Admin settings - Continuous Integration

The Continuous Integration page in the Platform section of the Admin menu lets you configure settings for the Looker Continuous Integration (CI) feature. Configure Looker (Google Cloud core) CI settings to ensure the quality and reliability of your LookML projects. CI prevents query errors and identifies issues with SQL, data tests, content, and LookML before they reach production. You can also configure CI validators to run automatically when a pull request is submitted to your LookML repository, streamlining your development workflow.

Note: For Looker (Google Cloud core) instances, Continuous Integration is supported on instances that are configured with a Public IP network configuration. CI isn't supported on Looker (Google Cloud core) instances that are enabled for CMEK, or on instances that are configured with a private connections or hybrid connections network configuration.

Compliance capabilities of Continuous Integration

Looker CI is not included in the FedRAMP High, FedRAMP Moderate, or DoD Impact Level 5 (IL5) authorization boundaries.

Prior to enabling the Looker CI setting for your Looker instance, consult with your authorizing body to determine whether Looker CI's compliance offerings meet your organization's specific security and regulatory requirements.

For Looker (Google Cloud core) instances, each Assured Workloads control package that becomes available will add Looker CI features as default offerings as that package's change requirements and processes are met.

Enable Continuous Integration

The Looker Continuous Integration (CI) feature lets you run tests on your LookML project to deliver more reliable, efficient, and user-friendly data experiences. You can use the CI validators to identify issues with SQL, data tests, content, and LookML before they hit production to verify your LookML and prevent query errors for your users. You can also configure the CI validators to run automatically on a schedule or when a pull request is submitted to your LookML repository.

A Looker admin can use the Enable Continuous Integration toggle to enable CI on your instance.

Note: For Looker (original) instances that use an IP allowlist to specify a list of IP addresses that can access your Looker instance, you must manually add an IP address for Continuous Integration. Contact Support to get the IP address. (For Looker (Google Cloud core) instances that use an IP allowlist, CI functionality is housed within the Google Cloud network, so you don't need to manually add an IP address for CI.)

Looker CI users

When you enable Continuous Integration on your instance, Looker automatically creates 10 Looker CI users in the Looker CI Users user group with the Looker CI Users role. A Looker admin can view the Looker CI users from the Service Accounts tab of the Users Admin page.

If your instance uses access grants to control access to Explores, the Looker CI users must be included in those access grants. You can include the CI users by assigning the relevant user attribute values to the Looker CI Users group, as described on the Admin settings - User attributes documentation page.

Integrations

Continuous Integration lets you run CI suites automatically when pull requests or commits occur in your remote Git repository. You can configure Continuous Integration to integrate with the following Git providers:

• GitHub (use the Looker CI GitHub app)
• GitLab (use the Looker API and GitLab CI)
• Bitbucket (use the Looker API and Bitbucket Pipelines)
• GitHub Actions (use the Looker API and GitHub Actions)

GitHub

If you have a cloud-based GitHub repository as a remote repository for your LookML project, you can configure Continuous Integration to automatically run CI suites when LookML developers submit pull requests to your LookML repository.

Note: Continuous Integration supports only cloud-based GitHub and doesn't support self-hosted GitHub Enterprise servers. In addition, CI doesn't support GitHub Enterprise configurations that use single sign-on (SSO) for login or that use GitHub's IP allowlist feature.

To automatically run CI suites on your repository, Continuous Integration needs the following permissions:

• Read access to your repository's metadata and pull requests
• Read and write access to your repository's commit statuses, repository hooks, and workflows

These permissions are not set up when you set up a Git connection for your LookML project in the Looker IDE. If you want to use pull request triggering for CI runs, your LookML project must be set up with a Git connection (as described on the Setting up and testing a Git connection page), and you must also configure the CI GitHub app as described in the Configuring the CI GitHub app section.

GitHub table

The GitHub table on the Continuous Integration Admin page lists the GitHub repositories that are configured for the LookML projects on your Looker instance. These GitHub repositories were configured by your LookML developers as described on the Setting up and testing a Git connection documentation page.

For each GitHub repository that's listed, the table shows whether the repository has been configured with the CI GitHub app:

• Installed: The repository has been granted the Looker CI GitHub application which enables CI to be automatically run when LookML developers submit pull requests to your LookML repository.
• Not Installed: The repository hasn't been set up for pull request integration with Looker CI. To configure the repository for CI pull request integration, see the Configuring the CI GitHub app section.

Configuring the CI GitHub app

To grant the CI GitHub application for a repository, follow these steps:

1. On the Continuous Integration Admin page in Looker, click the Configure GitHub App button. This will open a browser window to the GitHub apps webpage.
2. Select the GitHub account where your LookML is stored.
3. In the Repository access section, select All repositories to allow CI integrations for all of the Git repositories owned by the resource owner, or select Only select repositories to choose the repositories with which you want to use Continuous Integration.
4. Click Save.

If the Looker CI GitHub application is successfully granted to the repository, Looker displays Installed for the repository in the GitHub table on the Continuous Integration Admin page.

GitLab

You can trigger Looker Continuous Integration runs from GitLab CI by using the Looker API and the official Looker Python SDK (looker-sdk).

To trigger a Looker CI run from a GitLab CI pipeline, complete the following steps:

1. Configure CI/CD variables in GitLab.
2. Create the Python script for GitLab CI.
3. Configure the GitLab CI workflow.

Configure CI/CD variables in GitLab

In your GitLab project, go to Settings > CI/CD > Variables and create the following CI/CD variables. Set each variable to Masked to protect sensitive values:

• LOOKERSDK_BASE_URL: the API URL of your Looker instance (for example, https://example.cloud.looker.com)
• LOOKERSDK_CLIENT_ID: the API3 Client ID generated from the Users Admin page in Looker
• LOOKERSDK_CLIENT_SECRET: the corresponding API3 Client Secret generated from the Users Admin page in Looker

Create the Python script for GitLab CI

Create a Python script named run_looker_ci.py in your repository. This script uses the Looker SDK to trigger the CI run and poll until the run finishes:

import os
import sys
import time
import looker_sdk
from looker_sdk import models as mdls

# Retrieve required settings from environment variables
project_id = os.getenv("LOOKER_PROJECT_ID")
suite_id = os.getenv("LOOKER_SUITE_ID")

# GitLab CI specific environment variables
branch = os.getenv("CI_COMMIT_REF_NAME")
commit = os.getenv("CI_COMMIT_SHA")

if not all([project_id, suite_id, branch, commit]):
    print("Error: Missing required environment variables (LOOKER_PROJECT_ID, LOOKER_SUITE_ID, or GitLab vars).")
    sys.exit(1)

# Initialize the Looker SDK.
# The SDK automatically picks up LOOKERSDK_BASE_URL, LOOKERSDK_CLIENT_ID, and LOOKERSDK_CLIENT_SECRET.
print("Initializing Looker SDK...")
try:
    sdk = looker_sdk.init40()
except Exception as e:
    print(f"Failed to initialize Looker SDK: {e}")
    sys.exit(1)

# Configure the request body
print(f"Starting Looker CI run for project '{project_id}', suite '{suite_id}'...")
print(f"Branch: {branch} | Commit: {commit}")

request_body = mdls.CreateContinuousIntegrationRunRequest(
    suite_id=suite_id,
    branch=branch,
    commit=commit
)

# Trigger the CI run
try:
    run = sdk.create_continuous_integration_run(
        project_id=project_id,
        body=request_body
    )
    run_id = getattr(run, "run_id", getattr(run, "id", None))
    print(f"Looker CI run created successfully. Run ID: {run_id}")
except looker_sdk.error.SDKError as e:
    print(f"Failed to create Looker CI run: {e}")
    sys.exit(1)

# Poll for completion
run_status = run.status
terminal_statuses = ["cancelled", "error", "passed", "failed"]

while run_status not in terminal_statuses:
    print(f"Run {run_id} status is '{run_status}'. Waiting 15 seconds...")
    time.sleep(15)
    
    try:
        run = sdk.get_continuous_integration_run(
            project_id=project_id,
            run_id=run_id
        )
        run_status = run.status
    except looker_sdk.error.SDKError as e:
        print(f"Error while polling Looker CI run status: {e}")
        sys.exit(1)

print(f"Final Looker CI run status: {run_status}")

if run_status != "passed":
    print("Looker CI run did not pass. Failing the GitLab CI job.")
    sys.exit(1)

print("Looker CI run passed successfully!")

Configure the GitLab CI workflow

In the root directory of your repository, create or update your .gitlab-ci.yml pipeline configuration file to install looker-sdk and execute run_looker_ci.py:

stages:
  - test

looker-ci:
  stage: test
  image: python:3.10
  variables:
    LOOKER_PROJECT_ID: "LOOKER_PROJECT_ID"
    LOOKER_SUITE_ID: "LOOKER_SUITE_ID"
  script:
    - pip install looker-sdk
    - python run_looker_ci.py
  rules:
    - if: $CI_PIPELINE_SOURCE == "merge_request_event"

Replace the following:

• LOOKER_PROJECT_ID: the ID of the Looker project that you want to test
• LOOKER_SUITE_ID: the ID of the CI suite that you want to run

Bitbucket

You can trigger Looker Continuous Integration runs from Bitbucket Pipelines by using the Looker API and the official Looker Python SDK (looker-sdk).

To trigger a Looker CI run from Bitbucket Pipelines, complete the following steps:

1. Configure repository variables in Bitbucket.
2. Create the Python script for Bitbucket Pipelines.
3. Configure the Bitbucket Pipelines workflow.

Configure repository variables in Bitbucket

In your Bitbucket repository, go to Repository settings > Repository variables and create the following repository variables. Set each variable to Secured to protect sensitive values:

• LOOKERSDK_BASE_URL: the API URL of your Looker instance (for example, https://example.cloud.looker.com)
• LOOKERSDK_CLIENT_ID: the API3 Client ID generated from the Users Admin page in Looker
• LOOKERSDK_CLIENT_SECRET: the corresponding API3 Client Secret that's generated from the Users Admin page in Looker

Create the Python script for Bitbucket Pipelines

Create a Python script named run_looker_ci.py in your repository. This script uses the Looker SDK to trigger the CI run and poll until the run finishes:

import os
import sys
import time
import looker_sdk
from looker_sdk import models as mdls

# Retrieve required settings from environment variables
project_id = os.getenv("LOOKER_PROJECT_ID")
suite_id = os.getenv("LOOKER_SUITE_ID")

# Bitbucket Pipelines specific environment variables
branch = os.getenv("BITBUCKET_BRANCH")
commit = os.getenv("BITBUCKET_COMMIT")

if not all([project_id, suite_id, branch, commit]):
    print("Error: Missing required environment variables (LOOKER_PROJECT_ID, LOOKER_SUITE_ID, or Bitbucket vars).")
    sys.exit(1)

# Initialize the Looker SDK.
# The SDK automatically picks up LOOKERSDK_BASE_URL, LOOKERSDK_CLIENT_ID, and LOOKERSDK_CLIENT_SECRET.
print("Initializing Looker SDK...")
try:
    sdk = looker_sdk.init40()
except Exception as e:
    print(f"Failed to initialize Looker SDK: {e}")
    sys.exit(1)

# Configure the request body
print(f"Starting Looker CI run for project '{project_id}', suite '{suite_id}'...")
print(f"Branch: {branch} | Commit: {commit}")

request_body = mdls.CreateContinuousIntegrationRunRequest(
    suite_id=suite_id,
    branch=branch,
    commit=commit
)

# Trigger the CI run
try:
    run = sdk.create_continuous_integration_run(
        project_id=project_id,
        body=request_body
    )
    run_id = getattr(run, "run_id", getattr(run, "id", None))
    print(f"Looker CI run created successfully. Run ID: {run_id}")
except looker_sdk.error.SDKError as e:
    print(f"Failed to create Looker CI run: {e}")
    sys.exit(1)

# Poll for completion
run_status = run.status
terminal_statuses = ["cancelled", "error", "passed", "failed"]

while run_status not in terminal_statuses:
    print(f"Run {run_id} status is '{run_status}'. Waiting 15 seconds...")
    time.sleep(15)
    
    try:
        run = sdk.get_continuous_integration_run(
            project_id=project_id,
            run_id=run_id
        )
        run_status = run.status
    except looker_sdk.error.SDKError as e:
        print(f"Error while polling Looker CI run status: {e}")
        sys.exit(1)

print(f"Final Looker CI run status: {run_status}")

if run_status != "passed":
    print("Looker CI run did not pass. Failing the Bitbucket Pipeline.")
    sys.exit(1)

print("Looker CI run passed successfully!")

Configure the Bitbucket Pipelines workflow

In the root directory of your repository, create or update your bitbucket-pipelines.yml file to install looker-sdk and execute run_looker_ci.py:

image: python:3.10

pipelines:
  pull-requests:
    '**':
      - step:
          name: Looker CI
          script:
            - export LOOKER_PROJECT_ID="LOOKER_PROJECT_ID"
            - export LOOKER_SUITE_ID="LOOKER_SUITE_ID"
            - pip install looker-sdk
            - python run_looker_ci.py

Replace the following:

• LOOKER_PROJECT_ID: the ID of the Looker project that you want to test
• LOOKER_SUITE_ID: the ID of the CI suite that you want to run

GitHub Actions

You can trigger Looker Continuous Integration runs from GitHub Actions by using the Looker API and the official Looker Python SDK (looker-sdk).

To trigger a Looker CI run from a GitHub Actions workflow, complete the following steps:

1. Configure repository secrets in GitHub.
2. Create the Python script for GitHub Actions.
3. Configure the GitHub Actions workflow.

Configure repository secrets in GitHub

In your GitHub repository, go to Settings > Secrets and variables > Actions and create the following repository secrets:

• LOOKERSDK_BASE_URL: the API URL of your Looker instance (for example, https://example.cloud.looker.com)
• LOOKERSDK_CLIENT_ID: the API3 Client ID generated from the Users Admin page in Looker
• LOOKERSDK_CLIENT_SECRET: the corresponding API3 Client Secret that's generated from the Users Admin page in Looker

Create the Python script for GitHub Actions

Create a Python script named run_looker_ci.py in your repository. This script uses the Looker SDK to trigger the CI run and poll until the run finishes:

import os
import sys
import time
import looker_sdk
from looker_sdk import models as mdls

# Retrieve required settings from environment variables
project_id = os.getenv("LOOKER_PROJECT_ID")
suite_id = os.getenv("LOOKER_SUITE_ID")

# GitHub Actions specific environment variables
# GITHUB_HEAD_REF is the branch name for PRs. 
# GITHUB_REF_NAME can be used as a fallback for non-PR events.
branch = os.getenv("GITHUB_HEAD_REF") or os.getenv("GITHUB_REF_NAME")
# GITHUB_PR_SHA is the head commit SHA for PRs.
# GITHUB_SHA can be used as a fallback for non-PR events.
commit = os.getenv("GITHUB_PR_SHA") or os.getenv("GITHUB_SHA")

if not all([project_id, suite_id, branch, commit]):
    print("Error: Missing required environment variables (LOOKER_PROJECT_ID, LOOKER_SUITE_ID, or GitHub vars).")
    sys.exit(1)

# Initialize the Looker SDK.
# The SDK automatically picks up LOOKERSDK_BASE_URL, LOOKERSDK_CLIENT_ID, and LOOKERSDK_CLIENT_SECRET.
print("Initializing Looker SDK...")
try:
    sdk = looker_sdk.init40()
except Exception as e:
    print(f"Failed to initialize Looker SDK: {e}")
    sys.exit(1)

# Configure the request body
print(f"Starting Looker CI run for project '{project_id}', suite '{suite_id}'...")
print(f"Branch: {branch} | Commit: {commit}")

request_body = mdls.CreateContinuousIntegrationRunRequest(
    suite_id=suite_id,
    branch=branch,
    commit=commit
)

# Trigger the CI run
try:
    run = sdk.create_continuous_integration_run(
        project_id=project_id,
        body=request_body
    )
    run_id = getattr(run, "run_id", getattr(run, "id", None))
    print(f"Looker CI run created successfully. Run ID: {run_id}")
except looker_sdk.error.SDKError as e:
    print(f"Failed to create Looker CI run: {e}")
    sys.exit(1)

# Poll for completion
run_status = run.status
terminal_statuses = ["cancelled", "error", "passed", "failed"]

while run_status not in terminal_statuses:
    print(f"Run {run_id} status is '{run_status}'. Waiting 15 seconds...")
    time.sleep(15)
    
    try:
        run = sdk.get_continuous_integration_run(
            project_id=project_id,
            run_id=run_id
        )
        run_status = run.status
    except looker_sdk.error.SDKError as e:
        print(f"Error while polling Looker CI run status: {e}")
        sys.exit(1)

print(f"Final Looker CI run status: {run_status}")

if run_status != "passed":
    print("Looker CI run did not pass. Failing the GitHub Action.")
    sys.exit(1)

print("Looker CI run passed successfully!")

Configure the GitHub Actions workflow

In your repository, create a workflow file at .github/workflows/looker-ci.yml with the following configuration:

name: Looker CI
on:
  pull_request:
    branches:
      - main

jobs:
  run-looker-ci:
    runs-on: ubuntu-latest


    env:
      # Automatically picked up by the Looker SDK
      LOOKERSDK_BASE_URL: ${{ secrets.LOOKERSDK_BASE_URL }}
      LOOKERSDK_CLIENT_ID: ${{ secrets.LOOKERSDK_CLIENT_ID }}
      LOOKERSDK_CLIENT_SECRET: ${{ secrets.LOOKERSDK_CLIENT_SECRET }}


      # Passed directly to the script
      LOOKER_PROJECT_ID: "LOOKER_PROJECT_ID"
      LOOKER_SUITE_ID: "LOOKER_SUITE_ID"
      GITHUB_PR_SHA: ${{ github.event.pull_request.head.sha }}

    steps:
      - name: Checkout Code
        uses: actions/checkout@v4

      - name: Set up Python
        uses: actions/setup-python@v5
        with:
          python-version: '3.10'

      - name: Install Dependencies
        run: |
          python -m pip install --upgrade pip
          pip install looker-sdk

      - name: Run Looker CI
        run: python run_looker_ci.py

Replace the following:

• LOOKER_PROJECT_ID: the ID of the Looker project that you want to test
• LOOKER_SUITE_ID: the ID of the CI suite that you want to run

dbt Cloud Configuration

If you use dbt Cloud, you can configure Continuous Integration to automatically run CI suites when a dbt Cloud CI job finishes. The CI suite run helps ensure that changes to your dbt models don't break your LookML project.

To configure the dbt Cloud integration, follow these steps in the dbt Cloud Configuration section:

1. In the dbt Cloud Host URL field, enter the URL to your dbt Cloud account.
2. In the dbt Cloud API Key field, enter a dbt Cloud service account token.
3. Click Test Connection. Looker will verify that it can connect to your dbt Cloud account and then retrieve your dbt Cloud Account ID.
4. Click Save.

User Attributes

You can configure user attributes that Continuous Integration can override during validation runs. User attributes are used in conjunction with the dbt Cloud integration to point Looker to temporary schemas created by dbt Cloud CI jobs.

To configure user attribute defaults for CI, follow these steps in the User Attributes section:

1. In the User Attribute field, select a user attribute from the drop-down list. If no user attribute is selected, Looker will use the user attribute that's defined in the Primary Dataset field in your database connection for CI runs.
2. In the Value for CI run field, enter the value that should be used with this user attribute for CI runs.
3. Click Save.

You can add multiple user attribute and value pairs. Each user attribute configured in the User Attributes section will be available for selection as an override in your CI Suite configurations.

To delete a user attribute and value pair, click Remove.