A few weeks ago I gave a presentation at the Columbus Ruby Brigade about my approach and mental model for scaling Heroku apps. My attempt to record the talk failed, so I rerecorded it as a screencast just for you. ❤️
Here’s what I cover in the video:
Scaling option #1: Horizontal—add more dynos. If you see increased request queue times in Scout or New Relic, you need to make your app faster or add more dynos. As soon as you’re using more than one dyno, automate it instead of playing a guessing game.
Scaling option #2: Vertical—increase dyno size. Because of Heroku’s random routing, you need concurrency within a single dyno. This means running more web processes, which consume more memory and may require a larger dyno type. Aim for at least three web progresses.
Scaling option #3: Process types. You’re not limited to just “web” and “worker” process types in your Procfile. Consider multiple worker process types that pull from different job queues. These can be scaled independently for more control and flexibility.
Scaling option #4: App instances. Heroku Pipelines make it relatively easy to deploy a single codebase to multiple production apps. This can be helpful to isolate your main app traffic from traffic to your API or admin endpoints, for example. Heroku will route traffic to the correct app based on the request subdomain and the custom domains configured for each app.
My general advice:
Start simple.
Configure multiple web processes per dyno, increasing dyno size if needed.
If you need more than one web dyno, autoscale it.
If certain background workers are resource hogs, they may require a larger dyno size. Split into their own process types with dedicated job queues so they can be scaled independently.
If you have dedicated sections of your web app such as an API or admin section, split them into their own subdomain so you can divert traffic to a separate app instance. Keep them on a single app instance until the additional complexity is absolutely necessary.
Did you find the video helpful? Anything you’d add or change? Let me know!
Happy scaling!
— Adam (@adamlogic)