Autoscale Your Good Job Workers The Right Way
$ bundle add judoscale-good_job
Why autoscale your Good Job workers?
Most Good Job setups are over-provisioned. You’re paying through the nose for resources you don’t need, but you do it because you’ve been burned with downtime.
Even worse, you still encounter unexpected queue backlogs! Workloads are variable and sometimes unpredictable, so even your extra workers aren’t always enough.
Autoscaling is the solution here, and it’s pretty simple. We monitor the capacity of your Good Job queues, and we scale your workers accordingly. You’ll never pay for resources you don’t need, and you’ll always have capacity to meet those sudden bursts of jobs.
Explore for yourself in our sandbox app →
What makes Judoscale different?
While most autoscalers rely on generic metrics like CPU, Judoscale monitors the queue latency in your Good Job setup. Queue latency is a way more reliable capacity metric for workers, and we built our autoscaler with queue latency in mind from the beginning.
We also give you a whole lot of control and visibility into your autoscaling that you won’t find elsewhere. Autoscaling is all we do, and we’ve been doing it for a long time.
- Trusted by900+engineering teams
- Over2.5 millionrequests per month
- Since2017we are here to stay
The fastest autoscaler for Good Job
With autoscaling decisions made every 10 seconds, Judoscale ensures your Good Job workers scale up quickly to meet demand.
Independent queues & processes
No matter how many worker processes you have, Judoscale will autoscale all of them. And of course you’ll have dedicated controls for each one.
Reduce Good Job Hosting Costs
Avoid overscaling with Judoscale’s precise autoscaling algorithm, saving you money on hosting costs without sacrificing performance.
You’re In Control
Fine-tune your autoscale settings with Judoscale’s easy-to-use controls, ensuring the perfect configuration for your Good Job setup.
Explore the configs in our sandbox app →Start autoscaling for free
Setup takes less than 5 minutes