Show HN: Dynosaur, An autoscaler for Heroku using Google Analytics Live(engineering.harrys.com) |
Show HN: Dynosaur, An autoscaler for Heroku using Google Analytics Live(engineering.harrys.com) |
Of course, we are a Rails shop who have been on Heroku since we launched, so Heroku is really tailor made for us. If you're happy on raw AWS, good for you. Every hour I'm not thinking about AWS is an hour I can be writing a feature for our 10-month-old startup. The extra cost of Heroku is negligible when viewed in that light.
Congrats on the launch and thanks for helping!
Our main motivation was to write something that scaled as we scale manually (i.e. when we get a lot of traffic due to press hits etc, we scale up based on GA realtime data as well as New Relic response times). When we were given access to the GA live API it just seemed like a natural fit.
No offense intended: you picked a cool name!
Heroku provides log-runtime-metrics, which includes current cpu load / pending cpu tasks. The librato addon also shows request throughput in its dashboard UI. I'm not sure where it gets this data from. If not logging then perhaps new relic?
On two dynos you can have 1 do background jobs and 1 server content
obviously it varies, but you don't inherently need many.
We first conceived of Dynosaur as a plugin-based autoscaler (with GA and New Relic plugins to start with), but we've found the times we really need to scale fast are the times we have a lot of traffic generated from press stories etc (like this from today, if you will excuse the shameless plug: http://dealbook.nytimes.com/2014/01/21/a-start-up-run-by-fri...) and using the analytics live API allows us to react a little quicker than if we waited for New Relic to tell us our response times are getting slow. So far, we're happy enough with just a Google Analytics plugin.
One possible improvement would be to scale differently based on different traffic / performance metrics across the site. I think New Relic or other performance instrumentation would be very useful for that.
Just a thought. I know you abstracted it out the way you did so as not to tie it to just GA, but if GA is your analytics platform of record, it could be worth pursuing. Cheers!
Scaling should occur on actual traffic/user throughput statistics not on response time. Response times can increase for a variety of reasons, of which only one of is increased traffic load. For example, response times can increase based on back-end database contention or thread contention.
Of course whichever configuration is chosen, it is important to load test your application so you understand its performance profile and that all contention points are understood.