Describe the issue
A bundle deploy that makes no actual configuration change to a continuous
pipeline still causes the Pipelines service to cancel the pipeline's active
update and start a new one, with reason SETTINGS_CHANGE. This happens on
effectively every deploy of a bundle containing a continuous pipeline, even
when that specific pipeline's resource definition is byte-for-byte unchanged
between deploys.
This looks like the same class of bug as #6076, #6060 and #6315 — an
input-only or computed field on the pipeline resource that isn't registered
as such, so the direct engine perpetually diffs bundle state against a
remote value that structurally can never match, and replays an update every
run. Unlike those, the field responsible hasn't been identified yet; filing
this to track it and get guidance on capturing the right evidence.
Configuration
Minimal repro shape (the exact field causing the perpetual diff is not yet
isolated — happens on any continuous pipeline with a libraries.notebook
based DLT pipeline, no gateway/ingestion-specific config required):
resources:
pipelines:
example_stream:
name: example_stream
catalog: my_catalog
target: my_schema
continuous: true
development: false
channel: CURRENT
edition: PRO
libraries:
- notebook:
path: ../src/pipelines/example/pipeline
Steps to reproduce the behavior
databricks bundle deploy -t <target> with a continuous pipeline in the bundle, no source changes since the last deploy.
- Observe the pipeline's event log / update history immediately after deploy.
- See a new update start with
cause: SETTINGS_CHANGE, cancelling whatever update was previously running.
Expected Behavior
No update call (and therefore no cancel/restart) should occur against a
continuous pipeline when nothing about its resolved configuration actually
changed.
Actual Behavior
The pipeline is cancelled and a new update starts on every deploy.
OS and CLI version
CLI v1.17.0, Linux.
Is this a regression?
Yes, in scope: one continuous ingestion pipeline (Lakeflow CDC gateway) already
showed this behavior under the Terraform-based engine. After migrating this
bundle to the direct deployment engine, every continuous pipeline in the
bundle now exhibits the same behavior — not just that one.
Detailed plan
Can provide a redacted bundle plan -o json -t <target> on request — happy
to capture it if a maintainer confirms this is the most useful next
diagnostic, and to redact accordingly.
Debug Logs
Can provide on request, redacted.
Describe the issue
A
bundle deploythat makes no actual configuration change to a continuouspipeline still causes the Pipelines service to cancel the pipeline's active
update and start a new one, with reason
SETTINGS_CHANGE. This happens oneffectively every deploy of a bundle containing a continuous pipeline, even
when that specific pipeline's resource definition is byte-for-byte unchanged
between deploys.
This looks like the same class of bug as #6076, #6060 and #6315 — an
input-only or computed field on the pipeline resource that isn't registered
as such, so the direct engine perpetually diffs bundle state against a
remote value that structurally can never match, and replays an update every
run. Unlike those, the field responsible hasn't been identified yet; filing
this to track it and get guidance on capturing the right evidence.
Configuration
Minimal repro shape (the exact field causing the perpetual diff is not yet
isolated — happens on any continuous pipeline with a
libraries.notebookbased DLT pipeline, no gateway/ingestion-specific config required):
Steps to reproduce the behavior
databricks bundle deploy -t <target>with a continuous pipeline in the bundle, no source changes since the last deploy.cause: SETTINGS_CHANGE, cancelling whatever update was previously running.Expected Behavior
No update call (and therefore no cancel/restart) should occur against a
continuous pipeline when nothing about its resolved configuration actually
changed.
Actual Behavior
The pipeline is cancelled and a new update starts on every deploy.
OS and CLI version
CLI v1.17.0, Linux.
Is this a regression?
Yes, in scope: one continuous ingestion pipeline (Lakeflow CDC gateway) already
showed this behavior under the Terraform-based engine. After migrating this
bundle to the direct deployment engine, every continuous pipeline in the
bundle now exhibits the same behavior — not just that one.
Detailed plan
Can provide a redacted
bundle plan -o json -t <target>on request — happyto capture it if a maintainer confirms this is the most useful next
diagnostic, and to redact accordingly.
Debug Logs
Can provide on request, redacted.