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Conference Recap: Google Cloud Next

| by Richard Seroter Follow 2 Followers on Mar 14, 2017. Estimated reading time: 6 minutes | NOTICE: QCon.ai - Applied AI conference for Developers Apr 9-11, 2018, San Francisco. Join us!
Cloud enthusiasts from around the world attended Google Cloud Next to hear an update from the search giant. Three broad themes emerged from the many keynotes and 200+ sessions: service scale and maturity, usable machine learning, and enterprise-friendliness.
 
At the conference, Google executives announced many new and upgraded cloud services. As pointed out in TechRepublic, Google doubled the virtual machine vCPU ceiling and added bleeding-edge Intel processors.
On the compute side of things, Google Cloud customers will now have access to 64-core GCP VMs with up to 416 GB of memory. It was also noted in the presentation that Google is the first to have cloud services on the next-generation Intel Xeon Skylake processors.
Google is also expanding their cloud footprint. Urs Holzle, Google's senior VP of technical infrastructure, announced three new data center regions: California, Montreal, and the Netherlands. This represents a growth to eleven total regions comprised of fifty individual zones. According to Alphabet, Inc chairman Eric Schmidt, Google has plowed billions into cloud, so that customers don't have to.
We’ve put $30 billion into this platform,” Schmidt said. “Why try to replicate that? We’re here for real. This is an incredibly serious mission. The company has got both the money, the means, and the commitment to pull off a new platform of computation globally for everyone who needs it. Please don’t attempt to duplicate this. You have better uses of your money.
 
Image courtesy of Richard Seroter
 
The original cloud service from Google also got an upgrade. App Engine Flex has new language and Docker support.
App Engine now supports Node.js, Ruby, Java 8, Python 2.7 or 3.5, Go 1.8, plus PHP 7.1 and .NET Core, both in beta, all backed by App Engine’s 99.95% SLA. Our managed runtimes make it easy to start with your favorite languages and use the open source libraries and packages of your choice. Need something different than what’s out of the box? Break the glass and go beyond our managed runtimes by supplying your own Docker container, which makes it simple to run any language, library or framework on App Engine.
Google is known for web-scale data services, and at Google Cloud Next they made multiple enhancements to their database offerings. First, they expanded the Cloud SQL offering. Besides delivering fully-managed MySQL databases, Google now provides fully managed PostgreSQL instances. For Microsoft aficionados, Google announced the general availability of Microsoft SQL Server Enterprise images on Google Compute Engine. While it was announced a few weeks prior to the conference, Google Cloud Spanner was hard to miss. The CAP-theory-busting relational database played a prominent role in conference keynotes and sessions.
 
Open-source contributions and growth were front-and-center at the conference. Google highlighted the 287.024 commits by Googlers to open source projects on GitHub in 2016. They contributed to over 15,000 projects last year alone. One of the many Google sponsored initiatives is Kubernetes. At the conference, Google announced a partnership with Pivotal to bring BOSH—the release engineering tool that powers Cloud Foundry—to Kubernetes environments.
 
Google announced a handful of services infused with machine learning. The brand new Cloud Video Intelligence API uses machine learning to analyze videos and let developers search for objects. The new Data Loss Prevention API uses machine learning algorithms to identify and redact personally identifiable information (PII) from text or images. In an attempt to reduce the amount of time data scientists spend preparing data for analysis, Google also created Google Cloud Dataprep.
Google Cloud Dataprep is a new serverless browser-based service that can dramatically cut the time it takes to prepare data for analysis, which represents about 80% of the work that data scientists do. It intelligently connects to your data source, identifies data types, identifies anomalies and suggests data transformations. Data scientists can then visualize their data schemas until they're happy with the proposed data transformation. Dataprep then creates a data pipeline in Google Cloud Dataflow, cleans the data and exports it to BigQuery or other destinations.
Other machine-learning related announcements included the general availability of the Cloud Vision API, general availability of the Cloud Machine Learning Engine, and acquisition of Kaggle. Kaggle was described as "home to the world's largest community of data scientists and machine learning enthusiasts."
 
"Enterprise friendliness" was the final major trend that emerged from the conference. A parade of companies got on stage to tout Google's enteprise chops, and Google introduced a handful of capabilities catered to large businesses. One focus area was cost management.
Google also is targeting enterprises by talking about costs. According to Hölzle, businesses using other cloud service providers waste a lot of money by signing onto three-year leases to get the best pricing, but at the expense of being forced into fixed configurations that have to be paid for even if not all of the resources are used.
To address this, Google announced Committed Use Discounts. This program gives companies a significant discount when they prepay for use. While AWS offers discounts when customers reserve specific instance sizes, Google's discount is on total RAM and CPU. It's charged monthly and may be applied to a variety of machine and instance types. Google says that this model results in significant cost savings, without sacrificing flexibility.
In an analysis comparing Google and AWS pricing using those companies' discount structures in a "real world scenario," RightScale found that Google would be 28% to 35% cheaper than AWS for one- and three-year commitments.
Google also shared a new support model that differs from those of other cloud vendors. The cost for the Engineering Support program isn't derived from a company's monthly bill, but rather, is billed per support seat. Google says that this model provides more predictability, while offering greater freedom.
With this new model, you pay for only the roles your team needs and can decide what time-frame of support responses best suits the lifecycle stages of your applications and who in your organization needs to interact with support.
...
You can mix and match your support levels and spend to the stages of development maturity for your projects.
...
You can make adjustments month-to-month as your needs evolve, changing your support needs with shifts in your business.
 
Microsoft software is synonymous with "enterprise" and Google wants to make their cloud more attractive for these workloads. They announced multiple new capabilities that target Windows and .NET.
Google earlier vowed to build “a cloud environment for enterprise Windows that leads the industry.” The company also previously announced pre-configured images for Microsoft SQL Server Enterprise and Windows Server Core on Google Compute Engine. Stevens today announced the general availability of SQL Server Enterprise, plus the beta of .NET for Google App Engine and Container Engine.
Google executives also touted a handful of improvements to their business collaboration tools. This included Team-based storage drives, new governance controls for Drive content, and improvements to the Hangouts experience. The Google team also demonstrated Jamboard, a "whiteboard in the cloud" for distributed team collaboration.
 
Image courtesy of Richard Seroter
 
At the conference, many enterprise-friendly partnerships got announced. As is the rite of passage for any public cloud, Google announced a partnership with software giant SAP.
The companies announced that SAP will provide SAP HANA, its in-memory database and analytics engine, on Google’s cloud, an important step for Google as it looks to highlight large enterprises as both customers and partners on its GCP.
In the Fall of 2016, Google announced their Customer Reliability Engineering (CRE) program. At Google Cloud Next, Google revealed that Pivotal was the first CRE technology partner. Customers that run Pivotal Cloud Foundry on Google Cloud Platform "can feel comfortable that they’re going to build and deploy highly reliable systems by default." For customers looking for managed services on Google Cloud Platform, Google announced their new partnership with Rackspace.
 
Google wrote a blog post outlining "100 announcements from Google Cloud Next '17", and posted keynote and session videos on Youtube.

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Re: Eric Schmidt wants us to be gentle dependent people by Lord Fire

> "Please don’t attempt to duplicate this."
This sentence reads to me "please don't attempt to compete with us."

Which does mean they are afraid of the competition.

I'm looking forward to the upcoming interesting times.

Re: Eric Schmidt wants us to be gentle dependent people by Richard Seroter

That's one take.

Another is that it's extremely expensive for large enterprises to build and run data centers, let alone ones that are automation-centric, green, etc. Most cloud providers tout this message!

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