2 weeks ago
Hello!
I am deploying a databricks workflow using bundles and want to attach the prefix "prod_" to the name of my job.
My target uses the `mode: production` and I follow the instructions in https://learn.microsoft.com/en-us/azure/databricks/dev-tools/bundles/settings#mode-and-presets to set the name_prefix.
Unfortunatelly, nothing is happening ๐
To replicate:
- run `databricks bundle init` to create a new bundle repository
- adjust the prod target in the `databricks.yml` according to the above documentation
- run `databricks bundle deploy -t prod`
Thanks!
2 weeks ago
second update: the issue wasn't additional privileges but an outdated cli version used to deploy the job, updating the databricks cli resolved everything
2 weeks ago
@evangelos If you followed this doc, https://docs.databricks.com/en/dev-tools/bundles/settings.html it should work.
Can you send your `databricks.yml` file by removing all the values for the variables to check further.
2 weeks ago
@Satyadeepak here's the databricks.yml taken from `databricks bundle init` and adjusted to this issue
bundle:
name: my_project
include:
- resources/*.yml
targets:
dev:
mode: development
default: true
run_as:
user_name: ${workspace.current_user.userName}
prod:
mode: production
presets:
name_prefix: "prod_"
tags:
prod: "true"
run_as:
user_name: ${workspace.current_user.userName}
when deploying the above bundle to dev and prod this is the jobs that get created
2 weeks ago
You need to attach the prefix "prod_" to the name of your job in a Databricks workflow using bundles, you need to ensure that the name_prefix
preset is correctly configured in your databricks.yml
file.
targets:
prod:
mode: production
presets:
name_prefix: "prod_" # prefix all resource names with prod_
tags:
prod: true
Does it work for you when you are in dev mode?
2 weeks ago
@NandiniN @Satyadeepak update: my colleague with more privileges deployed the job and the prefix appeared, we are trying to figure out what type of privileges are needed. thanks for the help ๐
2 weeks ago
second update: the issue wasn't additional privileges but an outdated cli version used to deploy the job, updating the databricks cli resolved everything
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