following error:ERROR:kopf.objects:Handler 'learningcenter' failed temporarily: TLS secret tls is not available
-
Follow the steps in Enforcing Secure Connections in Learning Center Operator to create the TLS secret.
-
Redeploy the
trainingPortal
resource.
You are installing a TAP profile and you get this error:
Internal error occurred: failed calling webhook "image-policy-webhook.signing.run.tanzu.vmware.com": failed to call webhook: Post "https://image-policy-webhook-service.image-policy-system.svc:443/signing-policy-check?timeout=10s": service "image-policy-webhook-service" not found
Explanation
This is a race condition error among some packages.
Solution
To recover from this error you only need to redeploy the trainingPortal resource.
The training portals do not work or do not show updated parameters.
Run one of the following commands to validate changes made to parameters provided to the Learning Center Operator. These parameters include ingressDomain, TLS secret, ingressClass, and others.
Command:
kubectl describe systemprofile
Command:
kubectl describe pod -n learningcenter
Explanation
By design, the training portal resources do not react to any changes on the parameters provided
when the training portals were created. This prevents any change on the trainingportal
resource
from affecting any online user running a workshop.
Solution
Redeploy trainingportal
in a maintenance window where Learning Center is unavailable while the
systemprofile
is updated.
If you don't have enough nodes or enough resources on nodes for deploying the workloads, node pressure might occur. In this case, follow your cloud provider's instructions on how to scale out or scale up your cluster.