Re:Google Cloud Prediction API End of Life
by hackunomatter on Monday May 15, 2017 @02:04PM
(#14343668)
They _are_ giving a 1 year notice.
This. In GCP, they are handling these things transparently, professionally and proactively - usually giving you a personalized heads-up, alternatives and reminders as early as possible. Facebook on the other hand has been shutting down critical APIs under my systeme literally with a days' notice.
Does Facebook have paid APIs?
Good point. Definitely not as directly as Google, but in this case I guess I could make a fair point that their reporting and campaign management APIs for accessing campaigns we as a client pay 6-7 digit amounts per month for could be counted as such.
I think we agree that Google does a better job at shutting down APIs (paid or unpaid) than Facebook does. But I don't think people are bothered about the way Google shuts down services, but rather that they shut them down at all.
Which is one thing if your product is on a yearly (or quicker) release cycle. But it's a whole different level of pain if the project is in maintenance mode and the development team has already been reassigned to other projects.
People hate migration no matter what. Maybe Google should consider what how sustainable this service is going to be before selling it
If I had built a commercial product on that API how much money would this have cost me to move to the API. Also would the new API allow me to provide a better service to my customers or would it just be a pointless upkeep task.
If you build a product on an API you don't control, you'd better always have some realistic contingency plans on hand. A years notice is probably one of the easiest cases to handle out of the many scenarios that might force you to switch APIs.
Re:Google Cloud Prediction API End of Life
by joncampbelldev on Monday May 15, 2017 @06:59PM
(#14345957)
or build it on aws
> Q: What will happen with my existing models?
> A: You must recreate your existing Prediction API models using Cloud Machine Learning Engine. To learn more, please read our documentation about creating models on Cloud Machine Learning Engine.