Create a branch based of the main branch, the branch name you choose will be shown in the training environment URL (e.g. https://branch-ood-webnode.data.nesi.org.nz), choose something simple and related to the training you are running, avoid special characters, etc. (e.g. ml101, introtor, etc). Edit, commit and push the following files to your branch.
In vars/ondemand-config.yml.example:
- adjust
num_users_create
andnum_trainers_create
- adjust
ood_apps
- check
version
andk8s_container
- enable required apps (usually just leave them all enabled, except for containers)
- set which images to pre-pull (just choose the one you will be using, we have limited space currently on the worker nodes and pre-pulling will fail if you exhaust it)
- check
- set
enable_pod_prepull
to "true" (sometimes we have experienced really slow image pulls, this helps with that) - set
control_plane_flavor
, usually tobalanced1.4cpu8ram
for production - set
cluster_worker_count
andworker_flavor
to have enough capacity for the number of users
In terraform/terraform.tfvars:
- adjust
services_flavor_id
(usually use the id for 8cpu16ram for production) - adjust
services_volume_size
, must be big enough for all the user home directories - adjust
webnode_flavor_id
(the id for 8cpu16ram works well for up to 30-40 users, not tested past that) - adjust
webnode_volume_size
, usually leave at 30 GB