Work across more than one platform
Convert a scheduled data job to another platform without changing its required behavior
- When a scheduled job needs to run on a new platform without anyone renegotiating what it is supposed to do.
- When a cron-triggered load must become a native pipeline on the destination platform with the same cadence and retries.
Convert a scheduled data job from its current platform to another while preserving its cadence, retry policy, and dependency order. Covers the conversion, not redesigning the schedule or its failure handling.
Sample This Recipe has not been materialized in the Cookbook repository yet. Its trigger, description, prompt, agent guidance and acceptance conditions, and the explanation below, are prototype drafts. Its name, job, area and readiness come from the reconciled Cookbook seed snapshot. Readiness is a separate question from this one: it says whether the capability exists, not whether the writing has been reviewed.
Review planned Recipe
At least one capability or object type this Recipe needs is not supported yet.
Read the VibeData Recipe `cross-platform-scheduled-job` at https://getvibedata.ai/cookbook/cross-platform-scheduled-job At least one capability or object type this Recipe needs is not supported yet. Treat it as a reference, not as work to execute.
Recipe id cross-platform-scheduled-job · Not yet materialized in the Cookbook repository, so the pointer addresses this page.
Verified by
What has to be observably true before this Recipe is finished.
- the converted job runs on the same cadence as the original
- the retry policy behaves the same way on a forced failure
- the dependency order between steps is unchanged after conversion
- the original job is not disabled in the same change that introduces the new one
Recipe promptThe task specification the agent reads. Reference only — it is not what you copy.
Deliver: Convert a scheduled data job to another platform without changing its required behavior. Convert a scheduled data job from its current platform to another while preserving its cadence, retry policy, and dependency order. Covers the conversion, not redesigning the schedule or its failure handling. Execute inside the current Intent. Its Domain, repository, platform, environment and attached sources are the context for this work — read them rather than asking for them. The work is done when: - the converted job runs on the same cadence as the original - the retry policy behaves the same way on a forced failure - the dependency order between steps is unchanged after conversion - the original job is not disabled in the same change that introduces the new one Report the evidence for each condition above with the result. A condition you cannot meet is something to say, not something to work around.
Agent guidanceHow the agent approaches the work, and what it will not do.
Establish which platform is authoritative today and what in the project is platform-specific. Build against the target in an isolated copy and reconcile the two runs against each other before anything is cut over.
Composes
- job scheduling and run evidence
- Fabric Data Pipelines in the project
- dbt in the project
- isolated-copy execution and gate verification
Asks first
Semantic decisions the Intent cannot supply. Never context Studio already holds.
- which Fabric target this work lands on, when the Domain carries both a Lakehouse and a Warehouse
Guardrails
- Build in an isolated copy. Production is read, never written.
- At least one capability this Recipe needs is not supported yet. Say so and stop rather than substituting a different approach.
What you need
- Microsoft Fabric Lakehouse, Microsoft Fabric Warehouse, MotherDuck, or DuckDB.
- The jobs you want sequenced, and somewhere they are allowed to run.
- Fabric Data Pipelines and dbt in the project, or the intent to add it.
How it goes
- Name both platforms, and which one is authoritative today.
- Let it read what in the project is platform-specific and what is not.
- Review the plan before anything is rebuilt.
- Build and run against the target in an isolated copy.
- Reconcile the two runs against each other, at the grain the consumers read.
- Read the acceptance conditions before you cut over, not after.
What you end up with
The deliverable, in your own repository, as orchestration work a reviewer who knows the project reads as native to it. Alongside it, the evidence for every one of the acceptance conditions above — which is the part that is still there in three weeks when somebody asks.