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How Google Is Challenging AWS

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Re: How Google Is Challenging AWS

#161

Post by user5994461 »

obulpathi wrote: post #124
user5994461 wrote: post #61

Earlier quoted context omitted.

Author of the polemic post here! :D @ranman: You could start by disclosing that you work for AWS ;) I'll stand by my word. I can present the pricing comparison at reinvent 2017 if you'd like. 1) The equivalent instances are cheaper on Google. 2) Automatic discount is significantly superior and more customer friendly that reserved instances. 3) Google is faster or more flexible, usually both. That means that when you…

I completely agree with this. But, what I found more impressive about Google Cloud is that it requires a far fewer number of people to get things done compared to AWS. AWS believes in providing fundamental building blocks rather than frameworks. It takes a lot of time, money, skills, expertise and people to make it work. Google Cloud provides frameworks which are easy to use, secure by default, does not require tunin…

> what I found more impressive about Google Cloud is that it requires a far fewer number of people to get things done compared to AWS.

Yes. This is exactly why I keep pushing for Google Cloud.

I've found a way to talk about costs with understandable graphs, I didn't find a way yet to talk about the huge gains because it's easier to manage.

Re: How Google Is Challenging AWS

#162

Post by paulddraper »

dx034 wrote: post #143
paulddraper wrote: post #131

Earlier quoted context omitted.

https://techcrunch.com/2016/11/30/amazon-will-truck-your-mas...

> All this power fuels one terabyte per-second of data transfer speeds across a 40 gigabyte per-second connection. How is that supposed to work? Do they mean several 40gbit/s connections? Or did I misunderstand sth here?

Yes, several.

Re: How Google Is Challenging AWS

#163

Post by jonwayne »

Pigo wrote: post #150
jonwayne wrote: post #120

Earlier quoted context omitted.

We are indeed working on creating a standalone Task Queues service that will work across all hosting platforms. You can sign up for the alpha here: https://goo.gl/Ya0AZd (I work on the Python developer experience for Google Cloud Platform)

This is why I come to HN. Where else can you read an article about a high profile company, then find comments from people who work on what the article is about? Unless you guys are a brigade, it's pretty cool you happen to be browsing where the rest of us browse.

I am in Developer Relations so this is indeed part of my job. I'm glad we can be helpful.

Re: How Google Is Challenging AWS

#164

Post by jonwayne »

jay_kyburz wrote: post #134
waprin wrote: post #98

Earlier quoted context omitted.

Thanks for the feedback, not pointy at all. You're right my original comment was misleading, most of the GAE Standard samples are webapp2, but that's because it comes built-in to the platform and can be specified in the app.yaml, so webapp2 doesn't require people to `pip -t` to vendor Flask into the project. It might be worth revisiting if some of those samples should be in Flask or in both. 1) Guessing you already k…

No thoughts on the Python 3 issue?

(Not GP but also work on Python on GCP)

What was the specific Python 3 issue? I didn't see anything in your post specifically about Python 3.

Re: How Google Is Challenging AWS

#165

Post by olimashi »

halflings wrote: post #151
olimashi wrote: post #115

Earlier quoted context omitted.

I guess that's kind of my point about Ben's argument. Are pre-trained models going to be the "sustainable advantage" against AWS. I don't think so.

They definitely are for most customers: it is extremely expensive to gather and label enough data for a deep learning model to work correctly. It's very unlikely that you'll manage to configure and train your models + generate input data that Google lacks to make your model work much better than what Google already provide with their "generalist" API.

Say you are an insurance company and you want to use build a model that uses damage photos and meta data about car as a backstop to make sure that your repair shops aren't ripping you off.

In this case you already have a bunch of historical labeled data and a pre-trained model is useless to you application. It doesn't help you that the pre-trained model can recognized 10 different types of cats, you need a model trained on photos of damaged cars. Obviously the insurance companies own photo data will be more useful here because it's data about the application domain.

Google has collected a ton of photos for the purpose of image search and consumer photo organizing and that models utility has been tuned to those application area.

The key question is what is the overlap between all applications of images models and what photos Google has collected.

There will be for some but my guess is that those are the mission critical, I can only get this performance from Google cloud are few and far between.

I'm not saying there aren't any. Ben's article suggests that Google's data is somehow going to be a mission critical asset for all applications areas. Which I think is a terribly naive idea when it comes to ML.

Re: How Google Is Challenging AWS

#166

Post by olimashi »

brilliantcode wrote: post #99
olimashi wrote: post #74

I think Ben (who I generally think is right on) in this post misapprehends the effectiveness of generalized data for machine learning services and thus the effectiveness of this approach in Google’s strategy here. Perhaps the slide makers in Mountain View have the same misapprehension. 1 - Prediction API - you provide your own data there, so no data advantage from Google there. 2 - Cloud Natural Language API - the ef…

I think you've really pointed out a very important flaw in that as developers and startups we don't have terabytes of training data. However, I'm not sure who's in the leading edge here while Microsoft seems to suggest as the leader, but in the end machine learning, deep learning will be commoditized with enough training already baked in. ex. Need your web app translated flawlessly into Farsi? Just drop in farsi.js t…

Information embedded in a pre-trained model (Google isn't given out that data, just access to an artifact) is helpful if your application lines up to goals of the model. I think it's an open question how broad that alignment might be. It totally depends on the application.

You can control the app, but you don't have control over the model.

It will be useful to some apps but I don't think it is going to be the secret weapon in Google's fight against AWS as Ben's article suggests. It's a neat argument but I think it ignores the reality of applications and machine learning.

Re: How Google Is Challenging AWS

#167

Post by fhoffa »

ranman wrote: post #156
obulpathi wrote: post #124

Earlier quoted context omitted.

I completely agree with this. But, what I found more impressive about Google Cloud is that it requires a far fewer number of people to get things done compared to AWS. AWS believes in providing fundamental building blocks rather than frameworks. It takes a lot of time, money, skills, expertise and people to make it work. Google Cloud provides frameworks which are easy to use, secure by default, does not require tunin…

(I WORK FOR AWS) >Pokemon Go was able to scale to facebook level user engagement in a mere month time period with 4 backend engineers (and of course with lot of help from Google). I mean... did they? I was trying to play for weeks and I couldn't even login. I loved the game when I was able to play but I don't think they scaled seamlessly. Maybe that had nothing to do with the cloud provider and had more to do with th…

(I WORK FOR GOOGLE)

James Watters, Pivotal SVP says they saved 50% by moving from AWS to Google Cloud. For an 8 figures bill, that's a lot.

He said this 2 days ago at re:invent, FWIW.

- https://twitter.com/felipehoffa/status/804478208330514432

- https://www.youtube.com/watch?v=BUN0wx2e6Dc&t=287

Re: How Google Is Challenging AWS

#168

Post by foxylad »

detaro wrote: post #113
foxylad wrote: post #112

Earlier quoted context omitted.

We jumped on Appengine very early, and have never regretted it. It's remarkably stable, and not having to worry about the security issue du jour, scaling, or any other sysadmin stuff means we can concentrate on what we do best - building apps. I've been surprised how few people understand the value proposition, and how little competition there is. When I first heard about Azure I expected it to be PaaS, but it turned…

Isn't Azure Cloud Services pretty close to Appengine?

Not as I understand it. Both AWS and Azure force you to use machines - you may put them behind load balancers, and they may start up automatically when required, but you still need to design the system and do provisioning and plumbing to make your application working.

With Appengine, you don't know anything about the hardware of software your application is running on - you simply upload your app.

I haven't used Azure, so please correct me if I'm wrong. I believe AWS Lambda is the beginnings of a "serverless" environment - maybe Azure has an equivalent.

Re: How Google Is Challenging AWS

#169

Post by Rapzid »

dzhiurgis wrote: post #89
Rapzid wrote: post #49

Earlier quoted context omitted.

AWS has fallen flat in the past with cross-service initiatives. Tagging and IAM keys come to mind. I haven't personally used Google much but from what I hear their stuff is a bit more cohesive.. This new Org stuff might be a recent exception though; I haven't read through it all and tested it to know. Hopefully.

Reading GCP documentation is a delight. Reading AWS documentation feels like reading Salesforce's documentation.

Haha, I have never read Salesforce docs.. I must say though that I'm pretty happy with their docs. Sure, they are dense. However, they have most of what you need if you spend the time to read them. I MUCH prefer comprehensive docs to those that are lacking..

Re: How Google Is Challenging AWS

#170

Post by jay_kyburz »

jonwayne wrote: post #164
jay_kyburz wrote: post #134

Earlier quoted context omitted.

No thoughts on the Python 3 issue?

(Not GP but also work on Python on GCP) What was the specific Python 3 issue? I didn't see anything in your post specifically about Python 3.

>>> Want to use python3? That's cool, use the flexible environment. But it doesn't support taskqueues or many other features.

As far as I know there is no planned support for Python 3 in the standard env. I've been using GAE since 2010 but I'm a little uncomfortable continuing to writing new apps in Python 2.7 when they have a clear end of life date set now.

Given it might take you guys a year or two to support 3 after you decide to do it, then a year or two for me to port my apps over to python 3, my apps might be running for a while past the end of life date for Python 2.7.

Besides, I can't just keep writing 2.7 apps forever, so either I you guys have to update the SE to 3, or I need to start evaluating and comparing the flexible environment to what everybody else offers.

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