obulpathi

I have been running my website on AppEngine for 6+ years now. No problems at all.

One of the big advantages of Google Cloud platform is "Scalability".

Load balancers: Scale to millions of users seamlessly. No warming up, no tickets, ...

PubSub: You can send the whole Internet 10 times in a day through it. Google does that every day

Big Query: Its equivalent to spinning up a 100+ node cluster in a matter of seconds and it can process data at speeds of GB's of data per sec, I heard couple of use cases where the user was able to process at ~ 50 GB/s

Kubernetes: 1000's of nodes running 100's of thousands of containers.

Can't beat that!

True, while other providers focus on DevOps, Google Cloud strives for NoOps. They should do more marketing on that.

> I really hope Google adds Postgres to Cloud SQL at some point.

I too hope so.

Copying my comment from the other post (https://news.ycombinator.com/item?id=11160253), since this post is heading to the top

> Google has long been a thought-leader in this space, and this shows in the sophistication and quality of its data offerings. From traditional batch processing with Dataproc, to rock-solid event delivery with Pub/Sub to the nearly magical abilities of BigQuery, building on Google’s data infrastructure provides us with a significant advantage where it matters the most.

Big Data is the core strength of Google Cloud. Good to see this move by Spotify!

> What really tipped the scales towards Google for us, however, has been our experience with Google’s data platform and tools. Good infrastructure isn’t just about keeping things up and running, it’s about making all of our teams more efficient and more effective, and Google’s data stack does that for us in spades.

What I really really liked about Google Cloud is the ease of use. Spin up a VM, start Cloud shell, SSH into your instance, install a bunch of software and you will know what I mean. It's "Quality" Cloud.

> Google has long been a thought-leader in this space, and this shows in the sophistication and quality of its data offerings. From traditional batch processing with Dataproc, to rock-solid event delivery with Pub/Sub to the nearly magical abilities of BigQuery, building on Google’s data infrastructure provides us with a significant advantage where it matters the most.

Big Data is the core strength of Google Cloud. Good to see this move by Spotify!

> What really tipped the scales towards Google for us, however, has been our experience with Google’s data platform and tools. Good infrastructure isn’t just about keeping things up and running, it’s about making all of our teams more efficient and more effective, and Google’s data stack does that for us in spades.

What I really really liked about Google Cloud is the ease of use. Spin up a VM, start Cloud shell, SSH into your instance, install a bunch of software and you will know what I mean. It's "Quality" Cloud.

Google Cloud has MySQL for RDS. Agree that its lacks Oracle, MSSQL and Postgres. You can use managed Postgres by Enterprise if you like. If you are startup and running Oracle in AWS / Google Cloud, that's probably not a wise choice (You don't get the benefits Oracle, which is performance in AWS / Google Cloud). A startup using MSSQL in cloud? May for a niche purpose. If you are a big company with lots of legacy apps built with Oracle / Postgres / MSSQL, AWS makes more sense in short run.

Let's look at Google vs AWS from people's time:

* Ease of use: Google Wins(Cloud Shell, SSH into instance from browser). Its far easier to spin up an instance and manage it on Google Cloud than AWS with VPC mess.

* Platform Cohesivity: Google Wins (See the comparisio below)

* AWS has 2 storage solutions with different APIS: S3 and Glacier; Compare that to Google. Just one storage solution to serve all needs. You get a backed in CDN for free!

* AWS has two queuing systems (SQS and Kinesis) and still require the developer / admin to adjust the scaling of infrastructure. Google has just one Pub/Sub. You get push notifications on top. No need to tune knobs to get extra scale. It just works.

* AWS load balancers and persistent disks need warming up before high usage. If you are running a website on global scale, you need to use DNS geo load balancing on top. Google load balancers are global (as opposed AWS regional load balancers), no need of DNS tricks. No need of prewarming. Google persistent disks need no prewarming. You can mount a single persistent disk on multiple instance and share data easily.

* Security: Google encrypts data at rest and at wire by default. Try doing that on AWS. Google takes care of SSH key provisioning and management. AWS: You have to do it by yourself.

* AWS NATs and micro instance are known to be unreliable. Google has live migration. If something goes wrong with instance they work their magic behind the scenes so that you don't have to worry about migrating the instance to another physical host.

* Automation: Instance id are not global on AWS. Have fun creating maps and stuff inside CloudFormation templates. Google Cloud resources are global. All resources (images ids) have a global identifier. No more messing with zonal vs regional vs global resources.

Google Cloud can save money by saving your time too!

For startups planning to host their infrastructure on AWS, a better alternative might be to go with Google Cloud or other cheaper alternatives. This can significantly increase the startups runway, by lowering the operational costs. Google Cloud lacks some bells and whistles at this point but it shaves off 50% of your AWS bill.

Edit: Here is why Google Cloud can save 50% of your aws bill

"1X" is AWS

Compute:

VMs Price: 30% less + Per minute billing

Boot time: ¼ X

Network between VMs: Same region: 4X Across regions: 10X

BigQuery vs Redshift : ½ -20X

Big Data (Hadoop and Spark): 3X

Disks:

Read throughput: 1X Write throughput: 4X (Ephemeral); 2X (Persistent)

Local SSDs: Read throughput: 8X Writes throughput: 4X

Storage (S3): Throughput: 2X Latency: 3X (initial); ½ X (for subsequent reads)

A very interesting point! Cloud services cost tons of money. For companies running on AWS, a better alternative might be to migrate to Google Cloud or alter cheaper alternatives. Google Cloud lacks some bells and whistles at this point but it shaves off 50% of your AWS bill.

Marc Andreessen's comments showed the true color of the Facebook.

It would be awesome to have the code portable across various big data engines.

That is why I am sharing my findings in detail at out local meetup. If interested to know more, just shoot an email to me at Obulpathi at gmail. Also see my another comment above.

Google Cloud is not just App Engine now. Its pretty much the equivalent to aws in features. Let me also say I have PhD in Cloud and big data (graduated in 2013), worked for Amazon aws, worked for an rackspace for year and half, I was a core contributor to OpenStqck for the products OpenStack Poppy and OpenStack Zaqar. I hope you his puts se more weight behind my statements. If you are interested to know the details and why Google Cloud is better that aws for 90% of products, reach out to me.

CloudFormation is not very elegant. Things become complicated with the concept region, zonal resources (same AMI is represented by a different id in different region etc). Try Google Clouds's Deployment Manager. Functionally similar, but Google Cloud Deployment Manager is far easier (everything is a global resource), Jinja based templates (you get to write for's and if's, evaluate lists, dictionaries inside templates .. )

Try Kubernetes may be?

Look into Kubernetes. Since everyone is migrating to Docker and Microservices, Kubernetes provides a perfect fit to run your workloads on local premise and then migrate to Cloud when extra capacity is needed. It's opensource and supported by several vendors.

Please take a look into Google Cloud. It's now feature equivalent with AWS (https://cloud.google.com/docs/google-cloud-platform-for-aws-...). Google Cloud is better than AWS on all fronts other than Relational Databases. Google Cloud has MySQL only. AWS has MySQL, PostreSQL, Oracle, MSSQl. Rest of the services Google beats AWS by a fair and wide margin. I have done a fair amount of benchmarking Google vs AWS in past 3 months and conclusions are shocking. With Google Cloud, you can save about 50% of your bill (I have taken into account of reserved instances), huge increase in companies agility (Speed in taking decisions like capacity planning, instance type, sizing, zones, cluster sizes ... due to simplified infrastructure and pricing & performance wise too, blazing fast disks, live vm migration), far better security (data encryption at rest and on wire by default for all products, ssh key management). I am presenting my findings at our meetup group (http://www.meetup.com/Cloud-Big-Data-and-Data-Science-Group-...) in a couple of months. If any of you want to talk, reach out to me at obulpathi at gmail.

Google Cloud had a very impressive year. It has lots of killer features that AWS lacks. * Cloud Shell: Sweetest thing that happened since I started using cloud, no need to install dev tools * SSH right from web console * No need of managing ssh keys: Google takes care of it. If a user is removed, the users ssh keys are automatically revoked. * Security by default: Encryption at rest and on wire for all the products (Storage, Disks, SQL .. ) * Datalab (in alpha): Do data science from the browser (Jupyter as a service). * Pub/Sub + Dataflow: This is how I envision next generation Kafka + Samza to look like. * Container Engine, consistent performance, blazing fast disks and more.

Wondering if there are any plans to support Google Cloud?

I wish they add support for sending money internationally. That would be a killer feature for Google Wallet!

Does that mean MySQL patching and updates without downtime?

Not for me! They are pretty much comparable. Google's sustained use discounts mean no lock-in, lower price and flexibility too! Considering the fact that Google Cloud's disks are way faster than AWS's disks, your overall price is much lower with Google Cloud.

I agree with that.

Wow! Google is releasing products at a super fast speed! Go Google Cloud!

Oh Cool. Thanks for the link.

Looks like its neck to neck with AWS RDS MySQL. Has anyone done any benchmarks on performance?

Wondering how this can be used for specific content detection! Say I want to take pictures of a crop using a drone and analyse the pictures for pests and disesases etc ...

Google Container Engine is far ahead of AWS ECS. Google does not have a counterpart to Lambda and IAM. Block storage is far better with Google Cloud (Things like the ability to mount a drive read-only on multiple instances simultaneously make sharing data breeze. We ran into some weird race conditions related to inode pointers being modified with AWS EBS sometimes). And yes, it supports snapshots.

GCE > EC2, GCS > S3, Big query > Red Shift. Compute engine costs less and gives you more flops per buck compared to EC2. GCS has unified storage interface to all the storage classes. This makes developer life easy. Amazon has two different services (S3 and Glacier). With Redshift, you create a cluster of fixed size and pay for it whether you use it or not. With Big Query, you just pay for what you use.