How to deploy Vizzly on GCP Cloud Run
This guide will take you through deploying the Vizzly Query Engine to the Google Cloud Run service. It assumes you have already;
- Created your Vizzly account and self-hosted project.
- Created your Google Cloud Platform (GCP) account.
- Installed and authenticated the Vizzly CLI.
- Have generated your
vizzly.envfile using the Vizzly CLI.
On your GCP account, search and open the "Cloud Run" product.
Click "Create service".
Set the "Docker image URI" of the Vizzly Query Engine. For this demo I will use
eu.gcr.io/vizzly/query-engine:latest, but for production, we strongly recommend pinning to a specific version of the query engine.
Then, select the region that you want to deploy the Query Engine to!
In the autoscaling section, ensure there is always at least one instance of the Vizzly Query Engine by setting the minimum number to at least 1.
maximum instances to a threshold that you are comfortable with given your traffic pattern.
We need to make the Cloud Run instance available over the internet, so select the "Allow unauthenticated invocations" option under the "Authentication" section.
This will not mean that anyone can access your data because the Vizzly Query Engine manages authentication on a request-by-request basis.
Set the container port to
Use the "Variables & Secrets" section to add all the key-value pairs in your
vizzly.env file to the Cloud Run instance.
Now we have created our secrets, we need to grant the Cloud Run instance a role that allows it to access them.
First, click "Create new service account" under the security tab.
If you are using Cloud SQL, you will need to allow access by completing the "Cloud SQL Connections" section.
When ready, click the "Create" button at the bottom of the page.
Once deployed, you will be able to see the URL where GCP has deployed the Vizzly Query Engine. You can visit the
/get-started page and continue the setup there!
For this example, we can see the URL is
You will then be able to go through the get started process for the Query Engine, and start building the data sets to make available to your users!