AltimateAI / AltimateAI/altimate-code

Add Databricks API support for notebooks, jobs, and clusters

Open
#1,243 0 comments 1 reaction 0 assignees View on GitHub
enhancement from-cli user-feedback
Dominant language
TypeScript
Stars
811
Forks
134
Avg merge
3d 2h
Merged PRs (30d)
50

Description

No Databricks APIs are currently available for managing notebooks, jobs, or clusters. Specifically requested capabilities:
- Create/manage Databricks Notebooks (Workspace REST API)
- Create/manage Databricks Jobs/Workflows (Jobs API) for scheduling and orchestration
- Create/manage Delta Live Tables (DLT) pipelines
- Manage clusters/compute (Cluster API)

Currently, altimate-code can only interact with Databricks via SQL warehouse connections (sql_execute, schema_inspect, dbt models, cost/finops analysis, lineage). There's no way to programmatically create or manage notebooks, jobs, or clusters directly — users must generate the content as text and manually apply it via the Databricks UI or CLI. Native API integration for these would let altimate-code build and orchestrate full Databricks pipelines, not just SQL-layer transformations.

---

### Metadata

| Field | Value |
|-------|-------|
| CLI Version | 0.9.7 |
| Platform | darwin |
| Architecture | arm64 |
| OS Release | 25.5.0 |
| Category | feature |

Contributor guide

Open the contributing guide

Research direction

Start by surveying the existing sql_execute, schema_inspect, dbt models, cost/finops, and lineage integrations to find the CLI's current Databricks connection points. Define the API entry points and tests for notebooks, jobs, DLT pipelines, and clusters; done means these resources can be managed programmatically rather than only generated for manual UI or CLI application.

Written by the indexing model from the issue text.

Assessment

Tech stack
typescript
Domain
backend-api-design, cli, data-engineering
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Active
Clarity
Needs clarification
Newbie friendliness
30/100

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