# Configuring a Multi-Instance Looker Deployment

DevFeed: [Configuring a Multi-Instance Looker Deployment](<https://devfeed.tech/articles/configuring-a-multi-instance-looker-deployment-23874.md>)

Original publisher: [Read original article](<https://engineering.premise.com/configuring-a-multi-instance-looker-deployment-0f1eec1b8e7a?source=rss----c5fada0a103d---4>)

Author: Dennis Mutia

Published: 2023-11-13T15:00:28Z

Content type: tutorial

Language: en

Sources: [Engineering at Premise - Medium](<https://devfeed.tech/sources/engineering-at-premise-medium.md>)

Topics: [dashboards](<https://devfeed.tech/topics/dashboards.md>), [GitHub](<https://devfeed.tech/topics/github.md>), [Backstage](<https://devfeed.tech/topics/backstage.md>), [releases](<https://devfeed.tech/topics/releases.md>), [Development](<https://devfeed.tech/topics/development.md>), [Deployment](<https://devfeed.tech/topics/deployment.md>)

Tags: [backstage](<https://devfeed.tech/tags/backstage.md>), [business-intelligence](<https://devfeed.tech/tags/business-intelligence.md>), [cloud-computing](<https://devfeed.tech/tags/cloud-computing.md>), [dashboards](<https://devfeed.tech/tags/dashboards.md>), [developer](<https://devfeed.tech/tags/developer.md>), [developer-portal](<https://devfeed.tech/tags/developer-portal.md>), [development](<https://devfeed.tech/tags/development.md>), [gcp](<https://devfeed.tech/tags/gcp.md>), [github](<https://devfeed.tech/tags/github.md>), [looker](<https://devfeed.tech/tags/looker.md>), [operational](<https://devfeed.tech/tags/operational.md>), [production](<https://devfeed.tech/tags/production.md>), [releases](<https://devfeed.tech/tags/releases.md>)

## AI overview

This article explains how Premise configured three Looker instances to separate development from production for LookML and dashboards. It describes standardized data connections, view-only production access, GitHub-based synchronization and releases, Backstage-driven promotion, and Slack notifications.

## Source excerpt

By Dennis Mutia, Software Engineer Image by ismagilov on Unsplash This article provides a high level overview of how we have configured multiple Looker deployments to separate development and production environments for both LookML and dashboards. Having a Looker deployment on a single instance has many challenges which include: a dashboard can get edited when someone else is presenting it to a client or a stakeholder someone testing a large dashboard can slow down Looker which will affect other dashboards Looker users cannot test the effects of model changes to their dashboards without having to request for developer access which has cost implications Multiple Looker instances We have set up 3 Looker instances: a development instance where LookML updates are made and dashboards created and reviewed before being released to production, and two production instances. One of the production instances is for internal looks and dashboards and the other for creating dashboards that can be shared with external clients. All three Looker instances have a standardized data connection to read from the same data warehouse. This is to ensure that dashboards and looks work the same access all environments. To ensure all development actually occurs on the development instance, both production instances enforce view only access for all users. This set up allows us to test both data models and dashboards without affecting production content. It also leads to standardized data models across all production instances. Linking development to production To take advantage of the benefits of multiple Looker instances, while limiting the operational maintance, we have linked all three looker instances using GitHub, and use GitHub Releases to update the production instances whenever changes have been tested and approved in development. To release dashboards from development to production we use Backstage, which is also our developer portal. We have created a template which dashboard builders