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Tuning Your Application

When Tuning Is Needed

It should be noted that the default settings often work well for the majority of applications. However, there’s no formula for determining the perfect autoscale settings. The best way to optimize for your app is to start with the defaults and observe how your app is autoscaled.

If your app has trouble recovering quickly from slowdowns, you might benefit from scaling up by multiple dynos at a time.

If you want to optimize for cost savings, you might want to downscale faster by shortening the time between downscale events.

Upscale Jumps

By default, Judoscale will scale up or down by one dyno at a time. It will continue to do this until queue time has settled within the target queue time range (between the upscale and downscale thresholds).

If your app receives sudden bursts of traffic and needs to scale up as quickly as possible, you might want to scale up by multiple dynos at a time.

Screenshot: Upscale jumps control

You can scale up by as many dynos as you want, but keep in mind you’ll never be autoscaled beyond your autoscale dyno range.

For example, let's say your dyno range is 2–10 dynos, and you've set "upscale jumps" to 2 dynos. If you're currently running 7 dynos, the first upscale event will jump to 9 dynos, and a subsequent upscale event would scale to 10 dynos—your dyno range would prevent a 2-dyno jump.

Downscale Delay

This downscaling option controls the time between subsequent downscales, and it also controls the time before the first downscale event.

Screenshot: Downscale delay control

Downscaling is not triggered immediately when queue times drop below the downscale threshold because this could result in yo-yo autoscaling—rapidly autoscaling up and down. Judoscale waits to downscale until queue times have settled and remain below the downscale threshold for 10 minutes (the default), or whatever you specify here.

After that, your app will continue downscaling at the same rate (every 10 minutes by default) as long as queue time remains completely below the downscale threshold.

Autoscaling Responsiveness