Provision Databricks Lakebase Resources Seamlessly
Provisioning Lakebase environments by hand is laborious, and it leaves room for configuration drift between environments. Connecting Python applications to Lakebase securely adds a second problem, because the Databricks OAuth token lifecycle has to be managed, and that logic is complex to build from scratch. The v4c LakeForge Accelerator addresses both with a GitHub Actions workflow that generates and deploys the full Declarative Automation Bundle definition dynamically, and a Python connection pool that handles OAuth credential injection at connection time. Both components can be used independently or together.
Why Choose the Lakeforge Accelerator?
v4c’s LakeForge Accelerator is a Declarative Automation Bundle accelerator with two distinct capabilities. The first is a GitHub Actions CI/ CD pipeline that automates the full lifecycle of Lakebase infrastructure: creating projects, branches, and read-only endpoints from parameterised inputs, and tearing them down cleanly when no longer needed. The second is a Python SDK that provides synchronous and asynchronous psycopg connection pools with automatic Databricks OAuth credential injection, so applications can connect to Lakebase without managing static credentials or writing custom authentication logic.
We built LakeForge to reduce the manual effort involved in setting up and connecting to Lakebase environments, and to give teams a consistent, repeatable foundation they can build on.
We built LakeForge to reduce the manual effort involved in setting up and connecting to Lakebase environments, and to give teams a consistent, repeatable foundation they can build on.
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Built For Data Engineering and Platform Teams
LakeForge ships two components that can be used independently or together.
Infrastructure Automation via CI/CD
We provide a turnkey GitHub Actions pipeline that dynamically provisions multi-branch Lakebase environments - dev, staging, preprod, and production- from a single, parameterised workflow run. Platform teams no longer manually create projects, branches, or endpoints; LakeForge generates the full Databricks Asset Bundle definition at runtime and deploys or destroys it cleanly with no manual intervention required.
Python OAuth Solutions
LakeForge also includes a Python SDK with ready-to-use synchronous and asynchronous psycopg connection pools. The pools automatically inject Databricks-generated OAuth credentials at connection time, so there is no need to manage static passwords or write custom token refresh logic. This component is independent of the CI/CD pipeline and can be used in any Python application that connects to Lakebase.
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Key Benefits of the LakeForge Accelerator
Automated Environment Provisioning
Create Lakebase projects, branches, and read-only endpoints from a single GitHub Actions workflow run, replacing a sequence of manual steps with a repeatable, parameterised process.
OAuth-Based Connectivity
Connect to Lakebase with Databricks-issued OAuth credentials rather than static passwords. The connection pool injects and refreshes those credentials automatically.
Consistent Teardown
The destroy process recreates the resource definition that was used when the deployment took place and carries out a clean shutdown, making sure that no resources are left behind as orphans.
Repeatable Environment Structure
On each run, the environment configuration is generated using the same template, which ensures that the dev, staging, and production branches have a consistent structure without the need for manual coordination.
Configurable Autoscaling
Read-only endpoint compute units are set through bundle variables, so the resources allocated to each environment can be adjusted without editing the main configuration.
Sync and Async Support
The Python SDK provides both synchronous and asynchronous connection pool interfaces so that it can be used with standard scripts and async application frameworks without the need for any additional configuration.
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