> Does Google Cloud provide Machine Learning service?

Yes they do. [0]

> And this is common, as we've just seen people complain about Google Cloud 4 days ago.

To me, this is an isolated incident. On the other hand, seemingly every AWS customer of non-trivial size had to reboot a significant part of their machines in the last year because of Xen vulnerabilities (with no way to predict if you will land on a patched machine).

[0] https://cloud.google.com/prediction/docs

That's not true. AWS found a way to resolve the xen vulnerability without us having to reboot servers. # of servers I manage in AWS is >1k.

Ah, great. Apparently I didn't know they do. But again, being first doesn't automatically mean it's better. For instance, Sun's grid computing concept was earlier.

> To me, this is an isolated incident.

http://www.davidmturner.com/2013/07/26/gce-io-performance-su...

That's a 2 year old blog post from the time when GCE was still in beta.

Apart from that, noisy neighbors happen on any cloud platform, and as the author of the article said, those test were far from scientific.

http://robusttechhouse.com/google-prediction-api-review/ It ranked the worst comparing to AWS and Azure

I never said that they were any good, you just asked if it exists.

I personally don't know why one would use any of the GCE/AWS/Azure ML offerings apart for really small use cases (in which case you probably don't have enough data). Most businesses with an ML component (like my startup) need millions of predictions per day which would be crazy expensive on any of those platforms.

> For the longest time, it was only supporting Java and Python SDKs.

You are describing Google App Engine circa 2010. I recommend taking another critical look at what Google has available because it's quite competitive these days :)

Yep. Google hasn't met any of my needs when I play with it. I always end up back on AWS. Lambda is a stunning system IMHO.

I do like Google's new DB. It is like an easy to use spark w/ cassandra backend, all behind the scenes. Very nice.

Lambda looks awesome... I'm tethered to Azure, so the closest I get is Azure App Service which works, but not as elegantly... Dokku-alt is working pretty well (testing now) as a deployment system... was looking kubernetes and the like, but it's overkill for my needs.

Doesn't Amazon's mysql api fronted db work similar to google's?

I'm no expert on that. I thought it was just managed Mysql. The google stuff scales pretty well for startups who are starting to blow up.

Assuming you're both talking about Google Cloud SQL and AWS RDS, then with RDS you can actually choose between MySQL, PostgreSQL, SQL Server, Oracle, or Amazon Aurora which is supposed to be compatible with MySQL 5.6. Google Cloud SQL only seems to mention MySQL.

For scalability, RDS gives you up to 3TB storage (1TB for SQL Server, 64TB for Aurora) and DB instances with up to 244GB RAM, 32 vCPUs and 10Gigabit network, whereas it looks like Google Cloud SQL is 100GB and 16GB of RAM. It looks like Cloud SQL provides managed replication/failover as standard; with AWS this is optional, but simple to set up. (I use RDS; never tried Google Cloud SQL.)

(I have no connection with either company, beyond being a customer.)

Amazon RDS for Aurora is what I was thinking of as being similar to Google's Cloud SQL... they're both mySQL API layers over the top of their BigTable/distributed backends.

I was talking about BigQuery.

I was actually thinking of Amazon RDS for Aurora[1], which seems to be a mySQL api layer over Amazon's BigTable backend. and similar to Google Cloud SQL.

[1] http://aws.amazon.com/rds/aurora/

https://cloud.google.com/prediction has been out for years.

Uhm, yes, yes we do. https://cloud.google.com/prediction/docs

Nobody seriously uses AWS ML service, do they? This is the worst idea ever unless it's just to see how well it works, because you have very little control over the algorithms/model parameters.