Cube Core

Euno's Cube Core integration ingests a zip of Cube schema YAML from self-hosted Cube Core deployments. Euno discovers cubes, views, measures, and dimensions, and enriches them with lineage to warehouse tables and columns.

This integration is push-only: upload your Cube model/ tree as a zip file. Euno does not call Cube APIs.

Limitations

Euno currently supports Cube Core deployments connected to Snowflake only. Other warehouses, Cube Cloud, and JavaScript schema files are not supported.

What Euno discovers

• Cube deployment — optional container when Instance slug is set

• Cubes — semantic models over warehouse tables

• Views — consumer-facing projections over cubes

• Dimensions and measures — under cubes or views

• Lineage — warehouse table and column dependencies, cube-to-cube joins, and view member aliases

For property and relationship details, see Cube Core Integration Discovered Resources.

Prerequisites

Before setting up a Cube Core source in Euno:

1. Cube schema YAML — Export or package your Cube model/ directory as a .zip file. Files must be under model/**/*.yml or model/**/*.yaml and contain cubes: and/or views: at the root of each document.

2. Jinja stubs (if needed) — If your sql_table values use COMPILE_CONTEXT Jinja, configure Security context and Custom context in the source so Euno can render table names offline.

Upload the complete model/ tree when your deployment has joins or views that reference cubes defined in other YAML files. Partial uploads produce incomplete graphs.

Setting up a Cube Core source in Euno

Step 1: Access the Sources page

1. Navigate to the Sources page in Euno.

2. Click Add New Source and select Cube Core.

Step 2: General configuration

Asterisk (*) means a mandatory field.

Configuration	Description
Name*	Display name for this source (for example, Cube Core - Production).
Warehouse technology*	Warehouse type for the default Cube data source.
Snowflake host*	Warehouse host or account locator for the default data source (for example, JGB69604.us-west-2.aws or account.region.snowflakecomputing.com).
Default database	Default database for unqualified sql_table names on the default Cube data source.
Default schema	Default schema for unqualified table names on the default Cube data source.
Instance slug	URI namespace for cube resources. When set, Euno also creates a cube_deployment container for this instance.
Instance display name	Optional label for the deployment container. Defaults to the instance slug.

Step 3: Resource cleanup

To keep your data relevant and free of outdated resources, Euno provides automatic resource cleanup options. These settings determine when a resource should be removed if it is no longer detected by a source integration. For a detailed explanation, see Resource Sponsorship in Euno.

• Time-Based Cleanup (default): Remove resources that were last detected a number of days before the most recent successful source integration run (default is 7 days).

• Immediate Cleanup: Remove resources not detected in the most recent successful source integration run.

• No Cleanup: Keep all resources indefinitely, even if they are no longer detected.

Step 4: Advanced settings (optional)

Click Advanced to configure additional options:

Configuration	Description
Data source mapping	Map named Cube data_source values to warehouse hosts and default database/schema. Required for every non-default data_source referenced in your schema.
Cube pattern	Include or exclude cubes by name using regular expressions. Defaults to including all cubes.
View pattern	Include or exclude views by name using regular expressions. Defaults to including all views.
Security context	Stub values for offline Jinja rendering of COMPILE_CONTEXT.securityContext. Supported keys: tenant, deployment_id, team, environment.
Custom context	Additional top-level COMPILE_CONTEXT keys for offline Jinja rendering (string values).

Each data source mapping entry includes:

Field	Description
Warehouse technology	Warehouse type for this named data source.
Snowflake host	Warehouse host for cubes that use this named data source.
Default database	Default database for unqualified sql_table names on this data source.
Default schema	Default schema for unqualified table names on this data source.
Security context	Optional override of the top-level security context for this data source.
Custom context	Optional override of the top-level custom context for this data source.

Step 5: Save configuration

Click Save. Euno opens a modal with:

• Your trigger secret — copy and store it securely; it is shown only once

• The prepare-upload endpoint URL — for programmatic zip uploads

Use the trigger secret as a Bearer token in the Authorization header for prepare-upload calls.

Rotating your trigger secret: Open your Cube Core source on the Sources page and click Reset Trigger Key to generate a new secret. This invalidates the previous secret immediately.

Uploading Cube schema YAML

Preparing your upload

Package your Cube model tree as a single .zip file:

• Include YAML files under model/**/*.yml or model/**/*.yaml

• Each file must parse as YAML with a mapping root and contain a cubes: and/or views: section

• Upload exactly one .zip file per run

Upload methods

Manual upload via UI

The easiest way to upload Cube schema YAML is through Euno's UI:

1. Open your Cube Core source on the Sources page.

2. Click Upload Artifacts.

3. Select your .zip file and start the run.

Euno parses the schema, emits Cube resources, and runs lineage enrichment to warehouse tables and columns. Check the run report for inventory counts, skipped files, and Jinja render results.

Programmatic upload (recommended for production)

For production workflows, upload your zip after Cube schema changes using the prepare-upload endpoint:

1. Request a signed upload URL — POST to .../integrations/YOUR_INTEGRATION_ID/prepare-upload with the zip filename and Authorization: Bearer YOUR_TRIGGER_SECRET

2. Upload the zip — PUT the file to the signed URL from the response

3. Processing starts automatically — no further API call is required

See reference implementations below:

Python script

Use a standalone Python script to zip and upload your Cube model tree → View Python Upload Guide

GitHub Actions

Automate uploads when Cube schema YAML changes in your repository → View GitHub Actions Guide

Euno performs offline Jinja2 rendering for sql_table values that contain COMPILE_CONTEXT references. Rendering uses only COMPILE_CONTEXT assembled from Security context and Custom context—control-flow constructs such as {% if %} work when they depend on those stub values. Cube runtime helpers and macros (for example env_var() or functions from model/globals.py) are not available, and query-compilation variables such as {CUBE} are not evaluated.