Next, follow the link to your Render account settings to obtain your API key.
👀 Note
Judoscale needs your API key in order to fetch service information and update the number of
running instances. Your Render services are not affected until you explicitly enable autoscaling
In your Render account settings, create a new API key and name it “Judoscale” (you can name it anything you want).
Paste your API key into Judoscale, and click “Connect to Render”.
Judoscale will list your personal Render account and any teams you’re a part of. Select the team you want to link to Judoscale.
👀 Note
You can link additional teams later by clicking “Add team” in the Judoscale dashboard sidebar.
After linking a team to Judoscale, you’ll be on the Judoscale team dashboard. Here you’ll see all of your Render services, the number of running instances, and their autoscaling status within Judoscale. If this is your first time linking a team, none will be autoscaling yet.
👀 Note
Judoscale cannot see whether you’re using Render’s native autoscaling feature. You should disable
Render’s autoscaler before enabling autoscaling in Judoscale. **Using multiple autoscalers on the
Installing the adapter
In the Judoscale team dashboard, click the service you want to autoscale. This takes you to the Scaling page, where you’ll be prompted to install the adapter.
Choose your stack information, and follow the instructions to install the adapter. The adapter is how Judoscale collects queue metrics from your application, similar to a lightweight APM tool.
Once you’ve installed the adapter and deployed your application, Judoscale will begin showing your queue metrics in the Scaling page charts.
If your web service isn’t receiving traffic, or if your worker service has no jobs waiting in queue, you won’t see any activity in the charts. Let it collect metrics while your app is under load to see queue time inforamation.
Configuring and enabling autoscaling
Now that Judoscale is monitoring your service, you’re ready to autoscale!
Scroll down the Scaling page to review your autoscale settings. The default settings are usually a good starting point for most services, but you’ll want to customize your “Instances” range based on how high and low you’re comfortable scaling.
There’s no “correct” range here. Judoscale defaults to one instance as the minimum, but some teams always want multiple instances running even under light load, so they’ll see the minimum instances to two or higher. The maximum is really about limiting costs. Remember that under heavy load (high queue times), Judoscale will continue scaling your service up until the max instances is reached.
Scroll down and click “Save and enable autoscaling”, and that’s it!
🚨 Warning
If anything in these docs doesn’t work quite right or you have questions, know that you can always
reach out to us at [email protected]. Your email goes directly to the Judoscale devs!