Free Heroku Autoscaling for your Web and Worker Dynos

Serious cost savings for Ruby and Python applications with variable traffic and limited DevOps resources.

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What is Dynoscale?

Dynoscale is a SAAS tool to help you scale Heroku Dynos to meet the variable traffic of your site while helping keep costs low.

Simple, Yet Powerful Scaling Rules

We have very flexible autoscaling policies that work for both straightforward and complex traffic patterns.

Workers Too!

Do you have intermittent worker load with strict completion times? We can help with that too. Check out our Worker Dyno autoscaling policies.

Monitor Dyno Scaling

View dyno reporting in realtime with our helpful usage graphs.

Track your Savings

Curious how much Dynoscale is saving you? We have a report to show your savings.

Secondary Product Demo

Includes Dynoscale Fee for Standard Plan

Calculate Savings!

How much can you save with Dynoscale?

Dynoscale will save you a lot in Dyno costs. See how much you can save with our forecasting calculator.

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Simple Pricing

Easy pricing means no suprises.

$ 0 /mo
  • 1-2 Standard Dynos
  • Self Serve Support Documentation
  • Email support
$ 25 /mo
  • 1-99 Standard Dynos
  • Self Serve Support Documentation
  • Priority Email support
$ 100 /mo
  • 1-99 Standard or Performance Dynos
  • Self Serve Support Documentation
  • Expedited Email support
$ 1000 /mo
  • 1-99 Standard or Performance Dynos
  • Self Serve Support Documentation
  • Dedicated Support Contact
  • 99.99% Uptime SLA
  • Rules Consultation
Can I cancel anytime?

Yes, billing is based on monthly prorated usage. Cancel anytime and only pay for what you use.

What technologies are currently supported?

Dynoscale currently supports Ruby and Python Heroku applications.

Can I use Dynoscale accross mutliple Heroku Apps?

Dynoscale does not support attaching to multiple apps. You must install the add-on for each app.

Will the Dynoscale addon impact the performance of my application?

The addon has no noticeable end user impact. It collects request time metrics and stores the data in an in-memery store. Periodically, the data is shipped to our servers to control autoscaling.