Automated autoscaling for Heroku, Render, and AWS, optimizing costs with queue time metrics.
Product memo
Developers using Heroku, Render, and AWS get automated autoscaling for web processes and job queues. It uses queue time as a key metric, providing faster, more precise scaling than traditional CPU-based methods. This approach helps reduce hosting costs by preventing overprovisioning, ensuring applications scale efficiently with demand.
For who
Developers using Heroku, Render, and AWS
Solves what
Automated, fast, and cost-effective application autoscaling
- Queue time based autoscaling
- Job queue scaling
- Fast autoscaling algorithm
In their own words
One-Click Autoscaling
ultra-fast autoscaling, smart metrics, without the confusing config.
autoscaling that just works. for ruby, node, python, and more. platform-integrated with heroku, render, and amazon ecs.
Commercial cues
Model
subscription
Free tier
Yes
Trial
No
Pricing Strategy
- • A free tier provides a low-risk entry for basic scaling needs.
- • Task-based tiers align costs directly with application complexity.
- • Unlimited autoscaling events across paid tiers remove usage anxiety.
Operator context
Operating setup
Platform
API
Audience
Developers
Tech stack
Builder Strategy
- Strategy Type
- Niche Specialist
- Stage
- Vc Growth
- Effort
- Small Team
About Judoscale Expand
Judoscale offers specialized application autoscaling for developers working with Heroku, Render, and AWS. It focuses on critical metrics like queue time to deliver faster, more accurate scaling decisions for both web processes and job queues.
This precision helps reduce infrastructure costs by ensuring resources are always matched to current demand, avoiding unnecessary overprovisioning. The product's deep integration with popular platforms makes it a natural fit for teams already operating within these environments, providing a direct way to manage application performance and efficiency.