Closed mokane-db closed 3 weeks ago
Capturing some further debugging context: This appears to be down to improper handling of the suffix-matching approach for determining which environment the client is connecting through within the SDK, rather than UCX itself. When no match is found the SDK defaults to AWS. In the two scenarios I ran into:
DATABRICKS_HOST
environment variable being suffixed with :443
causing a failurehost
cli config appeared to cause a similar failure.In both cases the issue may be worked around by correcting the value of the host
config or removing the erroneous aws_attributes.availability
property from the generated UCX cluster policy.
SDK version 0.30 fixes the bug described in this issue. Closing
Is there an existing issue for this?
Current Behavior
Attempting to run
install ucx
on an Azure environment with defaults results in a failure after theCreating dashboards...
step, indicating an input validation error on a Cluster. This validation error indicates theaws_attributes.availability
attribute is required, which seems erroneous given this is Azure.Expected Behavior
Expectation is for
ucx install
to complete successfullySteps To Reproduce
❯ databricks --version Databricks CLI v0.220.0 ❯ databricks labs installed Name Description Version ucx Unity Catalog Migration Toolkit (UCX) v0.23.1
❯ databricks labs install ucx Using workspace profile:
17:09:51 INFO [d.l.ucx.install] Installing UCX v0.23.1
17:09:53 INFO [d.l.ucx.install] UCX v0.23.1 is already installed on this workspace
Do you want to update the existing installation? (default: no): yes
17:09:58 INFO [d.l.ucx.install] Installing UCX v0.23.1
17:09:58 INFO [d.l.ucx.install][installing_components_0] Creating ucx schemas...
17:09:58 INFO [d.l.ucx.install][installing_components_1] Creating dashboards...
Traceback (most recent call last):
...
databricks.sdk.errors.platform.InvalidParameterValue: Cluster validation error: Validation failed for aws_attributes.availability, the value must be present
Cloud
Azure
Operating System
macOS
Version
latest via Databricks CLI
Relevant log output